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--- title: Probiotics Supplementation Attenuates Inflammation and Oxidative Stress Induced by Chronic Sleep Restriction authors: - Yadong Zheng - Luyan Zhang - Laura Bonfili - Luisa de Vivo - Anna Maria Eleuteri - Michele Bellesi journal: Nutrients year: 2023 pmcid: PMC10054086 doi: 10.3390/nu15061518 license: CC BY 4.0 --- # Probiotics Supplementation Attenuates Inflammation and Oxidative Stress Induced by Chronic Sleep Restriction ## Abstract Background: Insufficient sleep is a serious public health problem in modern society. It leads to increased risk of chronic diseases, and it has been frequently associated with cellular oxidative damage and widespread low-grade inflammation. Probiotics have been attracting increasing interest recently for their antioxidant and anti-inflammatory properties. Here, we tested the ability of probiotics to contrast oxidative stress and inflammation induced by sleep loss. Methods: We administered a multi-strain probiotic formulation (SLAB51) or water to normal sleeping mice and to mice exposed to 7 days of chronic sleep restriction (CSR). We quantified protein, lipid, and DNA oxidation as well as levels of gut–brain axis hormones and pro and anti-inflammatory cytokines in the brain and plasma. Furthermore, we carried out an evaluation of microglia morphology and density in the mouse cerebral cortex. Results: We found that CSR induced oxidative stress and inflammation and altered gut–brain axis hormones. SLAB51 oral administration boosted the antioxidant capacity of the brain, thus limiting the oxidative damage provoked by loss of sleep. Moreover, it positively regulated gut–brain axis hormones and reduced peripheral and brain inflammation induced by CSR. Conclusions: Probiotic supplementation can be a possible strategy to counteract oxidative stress and inflammation promoted by sleep loss. ## 1. Introduction Sleep is a fundamental behavior that fills approximately one-third of a human’s lifetime and is critical for both physical and mental well-being [1]. Chronic sleep restriction (CSR), defined as insufficient/inadequate sleep over a prolonged period of time, is prevalent in contemporary society owing to professional obligations and lifestyle habits [2,3]. Epidemiological investigations have estimated that about $30\%$ of adults and adolescents regularly experience insufficient sleep [4]. CSR can lead to a range of brain deficits, including impaired attention and learning, and is associated with increased risk of neuropsychiatric disorders, but also cardiovascular diseases and metabolic alterations [4,5,6,7]. Growing evidence has demonstrated that CSR is linked to a low-grade inflammation, as reflected by increased inflammatory plasma cytokines and by the presence of other markers of inflammation in the brain, such as activation of microglia cells [8,9,10]. In addition, insufficient sleep can lead to the accumulation of intracellular reactive oxygen species (ROS) and/or reactive nitrogen species (RNS), resulting in an unbalance between the oxidant and antioxidant systems of the body [10,11]. Excessive ROS and RNS can react with carbohydrates, proteins, lipids, and DNA, and therefore, causes oxidative stress-related cellular damage and increased risk of disease, and in extreme cases, even death [11,12]. Sleep deprivation also affects energy homeostasis and has been associated with perturbed blood levels of peptide hormones, including ghrelin, leptin, and glucagon like peptide 1 (GLP-1) [13,14]. Probiotics have been attracting increasing interest in recent years for their ability to ameliorate inflammation-related illness. Numerous studies suggested that probiotics can effectively reduce both peripheral and central inflammation through multiple pathways. The underlying mechanism is associated with rebalancing of gut flora alteration, improvement of gut permeability, and modulation of immune function with lower production of proinflammatory cytokines [15,16,17]. Furthermore, probiotics can regulate microglia maturation and activity, and may also prevent neuroinflammatory processes, with positive impact in a series of diseases, such as inflammatory bowel disease, obesity, and neurodegenerative conditions [18,19,20]. Furthermore, it has been observed that probiotics and/or bacterial metabolites can interact with the host by modulating the level of both endogenous and exogenous ROS, ultimately improving oxidative status [21,22,23]. Long-term supplementation with multi-strain probiotic formulation exerted antioxidant and neuroprotective effects in a transgenic Alzheimer’s disease mouse model by activating the silencing information regulator 2 related enzyme 1 (SIRT1) pathway [24]. Several studies have provided evidence that sleep deprivation can perturb the composition of gut microbiota [25,26]. By inducing a breakdown of the intestinal epithelial barrier, sleep disruption may favor the passage of bacteria and their end-products, thus affecting the host and promoting immune reaction and inflammation [27]. Thus, sleep loss-associated inflammation may depend, at least in part, on an alteration of the gut microbiota physiology. There is also evidence that administration of probiotics can improve sleep. Manipulation of the gut microbiota through the administration of single or multi-strain probiotics can ameliorate sleep quality by reducing the Pittsburgh Sleep Quality Index (PSQI), a common indicator reflecting the impairment of sleep quality [28,29]. Here, we tested the hypothesis that chronic oral supplementation with a multi-strain probiotic formulation can reduce oxidative stress and inflammation induced by CSR. To this end, we administered a mixture of several probiotic strains (SLAB51) or vehicle in normal sleeping mice and in mice exposed to CSR, and we assessed the extent of oxidative damage and inflammation in the brain and at systemic level using biochemical and morphological methods. ## 2.1. Materials SLAB51 was provided by Ormendes SA (Jouxtens-Mezery, Switzerland, https://agimixx.net (accessed on 23 February 2023). SLAB51 is a multi-strain probiotic formulation that contains eight different live bacterial strains: *Streptococcus thermophilus* DSM 32245, *Bifidobacterium lactis* DSM 32246, *Bifidobacterium lactis* DSM 32247, *Lactobacillus acidophilus* DSM 32241, *Lactobacillus helveticus* DSM 32242, Lactobacillus paracasei DSM 32243, *Lactobacillus plantarum* DSM 32244, and *Lactobacillus brevis* DSM 27961. Polyvinylidene difluoride (PVDF) membranes and reagents for western blotting analyses, and the oxyblot protein oxidation protein detection kit for carbonyl groups introduced into proteins were obtained from Merck KGaA (Darmstadt, Germany). All antibodies used for western blotting, including nitrotyrosine, dityrosine, 4-hydroxynonenal (4-HNE), 8-oxoguanine DNA Glycosylase (OGG1), 8-oxo-2′-deoxyguanosine (8oxodG), ionized calcium-binding adapter molecule 1 (IBA-1), Interleukin 6 (IL-6), Interleukin 10 (IL-10), tumor necrosis factor alpha (TNFα), Interleukin 1 beta (IL-1β), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) antibody, were purchased from AbCam (Milan, Italy). Anti-IBA-1 for immunohistochemistry was purchased from Wako [019-19741], while fluorescent secondary antibodies were purchased from Thermo Fisher (Monza, Italy). ELISA Kits for IL-1β, TNF-α, IL-10, and IL-6 cytokines determination in plasma were obtained from Thermo Fisher Scientific Inc. (Italy). ELISA Kits for ghrelin, leptin, and GLP-1 measurement in plasma were from Merk-Millipore (Milan, Italy). Proteases inhibitors tosyl phenylalanyl chloromethyl ketone (TPCK) were from Merck KGaA (Darmstadt, Germany). Proteins immobilized on films were detected with the enhanced chemiluminescence (ECL) system (Amersham Pharmacia Biotech, Milan, Italy). A list of all the antibodies and their concentrations is given in Supplementary Table S1. ## 2.2. Animals Eight-week-old wild-type male B6128SF2 ($$n = 28$$, weight 25–35 g) mice were acquired from the Jackson Laboratory (Bar Harbor, ME, USA). All mice were housed in groups of four in environmentally controlled cages for the duration of the experiment (12 h light/dark cycle, light on at 8:00 P.M., the temperature of 24 ± 1 °C; food and water available ad libitum and replaced daily at 9:00 A.M.). The mouse body weight was measured before and after experimental conditions. All the experiments were performed according to the local Institutional Animal Care and Use Committee and the European Communities Council Directives ($\frac{2010}{63}$/EU). All appropriate measures were taken to minimize pain and discomfort in experimental animals. ## 2.3. Experimental Design and SLAB51 Administration Mice were divided into two weight-balanced groups, the water group (w) and the probiotic (p) group. Both the water and the probiotic groups were further separated into chronic sleep restriction (CSR-w, $$n = 7$$, CSR-p, $$n = 7$$) and normal sleep groups (S-w, $$n = 7$$, S-p, $$n = 7$$). CSR-p and S-p were administered with SLAB-51 dissolved in the drinking water, while CSR-w and S-w received only water. After 8 weeks of treatment, mice started the CSR experiment, during which the probiotic group was still fed with probiotics until the end of the experiment (Figure 1). The dosage of SLAB51 (200 billion bacteria/kg/day) was calculated using the body surface area principle based on our previous experiments. Before starting the experiment, we estimated the daily water intake and dissolved the proper amount of probiotics into the drinking water to reach the desired concentration [30]. We have previously checked the viability and stability of the probiotic formulation after dissolution in water at 21 ± 5 °C. Fluorescence microscopy was used to measure the proportion of vital bacteria, which indicated that 88 percent of the strains survived after 30 h under the aforementioned conditions [24]. The fresh drinking solution was changed every day. The body weights of mice were monitored every 2 weeks before treatment and subsequently weekly during the experiment to ensure normal experimental food consumption. ## 2.4. CSR Procedure CSR was achieved by an automated sleep deprivation chamber (Pinnacle Technology inc.). The effectiveness of this automated sleep deprivation method has been proved in previous experiments using EEG recording in rodents [31,32]. The procedure consists of a slow rotating bar placed at a short distance above the cage floor, lightly nudging the animal from sleep and encouraging low levels of activity until the animal maintains wakefulness on its own. Mice were sleep restricted for 7 consecutive days. To ensure a modest but persistent sleep restriction, mice were exposed to the rotating bar for 24 h/day at a velocity of 2 rpm (one turn each 30 s). Control mice were placed in the same sleep deprivation chambers and allowed to sleep undisturbed, except for 3 h/day (during the dark period, when mice are usually awake) during which the bar rotation was activated to expose the mice of this group to the experience of the bar movement and to the stress associated with it. Mice were housed in groups of four with ad libitum access to food and water or drinking bottle containing SLAB51. Animal behavior was daily assessed by direct visual observation. After 7 days, all mice were sacrificed between 9:00 and 11:00 A.M. to maintain the time of tissue collection within the same 2-h time of day window for all experimental groups. ## 2.5. Tissue Collection Mice were anesthetized with isoflurane (1–$1.5\%$ volume) and sacrificed by cervical dislocation. Brains were extracted—one hemisphere was processed for biochemical assessments, while the other one was immersed in cold $4\%$ paraformaldehyde dissolved in 0.1M phosphate buffer for fixation. Blood samples were collected from the abdominal aorta with a heparinized syringe connected to a 26 G needle and collected in EDTA tubes. They were centrifuged at 3500 rpm for 10 min at 4 °C, and the obtained plasma was promptly supplemented with Pefabloc 1 mM for subsequent cytokine ELISA detection. ## 2.6. Western Blotting Analyses Mouse brain tissue was homogenized in a solution of 50 mM Tris buffer, 150 mM KCl, 2 mM EDTA, and pH 7.5 (1:5 weight/volume of buffer). Brain homogenates were immediately centrifuged at 13,000× g for 20 min at 4 °C, and the supernatants were collected upon adding proteinase inhibitors (1 mM tosyl phenylalanyl chloromethyl ketone (TPCK) and Pefabloc). Protein concentration was determined using the Bradford protein assay [33]. Brain homogenates were analyzed through western blotting to investigate the following protein expression levels: 3-Nitrotyrsosine (3-NT), Dityrosine, 4-HNE, OGG1, 8-oxodG, and IBA-1. In detail, brain samples (30 μg total protein) were loaded on 10–$12\%$ sodium dodecyl-sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto polyvinylidene fluoride (PVDF) membranes. Following incubation with the specific antibodies, the immunoblot detection was performed with an enhanced chemiluminescence (ECL) western blotting ChemiDocTM System (Biorad, Milan, Italy). Molecular weight markers (6.5 to 205 kDa) were included in each gel. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used to ensure equal protein loading and to normalize western blot data. ChemiDoc acquired images or scanned autoradiographs (16 bit) were processed through ImageJ software (NIH) to calculate the background mean value and its standard deviation. The background intensity mean was then subtracted from the raw digital data to obtain a background-free image. For each band, the integrated densitometric value was determined as the sum of the density values for all pixels belonging to the analyzed band with a density value larger than the background standard deviation. The ratios of band intensities were calculated within the same western blot. All the calculations were carried out using Matlab (The MathWorks Inc., Natick, MA, USA). ## 2.7. Oxyblot Analysis The Oxyblot protein oxidation protein detection kit was used to determine protein carbonyl groups. According to the manufacturer’s instructions, brain homogenates (15 μg total proteins) were incubated at room temperature with 2,4-dinitrophenylhydrazine (DNPH) to generate 2,4-dinitrophenylhydrazone (DNP-hydrazone). The DNPH-derivatized samples were subsequently separated by SDS-PAGE and electroblotted onto the PVDF membrane. Then, the membrane was incubated with an anti-DNP antibody followed by a specific secondary antibody. The ECL system was utilized for the detection. To examine the same protein load, prior to incubation with an anti-DNP primary antibody, a reversible Ponceau stain was applied. The statistical significance was determined by comparing the densitometric values of oxyblot bands (oxidation level) to those stained with Ponceau red (protein content). ## 2.8. Plasma Cytokines Levels The levels of inflammatory cytokines IL-1β, TNF-α IL-6, and IL-10 in plasma were measured using an enzyme-linked immunosorbent assay NOVEX® ELISA kit (InvitrogenTM, Waltham, MA, USA), according to the manufacturer’s instructions and detected using a SpectraMax ABS Plus microplate reader (Molecular Devices, Germany). ## 2.9. Ghrelin, Leptin, and GLP-1 Determination Concentrations of gut–brain axis hormones were measured through ELISA in mouse plasma treated with protease inhibitors (Pefabloc and TPCK). We used a sandwich ELISA based on the capture of ghrelin, leptin, or GLP-1 (active form) in the plasma by specific monoclonal IgG. After the binding of a second biotinylated antibody to ghrelin, leptin, or GLP-1, the unbound material was washed. The remain complex was conjugated to horseradish peroxidase and the quantification of immobilized antibody-enzyme conjugates was performed by monitoring horseradish peroxidase activities in the presence of the substrate 3,3,5,5-tetra-methylbenzidine. The enzyme activity was measured spectrophotometrically by the increased absorbance at 450 nm, corrected from the absorbance at 590 nm, after acidification of formed products using a SpectraMax ABS Plus microplate reader (Molecular Devices, Germany). ## 2.10. Immunohistochemistry Brain tissue was allowed to fix for 10 days at 4 °C and then was cut on a vibratome in 50 μm coronal sections. Sections were rinsed in a blocking solution [$3\%$ bovine serum albumin (BSA) and $0.3\%$ Triton X-100] for 1 h and incubated overnight (4 °C) in the same blocking solution containing anti-IBA-1 (1:500). Sections were then probed with secondary antibodies: anti-rabbit Alexa Fluor 594 (1:600)-conjugated secondary antibodies. Sections were examined with a confocal microscope (Nikon Eclipse Ti, Tokyo, Japan). For IBA-1, microscopic fields ($$n = 5$$ per section, 1 section per mouse) were randomly acquired as 1024 × 1024-pixel images (pixel size, 561 nm; Z-step, 750 nm) in mouse frontal cortex using a UPlan FL N 40x objective (numerical aperture, 1.3). To improve the signal/noise ratio, two frames of each image were averaged. Image analysis. For IBA-1 staining, all analyses were performed on maximum-intensity projections (Z-project, Maximum Intensity function in ImageJ) of the 21 images constituting the Z-stack. Individual microglial cells were counted and manually segmented using the Single Neurite Tracing plug-in of FIJI [34]. Microglia process arborization was quantified using *Sholl analysis* by measuring the number of intersections between microglial branches and each Sholl ring. ## 2.11. Statistical Analysis Statistical analysis was performed using Graphpad prism software (La Jolla, CA, USA) and Matlab (The MathWorks Inc., Natick, MA, USA). One-way ANOVA was used for western blotting, ELISA experiments, and microglia density, while two-way ANOVA was used for microglial morphological branching analysis where the between-subject factor were the groups, and the within-subject factor were the Sholl rings. One or two-way ANOVA was followed by the Tukey post-hoc test. Alpha was set to 0.05 and appropriately corrected for multiple comparisons. ## 3.1. Probiotics Administration Ameliorates CSR-Induced Protein and Lipid Oxidation To verify the antioxidant effect of SLAB51, we measured the levels of protein and lipid oxidation by quantifying carbonyls, nitrotyrosine, dityrosine, and 4-HNE in the brain homogenates of all groups using western blotting. We found that levels of carbonyl groups, nitrotyrosine, dityrosine, and 4-HNE considerably increased in the CSR-w relative to the S-w group ($$p \leq 0.003$$, $$p \leq 0.0092$$, $$p \leq 0.0054$$, and $$p \leq 0.0118$$, respectively), confirming the reported role of CSR in promoting oxidative stress. SLAB51 administration reduced the CSR-induced effects on oxidative stress as the levels of nitrotyrosine, dityrosine, and 4-HNE were significantly lower in CSR-p than CSR-w ($$p \leq 0.0052$$, $$p \leq 0.0217$$, and $$p \leq 0.032$$, respectively) and no longer significantly different between CSR-p and S-p ($p \leq 0.05$), with the only exception of carbonyl levels that showed only a trend (CSR-p vs. CSR-w, $$p \leq 0.0666$$, Figure 2). ## 3.2. Probiotics Treatment Improves DNA Antioxidant Capacity In order to determine the effect of SLAB51 on DNA oxidation, the expression of the DNA base excision repair enzyme OGG1 and the DNA oxidation product 8-oxodG were measured in brain homogenates of all groups of mice. In the water group mice, CSR had no significant effect on OGG1 levels compared to control, whereas the probiotic treatment significantly increased OGG1 levels in both S-p ($$p \leq 0.029$$) and CSR-p mice ($$p \leq 0.0043$$), confirming the antioxidant effect of SLAB51 treatment. By contrast, we found higher levels of 8-oxodG in CSR-w mice compared to S-w (increased by 27 ± $9.4\%$; $$p \leq 0.049$$). This difference was no longer present in CSR mice treated with SLAB51 (CSR-p vs. S-w, $$p \leq 0.85$$; Figure 3). ## 3.3. Probiotics Reduces CSR-Induced Neuroinflammation and Systemic Inflammation We probed the effects of SLAB51 on neuroinflammation by measuring the expression level of several markers of inflammation, including IL-1β, TNF-α, IL-6, and IL-10 cytokines. In brain homogenates, CSR-w mice showed significantly enhanced expression of TNFα ($$p \leq 0.011$$) and IL-1β ($$p \leq 0.048$$), and attenuated expression of IL-6 (by 56 ± $9.8\%$, $$p \leq 0.023$$) relative to S-w. By contrast, SLAB51 treatment reduced the expression of IL-1β and TNF-α (CSR-p vs. CSR-w, IL-1β: $$p \leq 0.024$$; TNF-α: $$p \leq 0.0013$$), while it increased the expression of IL-6 (CSR-p vs. CSR-w, $$p \leq 0.014$$) and IL-10 (CSR-p vs. CSR-w, $$p \leq 0.017$$). We also measured the levels of the microglia-specific expression marker IBA-1 in brain homogenates. We found that CSR increased the expression of IBA-1 by 28 ± $8.9\%$ (S-w vs. CSR-w, $$p \leq 0.040$$) in the water group; this effect was blunted by probiotic administration (CSR-p vs. CSR-w, $$p \leq 0.013$$, Figure 4). At the systemic level, SLAB51 administration had no effect on plasma cytokines concentrations in S-w mice. Similar to the brain compartment, CSR significantly increased the plasma concentration of TNF-α ($$p \leq 0.005$$) and IL-1β ($$p \leq 0.015$$), while it decreased the concentrations of IL-6 ($$p \leq 0.002$$) and IL-10 ($$p \leq 0.001$$). Long-term SLAB51 supplementation effectively restored changes in the plasma cytokines levels in CSR mice (S-w vs. CSR-w, TNF-α: $$p \leq 0.0031$$; IL-1β: $$p \leq 0.0023$$; IL-6: $$p \leq 0.016$$; IL-10: $$p \leq 0.0089$$, Figure 5). ## 3.4. Probiotics Attenuate Morphological Microglial Changes Promoted by Sleep Loss Low-grade neuroinflammation can be associated with morphological changes of microglia, such as process retraction [35]. Hence, we quantified microglia process arborization using *Sholl analysis* (Figure 6). We manually segmented 2108 microglial cells in the frontal cortex (S-w, $$n = 606$$; S-p, $$n = 520$$; CSR-w, $$n = 383$$; CSR-p, $$n = 599$$) and found an effect of condition (F [3, 1289] = 4.355; $$p \leq 0.0046$$). Specifically, the administration of probiotics did not promote morphological changes in microglial cells in the normal sleeping mice (S-w vs. S-p, $$p \leq 0.4025$$; Figure 7A). When comparing CSR-w with S-w, we found a significant difference in the level of process arborization between these groups, with CSR-w mice showing a net decrease in the number of processes relative to S-w ($$p \leq 0.0032$$, Figure 7B). By contrast, the mice exposed to CSR that received probiotics showed comparable levels of process arborization to those of normal sleeping mice (CSR-p vs. S-p, $$p \leq 0.1359$$, Figure 7C) and significantly more than CSR-w ($$p \leq 0.0489$$; Figure 7D). Furthermore, we quantified microglia density, finding no changes in the density of cells in all groups of mice (F [3, 24] = 0.7390; $$p \leq 0.55$$; Figure 8). These results indicate that probiotic administration can attenuate the microglia morphological changes induced by sleep loss. ## 3.5. Probiotics Restored Blood Concentrations of Gut–Brain Axis Hormones To confirm the role of gut–brain axis modulation by probiotics, we measured the blood concentrations of key hormones involved in the gut–brain axis. Concentration of ghrelin, leptin, and GLP-1 were importantly modified by CSR. Specifically, we found an increase of ghrelin ($$p \leq 0.0025$$) and GLP-1 ($$p \leq 0.0068$$) and a decrease of leptin ($$p \leq 0.0004$$) in CRS-w relative to S-w. These changes were dampened by SLAB1 supplementation, with ghrelin, leptin, and GLP-1 concentration levels being comparable to those of the sleeping mice and statistically different from those of CSR-w mice (Ghrelin: $$p \leq 0.047$$; Leptin: $$p \leq 0.0045$$; GLP-1: $$p \leq 0.04$$, Table 1). ## 4. Discussion In this study, we found that a week of CSR induced oxidative stress in the mouse brain, promoted brain and systemic inflammation, and altered the gut–brain axis. The oral administration of SLAB51 boosted the antioxidant capacity of the brain, thus limiting the oxidative damage provoked by loss of sleep. Moreover, it restored the levels of gut–brain axis hormones and attenuated the development of peripheral and brain inflammation induced by CSR. Sleep is critical for maintaining body and brain functions, and insufficient sleep has been related to increased risk for a variety of diseases (e.g., type 2 diabetes, obesity, neurodegeneration, depression, anxiety, etc.), for which oxidative damage and inflammation have been proposed as potential underlying mechanisms [36,37,38]. Oxidative stress is the result of an unbalance between the production of reactive oxygen species (ROS) or reactive nitrogen species (RNS) and the antioxidant capacity of the cells [39]. Proteins, lipids, and DNA are major targets of ROS or RNS in biological systems [40,41]. There is no general consensus on the role of sleep loss in promoting oxidative stress [42]. Some studies found that sleep loss can either increase the production of oxidative radicals or lower antioxidant responses, while others did not find any change in oxidative stress markers or antioxidant capacity in peripheral blood or brain regions following sleep loss [43,44,45,46,47]. This discrepancy has been ascribed to the different sleep deprivation procedures (e.g., gentle handling vs. disk over the water) and the different duration of the sleep deprivation. While acute sleep loss appears to up-regulate the antioxidant cellular machinery, chronic loss of sleep weakens the antioxidant response, thus suggesting that extended wakefulness may be more likely associated with oxidative stress [38]. In our study, we found that 7 days of chronic sleep restriction were capable of increasing the brain levels of carbonyls, nitrotyrosines, and dityrosines, all well-established markers of protein oxidation. In parallel, we found augmented levels of 4-Hydroxynonenal (HNE), a major end product that is derived from the oxidation of lipids. Furthermore, studies on people over age 60 have shown that even one night of sleep loss can induce the expression of genes involved in DNA damage and aging [48]. Animal studies have also shown that sleep deprivation can cause genetic damage in a variety of organs [49]. The accumulation of DNA damage has been linked to DNA mutations, altered gene expression in the brain, and cognitive decline [50]. In our study, we observed increased DNA oxidation in CSR mice compared to control animals, as detected by the decreased OGG1 expression and the increased 8-oxodG levels in the brain homogenates. We also found increased plasma levels of ghrelin in the CSR-w group. Besides its role in regulating appetite, ghrelin has been recently proposed as a systemic oxidative stress sensor [51]. Collectively, these data suggest that chronic sleep loss can lead to oxidative damage of proteins, lipids, and DNA. Sleep loss has also been repeatedly associated with heightened inflammation. Increased plasma levels of numerous cytokines including IL-1, TNF-a, IL-6, IL-17, nuclear factor-kappa B (NFkB), and altered numbers and activity of macrophages and natural killer cells have been found after both acute and chronic sleep deprivation in healthy individuals [52,53,54]. These findings were also supported by preclinical studies, in which the inflammatory markers IL-1, IL-6, and TNF-a were found elevated in the peripheral blood and several brain regions [55,56]. While the mechanisms through which sleep loss leads to an inflamed state are unclear, oxidative stress may contribute to inflammation by stimulating the release of proinflammatory cytokines, including TNF-α and IL-1β [38]. Furthermore, ROS and RNS can activate other inflammatory mediators such as NF-kB and vascular cell adhesion molecule-1 (VCAM-1) [57]. In this study, CSR was associated with an increase of TNF-α and IL-1β and a decrease of IL-6 and IL-10 in the brain and peripheral blood. While IL-10 is a well-recognized anti-inflammatory cytokine, the role of IL-6 in sleep deprivation-related inflammation remains unclear. Some studies showed that total sleep deprivation or sleep fragmentation led to increases in plasma IL-6 levels, which were interpreted as a marker of inflammation [58,59]. However, other works demonstrated that IL-6 has a crucial anti-inflammatory role in local and systemic inflammatory responses by modulating levels of proinflammatory cytokines [60,61]. Our previous study showed that CSR could activate microglia without affecting the levels of cytokines in the cerebral spinal fluid [8]. Sustained microglia activation could potentially increase the brain’s vulnerability to various types of damage [8]. In this study, we confirmed the activation of microglia induced by CSR, but we also found an increase of IBA-1 expression in the brain of CSR mice. IBA-1 has been demonstrated to have a role in actin-crosslinking of microglial membrane ruffling, and its expression relates to the microglial activation since membrane ruffling is required for the shift from quiescent ramified to activated amoeboid microglia [62]. All together, these findings confirm that sleep loss is associated with increased systemic and brain inflammation. Probiotics are live microorganisms intended to change the composition of the flora of the gastrointestinal tract of the host and provide health benefits when consumed [63]. The mechanisms through which probiotics improve health are numerous and include the modulation of the host immune system, modification of the intestinal microbiota, protection against physiological stress, pathogen antagonisms, and improvement of the barrier function of the gut epithelium [64]. In this study, we used SLAB51, a multi-strain probiotic supplementation. Previous research has shown that SLAB51 could restore normal eubiosis in animal models of neurodegenerative disorders [30,65], while it had little/no effect on the microbiota of healthy wild-type mice [30]. The effects of probiotics on inflammation and oxidative stress biomarkers have been extensively investigated in animal models and clinical trials. Most recent studies confirmed the role of probiotics in decreasing the levels of CRP, high-sensitivity(hs)-CRP, and TNF-a levels [66,67,68,69]. Previous work using SLAB51 found that this formulation increased the relative abundance of gut anti-inflammatory bacteria such as Bifidobacterium spp. and decreased the concentrations of pro-inflammatory Campylobacterales, consequently regulating inflammatory pathways. Moreover, it promoted the proliferation of bacteria that produced short-chain fatty acids (SCFAs). It is, thus, possible that the enriched gut concentration of anti-inflammatory and neuroprotective SCFAs contributed to reduce the plasma levels of pro-inflammatory cytokines and to enhance the concentrations of anti-inflammatory cytokines [30]. Consistent with these results, a recent meta-analysis evaluating 42 controlled trials demonstrated that levels of several pro-inflammatory cytokines (i.e., IL-12, IL-4, etc.) were significantly lowered by probiotic supplementation [68]. By contrast, levels of IL-10, glutathione, nitric oxide, total antioxidant status, and total antioxidant capacity were significantly increased with probiotics administration [66,67,70,71,72]. It is worth noting, however, that several studies have reported no effect of the probiotic treatment in regulating inflammation or the oxidative status relative to the placebo group [68,70,73,74]. The anti-inflammatory effects of probiotics are not limited to the gut. Indeed, chronic low-grade inflammatory processes are now thought to play an etiological role in the pathogenesis of several neuropsychiatric disorders and probiotics have been proposed as potential compounds capable of mitigating these pathologies by modulating the immune-to-brain signaling and alleviating the chronic immune activation in the brain [75,76]. In that perspective, administration of multi-strain probiotics—including SLAB51—have resulted in reduced neuroinflammation in animal models of Alzheimer’s disease [24,77,78,79]. Moreover, a recent meta-analysis of 5 studies involving 297 subjects has found improved cognitive performance in AD or MCI patients following probiotic supplementation, likely through decreasing inflammatory and oxidative stress levels [80]. In our study, we found that administration of SLAB51 per se affected neither the levels of inflammatory cytokines in the brain and plasma nor the morphology of microglia cells of sleeping animals (S-p similar to S-w), whereas it induced the overexpression of OGG1 in both sleeping and sleep restricted mice (S-p and CSR-p). Thus, SLAB51 supplementation not only did not trigger an inflammatory response per se, but it enhanced cellular antioxidant capacity. More importantly, when administered in mice later exposed to CSR, it contrasted the rise of central and peripheral inflammation and oxidative stress levels, thus indicating that probiotics can abolish the immune and inflammatory response associated with loss of sleep. These findings are consistent with a recent study carried in acutely sleep-deprived monkeys, where supplementation of GABA-producing probiotics reduced the proinflammatory cytokines IL-8 and TNF-alpha, with no effect on the circulating levels of IL-6 and IL-10 [81]. Similarly, supplementation of Lacticaseibacillus paracasei was capable of restoring memory deficits in mice subjected to partial sleep deprivation [82]. Although it was not directly tested in this study, it is possible that the effect on cognition was mediated by the immunomodulation properties of probiotics. The mechanism through which probiotics exert their protective role on neuroinflammation is unclear, but it could be attributed, at least in part, to their direct effects on the gut–brain axis [83,84,85]. For example, numerous reports over the past decades have described ghrelin to be a potent anti-inflammatory mediator [86], while high levels of leptin have been related to inflammation [87]. In this regard, we found that probiotic supplementation restored nearly normal plasma concentration of ghrelin, leptin, and GLP-1, whose levels were remarkably altered by CSR. Although indirect, this evidence supports the hypothesis that probiotics can modulate neuroinflammation via the production and release of specific gut hormones [83,84,85,86,87]. In humans, probiotics have been mostly administered to improve sleep quality rather than counteract the effects of sleep loss. A recent systematic review analyzed a total of 14 studies finding that probiotics supplementation significantly reduced Pittsburgh Sleep Quality Index (PSQI) score (i.e., improved sleep quality) relative to baseline, while no significant changes were reported for other subjective sleep quality metrics or objective sleep parameters, such as efficiency and latency. Although not significant, subsequent analysis found that healthy participants had a greater benefit on sleep quality than those with a medical condition and the use of single-strain probiotics was better than multi-strain probiotics in improving sleep quality [88]. The possibility of counteracting the deleterious effects of sleep deprivation with probiotics is intriguing and could be relevant for populations who by necessity have a disrupted sleep schedule, such as shift workers. The few available studies along this direction showed that probiotics have the potential to reduce the magnitude of the stress response that anticipates the beginning of the night shift [89] and alleviate anxiety and fatigue in shift workers [90], but there are still no available data on the role of probiotics in reducing the proven long-term risk in developing shift work-associated diseases. A number of limitations to the study should be acknowledged. First, we did not use oral gavage to administer probiotics to mice, but we dissolved SLAB1 in the drinking water. This methodological aspect could have generated variability in the intake of probiotics within the probiotic group. However, we treated the animals for an overall 9 weeks (8 weeks before starting the sleep experiment and during the week of the experiment). This long treatment duration ensured adequate intake of probiotics and may have limited heterogeneous effects among animals. Additionally, since we administered probiotics before and during the CSR, we currently cannot distinguish whether probiotics had preventive or therapeutic effects on CSR-induced inflammation and oxidative stress, and future research with a different experimental design is needed to clarify this ambiguity. Furthermore, we did not assess cognitive functions in our mice, and therefore, we do not know whether probiotics were able to restore potential sleep loss-associated cognitive deficits and whether these effects were related to systemic and brain inflammation. Finally, we only studied male mice, and it is possible that probiotics exerted a different influence on inflammation in female mice, although other studies have found that sex had only a minor effect on the immune modulation of probiotics [91]. ## 5. Conclusions Our study provides direct support to the growing evidence that probiotics can attenuate oxidative stress and inflammation in the brain and at systemic level via the gut-brain axis. In addition, it indicates that probiotic supplementation can represent a viable strategy to counteract oxidative stress and inflammation related to sleep loss, thus possibly limiting its negative consequences on health and well-being. ## References 1. Scott A.J., Webb T.L., Martyn-St James M., Rowse G., Weich S.. **Improving Sleep Quality Leads to Better Mental Health: A Meta-Analysis of Randomised Controlled Trials**. *Sleep Med. Rev.* (2021) **60** 101556. DOI: 10.1016/j.smrv.2021.101556 2. 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--- title: Burden of Illness beyond Mortality and Heart Failure Hospitalizations in Patients Newly Diagnosed with Heart Failure in Spain According to Ejection Fraction authors: - Carlos Escobar - Beatriz Palacios - Victoria Gonzalez - Martín Gutiérrez - Mai Duong - Hungta Chen - Nahila Justo - Javier Cid-Ruzafa - Ignacio Hernández - Phillip R. Hunt - Juan F. Delgado journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054096 doi: 10.3390/jcm12062410 license: CC BY 4.0 --- # Burden of Illness beyond Mortality and Heart Failure Hospitalizations in Patients Newly Diagnosed with Heart Failure in Spain According to Ejection Fraction ## Abstract Objective: The objective of this study was to describe the rates of adverse clinical outcomes, including all-cause mortality, heart failure (HF) hospitalization, myocardial infarction, and stroke, in patients newly diagnosed with HF to provide a comprehensive picture of HF burden. Methods: This was a retrospective and observational study, using the BIG-PAC database in Spain. Adults, newly diagnosed with HF between January 2013 and September 2019 with ≥1 HF-free year of enrolment prior to HF diagnosis, were included. Results: A total of 19,961 patients were newly diagnosed with HF ($43.5\%$ with reduced ejection fraction (EF), $26.3\%$ with preserved EF, $5.1\%$ with mildly reduced EF, and $25.1\%$ with unknown EF). The mean age was 69.7 ± 19.0 years; $53.8\%$ were men; and $41.0\%$ and $41.5\%$ of patients were in the New York Heart Association functional classes II and III, respectively. The baseline HF treatments included beta-blockers ($70.1\%$), renin–angiotensin system inhibitors ($56.3\%$), mineralocorticoid receptor antagonists ($11.8\%$), and SGLT2 inhibitors ($8.9\%$). The post-index incidence rates of all-cause mortality, HF hospitalization, and both combined were 102.2 ($95\%$ CI 99.9–104.5), 123.1 ($95\%$ CI 120.5–125.7), and 182 ($95\%$ CI 178.9–185.1) per 1000 person-years, respectively. The rates of myocardial infarction and stroke were lower (26.2 [$95\%$ CI 25.1–27.4] and 19.8 [$95\%$ CI 18.8–20.8] per 1000 person-years, respectively). Conclusions: In Spain, patients newly diagnosed with HF have a high risk of clinical outcomes. Specifically, the rates of all-cause mortality and HF hospitalization are high and substantially greater than the rates of myocardial infarction and stroke. Given the burden of adverse outcomes, these should be considered targets in the comprehensive management of HF. There is much room for improving the proportion of patients receiving disease-modifying therapies. ## 1. Introduction Heart failure (HF) is associated with a high risk of mortality and frequent hospital admissions [1]. In fact, around $20\%$ of patients with a recent diagnosis of HF are expected to die during the following year [2]. HF hospitalizations are a common complication of patients with HF. HF hospitalizations represent an inflection point in the evolution of HF, as vulnerability to complications is particularly high during the first months after hospitalization for HF [3,4]. However, patients with HF are not only at risk of cardiovascular death and HF hospitalization but also other adverse outcomes, such as major adverse cardiovascular events (MACEs), myocardial infarction, and stroke [4]. Thus, HF remains a frequent complication of patients with prior myocardial infarction [5], and it is also common in the overall population with coronary artery disease [6]. In fact, coronary artery disease is one of the main risk factors for HF development [7]. Of note, chronic HF is a risk factor for the development of ischemic stroke by itself, beyond its association with atrial fibrillation [8,9]. In this context, the early initiation of guideline-directed HF therapy is crucial to decrease the comprehensive HF burden, including not only the risks of HF hospitalizations and death but also the risks of other adverse events [5,6,7,8,9]. However, only a few HF clinical trials have analyzed the effects of active treatments on endpoints other than HF hospitalizations and cardiovascular death, including MACEs, myocardial infarction, and stroke [10]. However, it is important to ascertain whether there are differences in the clinical profile, management, and risk of events (including MACEs, myocardial infarction, and stroke), not only in the whole HF population but also stratified by HF EF phenotypes (i.e., HF with a reduced ejection fraction (HFrEF), HF with preserved EF (HFpEF), and HF with mildly reduced EF (HFmrEF)). However, this has not been well studied, and more information is warranted [11,12,13]. The objective of this study was to describe the clinical characteristics of the population and the incidence rates of HF hospitalization and MACEs (including myocardial infarction, stroke, and all-cause mortality) in an overall incident HF cohort of newly diagnosed patients, who were also stratified by EF subgroup. In addition, the factors associated with increasing the risk of HF hospitalization and death, as well as the evolution of HF treatment over time, were determined. ## 2. Methods This was a retrospective observational cohort study that analyzed the information provided in the BIG-PAC database in Spain. This database collects information from integrated and computerized medical records of a total of 1.8 million patients in 7 Spanish Autonomous Communities. Data are available for the year 2012 onwards and are updated monthly. Many studies have demonstrated the validity and applicability of this database [13,14,15]. This study was approved by the Investigation Ethics Committee of HM Hospitals in Madrid, Spain. No informed consent was required, as this study was a secondary data study using fully anonymized data. Patients aged 18 years or older, with at least 1 year of enrollment in the database prior to the index date, were included. HF was defined as having at least 1 new HF diagnosis (ICD-9/ICD-10 codes) in the inpatient (any position) or outpatient records between 1 January 2013 and 30 September 2019. The index date was the date of the first HF diagnosis. Patients with chronic stage V kidney disease who required dialysis at any time before the index date were excluded from the study. Patients with HF were classified into different phenotypes according to left ventricular EF: HFpEF was defined as an EF value of ≥$50\%$ (subtype 1: EF 50 to < $60\%$; subtype 2: EF ≥ $60\%$), HFrEF was defined as an EF value of ≤$40\%$, HFmrEF was defined as an EF value > $40\%$ and < $50\%$, and HF with an unknown EF (HFuEF) included patients without echocardiograph data. At baseline, biodemographic data, cardiovascular risk factors, vascular disease, and other comorbidities, as well as newly prescribed HF treatments, were recorded. The baseline clinical characteristics, treatments, and outcomes were analyzed in the overall HF population and according to EF phenotype. If a patient was prescribed 2 different drug classes on the same date or took a combination of pills, they were included in both treatment classes. The evolution of HF treatment within the first year after the index date was determined. The primary outcome was a composite of HF hospitalization and all-cause mortality and its individual components. HF hospitalizations were determined as an inpatient admission (primary or any diagnosis) with an ICD-10 code for any HF. Furthermore, the occurrences of 2 additional adverse clinical outcomes, i.e., myocardial infarction, stroke, all-cause mortality, and its composite (MACEs) were also analyzed from 1 to 7 years from the index date. ## Statistical Analysis HF incidence (per 1000 person-years) was calculated by dividing the number of patients who received a new HF diagnosis during the study period by the total person-time contributed by all adult patients in the database without prevalent HF. The incidence rates of clinical outcomes were calculated in the overall cohort of patients with HF and according to EF phenotype. HF incidence was calculated in the overall cohort of patients with HF and according to EF phenotype. The baseline characteristics of the patients were summarized using descriptive statistics. For continuous variables, the number of patients, mean, and standard deviation were reported. Frequency distributions with quantity and percentages were reported for categorical variables. To analyze the relationship between the continuous variables amongst the EF phenotypes, a 2-sample t-test was used for variables normally distributed, and the Mann–Whitney U test was used for those non-normally distributed. The chi-square test was used for categorical variables. Wald contrast was used for the incident rates and event rates. The McNemar test was used to compare HF treatment changes over time. A statistical significance level of 0.05 was applied. The incidence rates of clinical outcomes were calculated as the total number of new events of interest divided by the total person-time at risk. Patients were followed from the index date until the earliest occurrence of the event of interest, death, loss to follow-up, or study end date. The incidence rates were reported per 1000 person-years over the entire follow-up duration and by year after the index date. The incidence rates and cumulative incidence rates for the primary endpoint of the composite of HF hospitalization and all-cause mortality, as well as for the composite of MACE outcomes (myocardial infarction, stroke, and all-cause mortality) and individual components, were calculated for the overall HF cohort and stratified by EF phenotype. Kaplan–Meier plots were constructed to illustrate the time to the first event (in days). The recurrent event rates (per 1000 person-years) were calculated for myocardial infarction, stroke, and HF hospitalizations. A minimum of 30 days was required between outcome events of the same type for them to be considered separate events. A multivariable Cox proportional hazards regression model was used to assess the associations between the baseline clinical characteristics and treatments and the risk of the composite endpoint of hospitalization for HF and all-cause mortality in the overall HF cohort. The regression analyses consisted of a 2-step assessment: in the first step, univariable Cox models were constructed for each baseline covariate, and unadjusted hazard ratios and the corresponding $95\%$ confidence intervals were calculated for each covariate. Covariates with a univariate p-value of <0.1 were included in the multivariate models. After all covariates were identified, they were combined in a multivariable regression model using stepwise backwards selection to exclude covariates that became nonsignificant. All data were analyzed using the statistical package SPSS v25.0 (SPSS Inc., Chicago, IL, USA). ## 3. Results The incidence of HF over the study period was 3.2 per 1000 person-years (1.4 for HFrEF, 0.9 for HFpEF, 0.2 for HFmrEF, and 0.8 per 1000 person-years for HFuEF), increasing from 2.7 per 1000 person-years in 2013 to 3.7 per 1000 person-years in 2018. The baseline characteristics and treatments in the incident 2013–2019 HF cohort are presented in Table 1. Of the 19,961 patients, $43.5\%$ had HFrEF, $26.3\%$ had HFpEF, and $5.1\%$ had HFmrEF; in the remaining $25.1\%$, EF was unknown. Overall, the mean age was 69.7 ± 19.0 years; $53.8\%$ were men; and $41.0\%$ and $41.5\%$ were in the New York Heart Association (NYHA) functional classes II and III, respectively. The most common comorbidities were hypertension ($59.1\%$), coronary artery disease ($33.1\%$), atrial fibrillation ($28.2\%$), type 2 diabetes ($27.6\%$), and chronic kidney disease ($26.7\%$). The baseline HF treatments included beta-blockers ($70.1\%$), renin–angiotensin system inhibitors ($56.3\%$), mineralocorticoid receptor antagonists ($11.8\%$), and sodium–glucose cotransporter-2 inhibitors (SGLT2is) ($8.9\%$). There were relevant differences in the clinical profiles and HF management according to HF phenotype. Compared to the patients with HFrEF, the patients with HFpEF were older (73.4 ± 18.6 vs. 65.6 ± 18.6 years; $$p \leq 0.001$$), more predominantly female ($66.2\%$ vs. $34.1\%$; $p \leq 0.001$) and had a higher prevalence of atrial fibrillation ($35.5\%$ vs. $23.5\%$; $p \leq 0.001$) at baseline. The patients with HFrEF had a higher prevalence of type 2 diabetes ($25.8\%$ vs. $28.3\%$; $p \leq 0.001$), chronic kidney disease ($22.5\%$ vs. $30.8\%$; $p \leq 0.001$), coronary artery disease ($26.2\%$ vs. $38.7\%$; $p \leq 0.001$), stroke ($6.0\%$ vs. $12.3\%$; $p \leq 0.001$), and peripheral artery disease ($3.2\%$ vs. $5.1\%$; $p \leq 0.001$) at baseline. The prevalence of comorbidities in the patients with HFmrEF was intermediate, falling between that of the patients with HFrEF and that of the patients with HFpEF. Among the patients with HFpEF those with EF $50\%$ to < $60\%$ had higher rates of diabetes ($38.3\%$ vs. $24.0\%$; $p \leq 0.001$), prior myocardial infarction ($17.8\%$ vs. $11.0\%$; $p \leq 0.001$), stroke ($8.1\%$ vs. $4.9\%$; $p \leq 0.001$), and peripheral artery disease ($4.6\%$ vs. $2.5\%$; $p \leq 0.001$), compared to those with EF ≥ $60\%$. Similarly, prescriptions of disease-modifying HF drugs (i.e., beta-blockers, renin–angiotensin system inhibitors, mineralocorticoid receptor antagonists, and SGLT2is) were more frequent in patients with HFrEF than in those with the other HF EF phenotypes. All HF drugs were significantly more frequently prescribed in the patients surviving to the 12-month followup regardless of HF phenotype. However, all HF drugs were more commonly taken among patients with HFrEF during the whole followup period (Table 2 and Supplementary Table S1). In all patients with HF, the incidence rates of all-cause mortality, HF hospitalization, and the combined endpoint of HF hospitalization and all-cause mortality were 102.2 ($95\%$ CI 99.9–104.5), 123.1 ($95\%$ CI 120.5–125.7), and 182 ($95\%$ CI 178.9–185.1) per 1000 person-years, respectively. The rates of myocardial infarction, stroke, and MACEs were 26.2 ($95\%$ CI 25.1–27.4), 19.8 ($95\%$ CI 18.8–20.8), and 148.9 ($95\%$ CI 145.9–151.9) per 1000 person-years, respectively. Although events were common in all HF EF phenotypes, the incidence rates were higher in the patients with HFrEF. Among the patients with HFpEF, although the rates of HF hospitalization and the composite outcome of HF hospitalization and mortality was independent of EF, the rates of myocardial infarction, stroke, all-cause mortality, and MACEs were more common in the patients with EF 50–$60\%$ compared to those with EF ≥ $60\%$ (Table 3, Figure 1, and Supplementary Figure S1). The evolution of adverse outcomes over the 7-year follow-up from the index date is shown in Supplementary Table S2. The factors associated with the risk of the composite outcome hospitalization of HF and all-cause mortality in the overall HF cohort are shown in Figure 2. HFrEF (vs. HFmrEF or HFpEF), an increased age, the male sex, prior myocardial infarction, unstable angina, percutaneous or surgical revascularization, stroke, type 2 diabetes, COPD, and the use of digoxin were associated with a higher risk of the composite outcome. ## 4. Discussion This study shows that, in Spain, patients with HF are of older age (nearly $60\%$ of all patients with HF in this study were older than 65 years), particularly those with HFpEF, and that they have many comorbidities. The rates of HF hospitalization, all-cause mortality, and their composite were particularly high. Although lower, the rates of myocardial infarction and stroke were also significant. Although the prescription of HF drugs has improved in recent years, many patients were not taking the disease-modifying HF drugs by the end of the follow-up. Previous studies have shown that the current incidence of HF in *Europe is* around 3–$\frac{5}{1000}$ person-years [1,4,16]. In our study, we found an incidence of 3.2 per 1000 person-years for all HF EF phenotypes, in line with previous data, with the annual incidence increasing over the study period. The number of patients with prevalent HF is predicted to increase in the coming years because of population aging and patients with HF surviving longer as a result of improved treatment options [17,18]. Our study included nearly 20,000 patients newly diagnosed with HF. Among those patients with known EF, $58.1\%$ had HFrEF, $35.1\%$ had HFpEF, and $6.8\%$ had HFmrEF. Although there were relevant disparities in the clinical profiles according to EF phenotype (i.e., the patients with HFpEF and HFmrEF were older and more commonly women than the patients with HFrEF, as expected), overall, the patients with HF were old and had many comorbidities. The relative proportions of the EF phenotype vary considerably across studies, as do the clinical profiles. This may be related to the clinical setting that patients attend, as well as reflecting geographic differences. Thus, patients of cardiologists are usually younger and have higher rates of HFrEF than patients of internal medicine departments, who are usually older and more likely to have HFpEF [11,12,13,14,19]. The BIG-PAC database collects information from integrated and computerized medical records from both inpatient and primary care [13,14,15]. Our data provide a more balanced and comprehensive picture of the Spanish population newly diagnosed with HF. The primary outcomes of our study, all-cause mortality and HF hospitalization, were designed to be similar to the outcomes of recent clinical trials [10,20,21,22,23,24]. The rates of all-cause mortality and HF hospitalization in this real-world population (10.2 and 12.3 per 100 patient-years, respectively) are higher than those reported in recent trials [10,20,21,22,23,24]. In a pooled analysis of the DAPA-HF and DELIVER trials, in the placebo arm, the rates of all-cause mortality and total HF hospitalizations per 100 patient-years were 8.3 and 11.4, respectively [10]. The higher rates in our study may be due not only to the longer follow-up time but also to the complexity of patients included in real-life studies being higher than that of patients included in clinical trials [25,26]. With regard to HF treatments, European guidelines recommend the use of renin–angiotensin system inhibitors (preferably sacubitril/valsartan), beta-blockers, SGLT2is, and mineralocorticoid receptor antagonists as first-line therapies for patients with HFrEF (and with a lower strength of evidence for patients with HFmrEF). By contrast, for patients with HFpEF, diuretics for treating congestive symptoms are the only drug class specifically recommended by European guidelines, along with the adequate management of comorbidities [4]. However, since the publication of these guidelines, two clinical trials have demonstrated that some SGLT2is can also reduce the risks of cardiovascular death and HF hospitalization in patients with HFpEF [23,24]. In addition, a recent pooled meta-analysis of the DAPA-HF and DELIVER trials has shown that the SGLT2i dapagliflozin significantly decreases the risks of cardiovascular death by $14\%$, all-cause death by $10\%$, and total HF hospitalizations by $29\%$ in the whole spectrum of patients with HF, regardless of left ventricular EF [10]. Our study shows that, across the EF spectrum, at baseline, only $70\%$ of patients were taking beta-blockers, $55\%$ were taking renin–angiotensin system inhibitors, $12\%$ were taking mineralocorticoid receptor antagonists, and $9\%$ were taking SGLT2is (our study period was prior to the first approval of SGLT2is for HF in the European Union). In addition, the increase in the proportion of patients taking HF drugs after the one-year follow-up was modest ($2\%$, $9\%$, $7\%$, and $1\%$, respectively), and, even 12 months after diagnosis, many patients remained untreated with guideline-directed therapies. Furthermore, a recent study has shown that the initiation of novel guideline-directed medical therapies, such as dapagliflozin or sacubitril/valsartan, is delayed compared with other that of HF drugs and that only a small proportion of patients receive the target doses of HF drugs requiring uptitration [27]. However, the use of some drugs (such as digoxin) that have not demonstrated benefits for mortality are still widely used [28]. Therefore, to decrease the risks of death and HF hospitalization, more efforts are necessary to reduce the gaps between recommended therapies impacting on morbidity and mortality and clinical practice [13]. Importantly, our study also analyzed the risks of other cardiovascular outcomes: the incidence rates of myocardial infarction, stroke, and their composite MACE with all-cause mortality were 26, 20 and 149 per 1000 person-years, respectively, with the rates of MACE increasing over time. This information is relevant, as it has not been well studied in previous studies. For example, it is well-known that myocardial infarction is an important cause of HF, particularly HFrEF, and when acute coronary syndrome is complicated with HF, the risk of recurrent adverse cardiovascular events markedly increases [5], yet coronary artery disease goes unrecognized in a great number of patients with HF (either HFrEF or HFpEF) [29,30]. In addition, our study found in a multivariate analysis that a history of myocardial infarction or coronary revascularization was associated with a higher risk of death or HF hospitalization. In this context, comprehensive management targeting both HF and coronary artery disease is mandatory [6,31,32]. Of note, a recent clinical trial has shown that, compared with optimal medical therapy, percutaneous revascularization does not provide additional benefits to patients with severe ischemic left ventricular systolic dysfunction, indicating that the best approach in these patients is the early implementation of disease-modifying HF therapies [4,33]. A recent meta-analysis has shown that patients with HF have a relative risk of developing ischemic stroke of 2.3 vs. those without HF. About $4\%$ of prevalent patients have prior ischemic stroke, and the annual incidence is $2.16\%$ (vs. 3.56 per 100 persons—3.64 per 100 person-years—within the first year of follow-up in our study) [9]. This higher risk of stroke markedly increases with the coexistence of atrial fibrillation [4]. Of note, ischemic stroke significantly increases morbidity and mortality in HF, independently of the presence of atrial fibrillation [34]. As a result, to reduce the risk of stroke in patients with HF, it is not only important to implement treatment with HF drugs but to also implement treatment with anticoagulation drugs when required (i.e., in the presence of atrial fibrillation) [34,35]. Finally, the risk of MACEs was high in our study, and, consequently, it should be considered a target by itself. As a result, when treating patients with HF, one should consider not only reducing the risks of cardiovascular death and HF hospitalization but also the risk of MACEs. Of note, the rates of MACEs were higher in the patients with HFrEF than in the patients with HFpEF, with the patients with HFmrEF having intermediate values; furthermore, in the HFpEF subgroup, the rates of MACEs were higher in the patients with EF 50–$60\%$ than in the patients with EF ≥ $60\%$. In this context, the pooled analysis of the DAPA-HF and DELIVER trials showed that the addition of dapagliflozin to standard therapy in patients with HF was associated with a significant reduction in MACE risk of $10\%$ [10]. ## 5. Study Limitations This study has some limitations. As this was a retrospective study, only data that were collected in the electronic clinical history of patients could be recorded, leading to the underdiagnosis of some variables. However, the high number of patients could have reduced this potential bias. Furthermore, the results of this study can only be extended to patients with similar clinical profiles and healthcare management. ## 6. Conclusions Patients with HF are of an older age, have many comorbidities, and have a high risk of adverse outcomes, including not only death and HF hospitalization but also myocardial infarction, stroke, and particularly MACE. 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--- title: Effect of Moderate to Severe Hepatic Steatosis on Vaccine Immunogenicity against Wild-Type and Mutant Virus and COVID-19 Infection among BNT162b2 Recipients authors: - Ka Shing Cheung - Lok Ka Lam - Xianhua Mao - Jing Tong Tan - Poh Hwa Ooi - Ruiqi Zhang - Kwok Hung Chan - Ivan F. N. Hung - Wai Kay Seto - Man Fung Yuen journal: Vaccines year: 2023 pmcid: PMC10054100 doi: 10.3390/vaccines11030497 license: CC BY 4.0 --- # Effect of Moderate to Severe Hepatic Steatosis on Vaccine Immunogenicity against Wild-Type and Mutant Virus and COVID-19 Infection among BNT162b2 Recipients ## Abstract Background: We aimed to investigate the effect of non-alcoholic fatty liver disease (NAFLD) on BNT162b2 immunogenicity against wild-type SARS-CoV-2 and variants and infection outcome, as data are lacking. Methods: Recipients of two doses of BNT162b2 were prospectively recruited. Outcomes of interest were seroconversion of neutralizing antibody by live virus microneutralization (vMN) to SARS-CoV-2 strains (wild-type, delta and omicron variants) at day 21, 56 and 180 after first dose. Exposure of interest was moderate-to-severe NAFLD (controlled attenuation parameter ≥ 268 dB/M on transient elastography). We calculated adjusted odds ratio (aOR) of infection with NAFLD by adjusting for age, sex, overweight/obesity, diabetes and antibiotic use. Results: Of 259 BNT162b2 recipients (90 ($34.7\%$) male; median age: 50.8 years (IQR: 43.6–57.8)), 68 ($26.3\%$) had NAFLD. For wild type, there was no difference in seroconversion rate between NAFLD and control groups at day 21 ($72.1\%$ vs. $77.0\%$; $$p \leq 0.42$$), day 56 ($100\%$ vs. $100\%$) and day 180 ($100\%$ and $97.2\%$; $$p \leq 0.22$$), respectively. For the delta variant, there was no difference also at day 21 ($25.0\%$ vs. $29.5\%$; $$p \leq 0.70$$), day 56 ($100\%$ vs. $98.4\%$; $$p \leq 0.57$$) and day 180 ($89.5\%$ vs. $93.3\%$; $$p \leq 0.58$$), respectively. For the omicron variant, none achieved seroconversion at day 21 and 180. At day 56, there was no difference in seroconversion rate ($15.0\%$ vs. $18.0\%$; $$p \leq 0.76$$). NAFLD was not an independent risk factor of infection (aOR: 1.50; $95\%$ CI: 0.68–3.24). Conclusions: NAFLD patients receiving two doses of BNT162b2 had good immunogenicity to wild-type SARS-CoV-2 and the delta variant but not the omicron variant, and they were not at higher risk of infection compared with controls. ## 1. Background Coronavirus disease 2019 (COVID-19), the illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in late 2019 and remains a public health burden globally. As of January 2023, there have been more than 600 million confirmed cases of COVID-19, including over 6 million deaths, reported to the World Health Organization. Measures to dampen the spread of COVID-19 have been of paramount importance to avoid the breakdown of major healthcare systems and to reduce excess mortality during peak infection periods. Vaccination is considered to be the most promising approach in preventing and reducing infection, severe disease and death [1]. Underlying comorbidities, including hypertension [2], diabetes mellitus (DM) [3] and obesity [4], have been shown to be associated with adverse COVID-19 outcomes and lower vaccine immunogenicity [5,6]. Chronic liver disease confers a higher risk of infection and disease severity of COVID-19, particularly those with liver cirrhosis and liver transplantation [7,8]. In addition, occurrence of liver injury in patients is associated with prolonged hospitalization [9]. A systemic meta-analysis by Wong et al. revealed that liver injury is mostly associated with severe forms of COVID-19 [10]. Obesity-associated inflammation is a risk factor for non-alcoholic fatty liver disease [11] and is associated with an increased risk of complications in COVID-19 patients [12]. With a prevalence of $32\%$ worldwide for non-alcoholic fatty liver disease (NAFLD) [13], concerns have also been raised about the response to COVID-19 vaccination in this population. Wang et al. [ 8] reported that BBIBP-CorV (inactivated vaccine) was safe, with good immunogenicity ($95.5\%$ had detectable levels of neutralizing antibody after two doses of vaccine). This study, however, did not recruit patients without NAFLD for comparison. While the effect of moderate to severe hepatic steatosis on the BNT162b2 vaccine immunogenicity in NAFLD patients was recently studied [14], data on neutralizing antibodies against mutant viruses, for instance, delta or omicron, and data on long-term immunogenicity (e.g., 6 months) and infection outcome are lacking. We aimed to further evaluate the vaccine immunogenicity (in term of neutralizing antibody response) and vaccine protection from COVID-19 infection in NAFLD subjects receiving the BNT162b2 vaccine in comparison with non-NAFLD subjects. ## 2.1. Study Design This is a prospective cohort study recruiting adult BNT162b2 vaccine recipients from two vaccination centers (Sun Yat Sen Memorial Park Sports Centre and Queen Mary Hospital) in Hong Kong. Exclusion criteria included age less than 18 years, organ transplant or blood transplant, in receipt of immunosuppressives or chemotherapy, other medical diseases (malignancy, hematological, rheumatological and autoimmune diseases), as well as prior COVID-19 infection (identified from both history taking and presence of antibodies to SARS-CoV-2 nucleocapsid (N) protein). Study subjects received two doses of BNT162b2 (0.3 mL) intramuscularly 3 weeks apart. Their blood samples were collected at four timepoints: (i) before vaccination (baseline), (ii) 21 days after the first dose, (iii) 56 days after the first dose and (iv) 180 days after the first dose. SARS-CoV-2 infection can be inhibited by blocking viral entry by inducing anti-SARS-CoV-2 neutralizing antibodies, namely receptor-binding domain (RBD) and N-terminal domain (NTD) of the spike protein [15]. Several methods are applied to evaluate the antibody level, such as immunofluorescence (IF), enzyme-linked immunoassay (ELISA) and live virus microneutralization (vMN) assay. IF and ELISA detect antibodies that can bind to virus or viral antigen, while vMN assay measures the neutralizing activity against the virus at the protein expression level. Anti-RBD antibody, which is evaluated by an ELISA-based surrogate neutralizing antibody (sNAb) test [16], is commonly used to express COVID-19 vaccine immunogenicity. On the other hand, vMN results express the total neutralizing activity, including anti-RBD and anti-NTD antibodies. Viral neutralization tests (VNTs) are regarded as the gold standard for serological detection [17], as vMN results indicate inactivation of infectious virus. VNTs, which are strongly correlated with disease protection, were chosen as the indicator of COVID-19 vaccine efficacy in our study. vMN assay was carried out in 96-well plate where serum samples were diluted in 2 folds serially starting from 1:10 (Gibco, Green Island, NY, USA). Diluted serum was mixed with 100 TCID50 ($50\%$ tissue culture infective dose) of SARS-CoV-2 and incubated at 37 degrees Celsius for one hour. The mixture was merged with VeroE6 cells and incubated at 37 degrees Celsius and $5\%$ carbon dioxide. After incubation for 72 h, the cytopathic effect was evaluated by examination under inversion microscopy. With reference to the standardization for SARVS-CoV-2 human immunoglobulin by the World Health Organization’s International Standard, the titer of vMN antibody was adopted from the highest dilution with $50\%$ inhibition of cytopathic effect. vMN positivity indicates seroconversion and was defined as a titer equal to or greater than 10 (31.25 IU/mL). vMN titers of three different strains of COVID-19—wild type, delta variants and omicron BA.1 variants—were measured respectively. The study was approved by the Institutional Review Board of the University of Hong Kong (HKU) and Hong Kong West Cluster (HKWC) of Hospital Authority. ## 2.2. Outcome of Interest Primary outcomes of interest were seroconversion rate at three time points (day 21, day 56 and day 180 after first dose of vaccination) to three different strains of SARS-CoV-2: wild type, delta variants and omicron variants. Secondary outcomes of interest were (i) COVID-19 infection rate and (ii) overall and individual adverse reactions. For the outcome of infection, subjects were followed until 18 May 2022 (study end date). COVID-19 was confirmed by either Rapid Antigen test (RAT) or Deep Throat Saliva (DTS). For the outcome of adverse reactions, subjects were requested to report any adverse reactions daily for 7 days after each dose of vaccine. They were classified into local reactions (pain, erythema, swelling and itchiness) and systemic reactions (fever, chills, headache, fatigue, myalgia, arthralgia, nausea, vomiting, diarrhea, skin rash and facial drooping). The severity of each adverse reaction was graded as 1 (mild), 2 (moderate), 3 (severe) and 4 (potentially life-threatening disease), with reference to the toxicity grading scale by the United States Department of Health and Human Services (HHS) [18]. ## 2.3. Exposure of Interest Controlled Attenuation Parameter measured by transient elastography (TE) using Fibroscan (Echosens, Paris, France) was used to define the presence of hepatic steatosis, which was further classified into different severity: mild (CAP 248–267 dB/m), moderate (CAP 268–279 dB/m) and severe (CAP 280 dB/m) [19]. Subjects with moderate to severe hepatic steatosis (i.e., CAP ≥ 268 dB/M) were grouped as “NAFLD” and those with mild or no hepatic steatosis were grouped as control. This is because subjects with moderate or severe hepatic steatosis have markedly higher risks in various clinical outcomes, including fibrosis, HCC and cardiovascular diseases, than those with mild hepatic steatosis [20,21]. Covariates included age, sex, overweight/obesity [22], diabetes mellitus (DM) [23] and antibiotic use (defined as any use of any antibiotics within 6 months before vaccination) [24]. Overweight/obesity was defined as BMI ≥ 23 kg/m2 with reference to National Institutes of Health (NIH) and World Health Organisations (WHO) guidelines for Asians. The correlation between obesity and poor vaccine-induced immune response was observed in hepatitis B [25], tetanus [26], rabies [27] and COVID-19 vaccines [5]. Data also reveal that efficacy of COVID-19 vaccine-induced neutralizing humoral immunity is potentially reduced among the obese subjects (seroconversion rate $82\%$ and $98\%$ in obese and normal BMI subjects, respectively). Poor vaccine-induced antibody protection in obese recipients suggests underlying factors related to obesity limit vaccine response [5]. Diabetes mellitus was defined as hemoglobin A1c ≥ $6.5\%$ or fasting glucose > 7 mmol/L. Immunogenicity of the COVID-19 vaccines has mostly been reported to be lower among patients with DM compared to healthy controls in a recent meta-analysis, regardless of vaccine type [6]. NAFLD is associated with distinct changes in gut microbiota profile [28]. Gut microbiota are important in modulating immune response to different types of vaccination [29,30], including influenza vaccine immunogenicity, which may be affected by antibiotic-induced gut microbiota perturbation [31,32]. Antibiotic-induced gut dysbiosis has also been shown to affect various outcomes, including response to immune checkpoint inhibitors [33] and colorectal cancer development [34]. ## 2.4. Statistical Analysis All statistical analyses were performed using R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria) statistical software. The values of continuous variables were displayed as medians and interquartile range (IQR), while values of categorical variables were displayed as numbers and percentages. For two continuous variables, the Mann–Whitney U-test was used. For categorical variables, the chi-square test or Fisher exact test was used. A multivariable logistic regression model was applied to estimate the adjusted odds ratio (aORs) of seroconversion rate and vaccine protection to COVID-19 infection with moderate/severe NAFLD as well as all the aforementioned covariates. An MN titer less than 10 was expressed as 5 for the purpose of statistical analysis. Sensitivity analysis was performed by reclassifying subjects with mild hepatic steatosis into the NAFLD group. The statistical significance level threshold was set at p-value ≤ 0.05 and all tests were two-sided. ## 3.1. Demographics and Baseline Characteristics In total, 259 subjects were enrolled; 68 had moderate ($$n = 20$$) or severe ($$n = 48$$) hepatic steatosis (NAFLD), and 191 had mild ($$n = 31$$) or no ($$n = 160$$) hepatic steatosis (control). The demographics of subjects are displayed in Table 1. The median age was similar between NAFLD patients and controls (NAFLD: 51.0 years vs. control: 50.8 years; $$p \leq 0.271$$). There were more males in the NAFLD group than controls ($52.9\%$ vs. $28.3\%$; $p \leq 0.001$). There was a higher proportion of NAFLD patients being overweight or obese compared to controls ($89.7\%$ vs. $39.8\%$; $p \leq 0.001$). A higher proportion of NAFLD patients had DM compared to controls ($17.6\%$ vs. $3.1\%$; $p \leq 0.001$). ## 3.2. Comparison of Vaccine Immunogenicity to Wild-type SARS-CoV-2 between NAFLD and Control Groups Table 2, Figures S1 and S2 show the seroconversion rate and vMN GMT of the BNT162b2 recipients. At day 21, there was no significant difference in seroconversion rate between NAFLD and control groups ($72.1\%$ vs. $77.0\%$; $$p \leq 0.418$$) or the vMN GMT (13.4 vs. 13.6; $$p \leq 0.885$$). At day 56, all vaccines achieved seroconversion with a similar vMN GMT (90.4 vs. 99.6; $$p \leq 0.610$$). At day 180, more than $97\%$ remained seropositive, with vMN GMT decreasing from 90.4 to 33.3 in NAFLD and from 99.7 to 35.6 in the control group, and there was no significant difference between NAFLD and control groups. Sensitivity analysis by reclassifying subjects with mild hepatic steatosis into NAFLD group shows similar results (Table S1). In univariate analysis, the OR of seropositivity for wild-type virus with male sex was 0.48 ($95\%$ CI: 0.27–0.87) (Table 3). Other factors, including age, NAFLD, overweight/obesity, DM and antibiotic use, were not associated with seropositivity to wild-type SARS-CoV-2. In multivariable analysis, male sex remained as the only independent factor with seropositivity (aOR: 0.57, $95\%$ CI: 0.28–0.94) (Table 3). ## 3.3. Comparison of Vaccine Immunogenicity to SARS-CoV-2 Delta/Omicron Variant between NAFLD and Control Groups There was no significant difference in the seroconversion rate of neutralizing antibodies to the delta variant between NAFLD and control groups, at day 21 ($25.0\%$ vs. $29.5\%$; $$p \leq 0.70$$), day 56 ($100\%$ vs. $98.4\%$; $$p \leq 0.57$$) and day 180 ($89.5\%$ vs. $93.3\%$; $$p \leq 0.58$$), respectively, or, alternatively, the vMN GMT at day 21 (6.83 vs. 6.95; $$p \leq 0.76$$), day 56 (62.77 vs. 53.75; $$p \leq 0.51$$) and day 180 (20 vs. 25.49; $$p \leq 0.25$$), respectively (Table 4, Figures S1 and S2). There was also no significant difference in seroconversion rate of neutralizing antibody to omicron variant between NAFLD and control groups. By day 21, none achieved seroconversion. At day 56, less than $20\%$ achieved seroconversion, and there was no significant difference in seroconversion rate ($15.0\%$ vs. $18.0\%$; $$p \leq 0.76$$) or the vMN GMT (5.55 vs. 5.86; $$p \leq 0.71$$) among NAFLD and control groups. At day 180, all vaccines became seronegative in both groups. Sensitivity analysis by reclassifying subjects with mild hepatic steatosis into the NAFLD group shows similar results (Table S1). ## 3.4. Comparison of Vaccine Protection to SARS-CoV-2 Infection (Any Variants) between NAFLD and Control Groups There were 4 ($1.5\%$) pieces of missing data on infection rate out of 259 study subjects. Thus, 55 of 255 ($21.6\%$) study subjects had SARS-CoV-2 infection as of 18 May 2022. The median time from vaccination with the first dose to infection was 244 days (IQR: 227.5–264.0). All infections were mild and did not require hospitalization. There was no significant difference in the seroconversion rate at all time points (day 21, day 56 and day 180) between the infected and non-infected subjects (all $p \leq 0.05$; Table S2). There was no significant difference in the infection rate between NAFLD and control groups ($25.8\%$ vs. $20.1\%$; $$p \leq 0.337$$). In univariate and multivariable analyses, factors, including age, sex, NAFLD, overweight/obesity, DM, and antibiotic use, were not associated with vaccine protection to SARS-CoV-2 infection (Table 5). ## 3.5. Safety Thus, 240 ($92.7\%$) BNT162b2 recipients reported adverse effects within 7 days of either the first or the second dose of vaccine (Table S3). All the adverse effects were mild to moderate (grade 1 and 2) and self-limiting, with no serious adverse events (grade 3 and 4), such as anaphylaxis or cardiovascular events. The most common local adverse events were injection site pain ($88.9\%$), while the most common systemic adverse reaction was fatigue ($52.5\%$). Overall, the rate of adverse events was similar between NAFLD and control groups (63 ($92.6\%$) vs. 177 ($92.7\%$), $$p \leq 0.343$$). Among systemic adverse reactions, the NAFLD group showed a higher rate of chills and rigors (12 ($17.6\%$) vs. 21 ($11.0\%$), $$p \leq 0.042$$), joint pain (12 ($17.6\%$) vs. 27 ($14.1\%$), $$p \leq 0.026$$) and nausea (6 ($8.8\%$) vs. 13 ($6.8\%$), $$p \leq 0.027$$) than the control group. There was no significant difference in the rate of local adverse reactions between NAFLD and control groups (59 ($86.8\%$) vs. 173 ($90.6\%$), $$p \leq 0.412$$). ## 4. Discussion This prospective cohort study demonstrates that there was no difference in the vaccine efficacy in terms of neutralizing antibody response to wild-type and mutant SARS-CoV-2 between moderate to severe NAFLD and control groups. The seroconversion rate of neutralizing antibodies against the wild-type, delta variant and omicron variant was >$97\%$, >$89\%$ and $0\%$ after 6 months, respectively. There was also no difference in the rate of COVID-19 infection between the two groups ($25.8\%$ vs. $20.1\%$). It has been observed that COVID-19 patients with chronic liver disease had increased length of hospital stay, higher rates of intensive care unit stay and need for mechanical ventilation compared to those without chronic liver disease. This association was also observed in patients with NAFLD, even after controlling for the presence of obesity [35]. The effect of NAFLD on COVID-19 severity may be due to underlying obesity and hepatic steatosis with higher serum markers of inflammation and oxidative stress [36]. Vaccination is paramount in preventing SARS-CoV-2 infection, severe symptoms and death. There are few studies that have evaluated the efficacy of SARS-CoV-2 vaccination in patients with NAFLD, and available studies are limited to assessing vaccine immunogenicity to wild-type SARS-CoV-2 infection only. As far as we know, our study is the first to compare the immunogenicity of mRNA vaccines to different strains of COVID-19, including wild-type, delta and omicron variants, between NAFLD and control groups. Another merit of this study was the prolonged follow-up to more than 6 months in terms of immunogenicity and infection outcome. In a multicenter study conducted in China, Wang et al. [ 37] reported an encouraging result of more than $95\%$ of NAFLD patients elicited detectable neutralizing antibody responses after two doses of the inactivated COIVD-19 vaccine (BBIBP-CorV). However, the vaccine studied (BBIBP-CorV) was an inactivated vaccine and there was no comparison with a control group. Moreover, status of NAFLD might be misclassified as the diagnosis of NAFLD was heterogeneously defined by either clinical findings or liver biopsy. Our study had additional advantages. First, live virus, the gold standard for analysis of vaccine humoral response [38], was used, in comparison with a surrogate virus neutralization test, where correlation with live virus was only 0.7–0.8 [39]. Second, a homogeneous definition of NAFLD using CAP measurement from transient elastography was adopted, which also allowed us to analyze vaccine immunogenicity based on the severity of NAFLD. A prospective cohort study [14] demonstrated that a lower proportion of moderate or severe hepatic steatosis patients, as compared to the control group, achieved the highest-tier response for either mRNA (BNT162b2) or inactivated vaccines (CoronaVac). However, SARS-CoV-2 variants were not evaluated and vaccine immunogenicity on day 180 was not well studied due to the relative proportion of missing data. Our current study emphasized the long-term immunogenicity, as well as a comparison of, SARS-CoV-2 variants (delta variants and omicron variants). We found that BNT162b2 was effective against wild-type SARS-CoV-2, but there was no difference in the seroconversion rate or vMN GMT after either the first or second dose between the NAFLD and control groups at different time points. At day 21, more than $70\%$ achieved seropositivity; at day 56, all vaccinees attained seroconversion with a similar vMN GMT (90.4 vs. 99.7, $$p \leq 0.61$$); and at day 180, over $97\%$ remained seropositive with a similar vMN GMT. Multivariable analysis further shows that male sex was the only independent factor predicting serological response to wild-type SARS-CoV-2 but not other factors, including NAFLD and cardiovascular risk factors. Similar findings were observed for SARS-CoV-2 delta and omicron variants, in which there was no significant difference in the seroconversion rate of neutralizing antibody nor vMN GMT to SARS-CoV-2 delta and omicron variant among the NAFLD and control group. Of note, BNT162b2 vaccine efficacy remained high to delta variants, in which more than $98\%$ achieved seropositivity at day 56. However, BNT162b2 vaccine was less effective on omicron variants, in which less than $20\%$ achieved seroconversion at day 56. A similar proportion of NAFLD and control groups ($25.8\%$ vs. $20.1\%$) had COVID-19 disease despite receiving two doses of BNT162b2. All infections were contracted after day 180 of first dose BNT162b2 vaccine, in early 2022, during which the omicron variant was the predominant strain in Hong Kong. With regard to safety, COVID-19 vaccines were well tolerated, with mild and self-limiting side effects. They were generally similar between NAFLD and control groups in terms of overall adverse events. It was observed that the NAFLD group reported a higher frequency of chills and rigors, nausea and joint pain than control group. Nonetheless, the symptoms were mild and resolved within days. The association between reactogenicity and immunogenicity is still not well established and yet to be answered. There were several limitations in our study. First, the sample size was relatively small, and this study was only limited to the BNT162b2 vaccine. Future studies with a larger sample size and assessment of different COVID-19 vaccine platforms, in particular to the latest COVID-19 bivalent vaccine boosters, will allow for better evaluation. Second, vaccine-induced cellular immunity against SARS-CoV-2 was not studied. Given the role of CD4 and CD8 T cells in the clearance of infections, via suppression of viral replication and mounting of long-term memory of the immune system, it was believed that vaccine-induced T-cell response may substantially protect against severe SARS-CoV-2 disease, even with antibody seronegativity [40]. This may be specifically relevant for the omicron variant, which dramatically evades neutralizing antibody responses [41]. Third, NAFLD was defined by measurement of CAP using transient elastography. However, magnetic resonance elastography (MRE), which has a diagnostic accuracy of 0.9, remains as the most accurate method in diagnosing NAFLD among the available non-invasive modalities. Fourth, more long-term data on immunogenicity data beyond 180 days are lacking. With the advocation of third, fourth and even fifth dose of vaccine, longer-term follow-up (e.g., one year) and further investigation on serological response to additional doses of vaccine in NAFLD patients are needed. There are two implications in our study. First, given the good immunogenicity of the BNT162b2 vaccine, with comparable effectiveness on COVID-19 protection between NAFLD and control groups, NAFLD patients should be ascertained and encouraged to receive vaccination (at least two doses) to prevent severe complications. Second, the BNT162b2 vaccine is proven to be safe. Mild and self-limiting side effects should not deter NAFLD patients from being vaccinated in exchange for immunogenicity to SARS-CoV-2. ## 5. Conclusions There was no difference in the seroconversion rate to wild-type SARS-CoV-2 and variants between moderate to severe NAFLD and control groups after two doses of BNT162b2. 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--- title: Anti-Atopic Dermatitis Effects of Abietic Acid Isolated from Rosin under Condition Optimized by Response Surface Methodology in DNCB-Spread BALB/c Mice authors: - Jumin Park - Ji Eun Kim - You Jeong Jin - Yu Jeong Roh - Hee Jin Song - Ayun Seol - So Hae Park - Sungbaek Seo - Heeseob Lee - Dae Youn Hwang journal: Pharmaceuticals year: 2023 pmcid: PMC10054120 doi: 10.3390/ph16030407 license: CC BY 4.0 --- # Anti-Atopic Dermatitis Effects of Abietic Acid Isolated from Rosin under Condition Optimized by Response Surface Methodology in DNCB-Spread BALB/c Mice ## Abstract Abietic acid (AA) is known to have beneficial effects on inflammation, photoaging, osteoporosis, cancer, and obesity; however, its efficacy on atopic dermatitis (AD) has not been reported. We investigated the anti-AD effects of AA, which was newly isolated from rosin, in an AD model. To achieve this, AA was isolated from rosin under conditions optimized by response surface methodology (RSM), and its effects on cell death, iNOS-induced COX-2 mediated pathway, inflammatory cytokine transcription, and the histopathological skin structure were analyzed in 2,4-dinitrochlorobenzene (DNCB)-treated BALB/c mice after treatment with AA for 4 weeks. AA was isolated and purified through isomerization and reaction-crystallization under the condition (HCl, 2.49 mL; reflux extraction time, 61.7 min; ethanolamine, 7.35 mL) established by RSM, resulting in AA with a purity and extraction yield of $99.33\%$ and $58.61\%$, respectively. AA exhibited high scavenging activity against DPPH, ABTS, and NO radicals as well as hyaluronidase activity in a dose-dependent manner. The anti-inflammatory effects of AA were verified in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages through amelioration of the inflammatory response, including NO production, iNOS-induced COX-2 mediated pathway activation, and cytokine transcription. In the DNCB-treated AD model, the skin phenotypes, dermatitis score, immune organ weight, and IgE concentration were significantly ameliorated in the AA cream (AAC)-spread groups compared to the vehicle-spread group. In addition, AAC spread ameliorated DNCB-induced deterioration of skin histopathological structure through the recovery of the thickness of the dermis and epidermis and the number of mast cells. Furthermore, activation of the iNOS-induced COX-2 mediated pathway and increased inflammatory cytokine transcription were ameliorated in the skin of the DNCB+AAC-treated group. Taken together, these results indicate that AA, newly isolated from rosin, exhibits anti-AD effects in DNCB-treated AD models, and has the potential to be developed as a treatment option for AD-related diseases. ## 1. Introduction Abietic acid (AA, C20H30O2, MW 302.458 g/mol) is an organic acid naturally found in pine obtained from Pinus sp. ( Pinaceae). It belongs to the abietane diterpene group of organic compounds derived from four isoprene units (20 carbon atoms) [1,2]. Natural AA and its derivatives with high anti-oxidant activity have received great attention due to its various therapeutic effects, including anti-microbial, anti-ulcer, anti-cardiovascular, and anti-allergy activities [3,4,5,6,7,8]. However, the isolation of natural AA from rosin, which a solid form of resin collected from pines and other plants, has only been attempted in several studies through isomerization, amination, and recrystallization processes [9,10,11]. Among these, an early study isolated this compound without reporting accurate yield or purity and only used it for efficacy evaluation [9]. Only recent studies have reported actual values for the purity and yield of AA. Approximately 98 g of AA was first isolated from 250 g of wood rosin at a yield of $39.2\%$ [10]. In addition, AA with high purity ($98.52\%$) was obtained from gum rosin with a yield of $54.93\%$ [11]. To date, the purification stage of AA involves a complex process and has low yields, although the isolation stage consists of a similar process. Additionally, the optimization of AA isolation conditions using response surface methodology (RSM) has never been attempted. Therefore, it is necessary to optimize and simplify the isolation and purification stages to improve the yield and purity of natural AA. The beneficial effects of AA have been actively studied in various biological fields, including angiogenesis, cancer, nephropathy, lung injury, osteolysis, endoplasmic reticulum stress (ER stress), and inflammation. Among them, notable suppression effects were detected in the growth, metastasis, and invasiveness of several types of cancer cells, such as melanoma, non-small-cell lung and breast cancer cells, and breast cancer cells [12,13,14]. In addition, AA accelerates cutaneous wound healing by enhancing angiogenesis [15], ameliorating sepsis-induced lung injury by inhibiting the nuclear factor-kappa B (NF-κB) signaling pathway [16], and mitigating obesity in models related to suppressing steatosis and adipogenesis [17,18]. The osteoprotective effect of AA was detected in receptor activator of nuclear factors κB ligand (RANKL)-induced osteoclastogenesis and in lipopolysaccharide (LPS)-induced osteolysis models [19], while its mitigation effects on nephropathy progression were detected in the kidney in type-2 diabetes mellitus (DM) [1]. Furthermore, AA significantly ameliorated psoriasis-like skin inflammation in imiquimod (IMQ)-treated BALB/c mice, interleukin (IL)-1β-induced inflammation in human osteoarthritic chondrocytes, airway inflammation in an allergic asthma model, and kidney inflammation in a type-2 DM model [1,20,21,22]. However, whether AA has anti-atopic dermatitis (AD) effects in the DNCB-induced AD model remains unclear. In this study, we investigated the anti-AD activity of AA newly isolated from rosin and its molecular mechanism of action in DNCB-treated BALB/c mice with AD phenotypes based on the results of LPS-stimulated RAW264.7 macrophages. ## 2.1. Isolation and Purification of AA under Optimal Condition Established by RSM, and Its Characterization Firstly, an optimal condition for AA isolation was established by RSM to improve the purity and yield of AA. According to the RSM design, 17 combinations were performed in triplicate and the obtained results are showed in Supplementary Table S1. During the optimization, the response results in the following regression equations: Y1 = 60.00 + 1.91X1 + 1.19X2 − 1.40X3 − 0.90X1X2 + 0.47X1X3 − 1.77X2X3 + 2.14X12 − 1.37X22 − 1.50X32 Y2 = 90.27 + 1.26X1 + 1.17X2 − 1.31X3 − 1.11X1X2 + 0.67X1X3 − 1.56X2X3 + 1.60X12 − 1.43X22 − 1.45X32 where Y1 and Y2 are the maximal extraction yield and purity of AA as a function of the amount of HCl (X1), reflux extraction time (X2), and amount of ethanolamine (X3). Based on the experimental response, the optimized conditions based on both extraction yield and purity were determined as the amount of HCl added (2.49 mL), reflux extraction time (61.7 min), and the amount of ethanolamine added (7.35 mL). To evaluate the purity of AA derived under optimal isolation conditions, HPLC coupled with PDA under the same isocratic conditions was carried out. As shown in Figure 1A,B, AA peaks of AA appeared at 20.3 min and its wavelength spectrum by PDA was identical to the AA standard. The purity of the isolated AA was $99.33\%$. Furthermore, the MS spectra showed an AA [M-H]- ion at m/z 301.2148 as the molecular ion peak (Figure 1C), and its MS spectra showed a fragmentation pattern in good agreement with that of the AA standard. To further support the assignment of the isolated and purified compound from rosin as AA, the IR spectrum was analyzed (Figure 1D). The IR spectrum of the compound revealed the same patterns as the AA standard, and it showed a large narrow band at 1691 cm−1 related to the stretching of C=O, corresponding to the –COOH group. The bands at 2953–2835 cm−1 belong to the C–H stretching absorption bands owing to the presence of =CH, –CH3, –CH2, and –CH groups. In addition, the peaks at 1282 cm−1 and 891 cm−1 correspond to C–O deformation from the –COOH group and C–H deformation out of the plane of conjugated double bonds, respectively [23,24]. Based on these results, the isolated and purified compound from rosin was identified as AA. ## 2.2. Biochemical Properties of AA against Inflammation and Oxidative Stress Next, we analyzed the biochemical properties of AA, newly isolated from rosin, against inflammation and oxidative stress to evaluate its potential for the amelioration of inflammatory diseases. Alterations in hyaluronidase activity and radical scavenging activity were measured at various concentrations of AA. The activity of HAase decreased in a dose-dependent manner with AA. The lowest level (48.31 ± $0.83\%$) was detected at 2000 μg/mL, followed by 1000 μg/mL (56.40 ± $1.32\%$), 500 μg/mL (70.32 ± $0.84\%$), 250 μg/mL (79.09 ± $1.03\%$), and 125 μg/mL (82.72 ± $1.05\%$) of AA (Figure 2A). In addition, a similar dose-dependent increase in AA was detected in the AA scavenging activity for the three radicals, including DPPH, ABTS, and NO. The IC50 value for the DPPH, ABTS and NO radicals was determined to be 109.14 ± 2.21 µg/mL, 49.82 ± 0.13 µg/mL, and 166.49 ± 0.18 µg/mL (Figure 2B). These results suggest that AA, newly isolated from rosin, shows strong anti-inflammatory and anti-oxidative properties and has the potential to be developed into a therapeutic drug for inflammatory diseases. ## 2.3. Verification of Anti-Inflammatory Activities of AA in LPS-Stimulated RAW264.7 Macrophages Based on the biochemical properties of AA against inflammation and oxidative stress, we verified the anti-inflammatory effects of AA isolated from rosin in macrophages before evaluating their effects in a DNCB-treated AD model. To achieve this, alterations in cell death, NO production, the iNOS-induced COX-2 mediated pathway, and inflammatory cytokine transcription were analyzed in LPS-stimulated RAW264.7 macrophages. First, changes in cell viability and morphology in RAW264.7 treated with AA+LPS were analyzed to investigate whether treatment with AA newly isolated from rosin can inhibit LPS-induced cell death. Cell viability was $51\%$ lower in the Vehicle+LPS-treated group than in the non-treated group. However, these effects were significantly ameliorated in a dose-dependent manner in the LAA+LPS-, MAA+LPS-, and HAA+LPS-treated groups. In particular, in the HAA+LPS-treated group, these levels were recovered in the non-treated group (Figure 3A). In addition, these alterations in cell viability were fully reflected in the morphology of RAW264.7 macrophages (Figure 3B). Second, changes in NO concentration and iNOS-induced COX-2 mediated pathway were measured in AA+LPS-treated RAW264.7 macrophages, to investigate whether the treatment of AA newly isolated from rosin can ameliorate against the NO production caused by LPS, The NO concentration was 13.7 times higher in Vehicle+LPS-treated group than in the non-treated group. However, this concentration was markedly ameliorated in a dose-dependent manner after AA treatment (Figure 4A). A similar response was observed in the expression of iNOS and COX-2 proteins in the iNOS- induced COX-2 mediated pathway. The increased iNOS and COX-2 levels in the Vehicle+LPS-treated group were remarkably ameliorated by AA treatment, although a dose-dependent response was observed only in COX-2 expression (Figure 4B). In addition, the expression levels of iNOS and COX-2 proteins were partially reflected in the transcript levels of both genes (Figure 4C). Furthermore, the recovery of iNOS and COX-2 proteins was accompanied by the recovery of the mitogen-activated protein kinase (MAPK) signaling pathway. The enhanced phosphorylation levels of the three key proteins in the Vehicle+LPS-treated group were significantly ameliorated in the three AA+LPS-treated groups (Figure 4D). Third, the transcription levels of inflammatory cytokines were measured in the AA+LPS-treated RAW264.7 macrophages, to examine whether the amelioration effects of AA newly isolated from rosin on LPS-induced NO production are accompanied by alterations in cytokine secretions. The regulation of inflammatory cytokine transcription is well reflected in the regulation of NO production and the iNOS-induced COX-2-mediated pathway. The AA+LPS-treated groups exhibited a significant amelioration in the transcript levels of six cytokines, including TNF-α, IL-1β, IL-4, IL-5, IL-6, and IL-10, compared to the Vehicle+LPS-treated group. Most of them showed the highest decrease in the HAA+LPS-treated group, although a dose-dependent response was detected in the expression of IL-4 (Figure 5). Finally, a similar amelioration effect of AA in the NO-producing system was reflected in inflammasome activation. The increased levels of NLR family pyrin domain containing 3 (NLRP3), apoptosis-associated speck-like protein containing a CARD (ASC), and the cleavage of Cas-1 proteins in the Vehicle-treated group were significantly decreased in the LAA+LPS-, MAA+LPS-, and HAA+LPS-treated groups compared to those in the Vehicle+LPS-treated group (Figure 6). Therefore, the results of all experiments indicate that AA, newly isolated from rosin, may contribute to the amelioration of the increase in cell death, NO production systems, and inflammatory cytokine transcription in LPS-stimulated RAW264.7 macrophages. ## 2.4. Amelioration of Skin Phenotypes in DNCB-Induced AD Mice by AA Spreading Furthermore, we investigated the ameliorative effects of AA, newly isolated from rosin, against AD symptoms in DNCB-treated BALB/c mice to confirm the same effects of AA detected in LPS-stimulated RAW264.7 macrophages. As part of these experiments, alterations in skin thickness and dermatitis score were first analyzed in the skin of the DNCB-induced AD model after AA spreading. As shown in Figure 7A,B, skin thickness was greater in the DNCB+Vehicle-treated group than in the non-treated group. However, this level was markedly ameliorated in a dose-dependent manner after AA spread, although the DNCB+Steroid-treated group remained constant. In addition, a similar response to AA was observed in the dermatitis score. After treatment with AA for 14 days, these scores were significantly ameliorated in the DNCB+LAAC-, DNCB+MAAC-, and DNCB+HAAC-treated groups compared to the DNCB+Vehicle-treated group, although the highest decrease rate was detected in the DNCB+HAAC-treated group (Figure 7A,C). Therefore, these results indicate that the spread of AA newly isolated from rosin can ameliorate the deterioration of skin phenotypes in a DNCB-induced AD model. ## 2.5. Amelioration of IgE-Mediated Symptoms in DNCB-Induced AD Mice by AA Spreading To determine whether the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype are accompanied by alterations in IgE-mediated symptoms, the weight of the immune organ and IgE concentration were measured in the DNCB-induced AD model after spreading AA. First, the weight of the spleen and the relative size of the lymph node were remarkably higher in the DNCB+Vehicle-treated group than in the non-treated group. However, these alterations were ameliorated in the DNCB+AAC-treated groups compared to the DNCB+Vehicle-treated group (Figure 8A). A similar response was observed for the concentration of serum IgE. The increased level in the DNCB+Vehicle-treated group was ameliorated in a dose-dependent manner in the DNCB+AAC group (Figure 8B). Thus, the above results indicate that the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype may be tightly linked to the alleviation of IgE-mediated symptoms in the DNCB-induced AD model. ## 2.6. Amelioration of Skin Histopathological Structure in DNCB-Induced AD Mice by AA Spreading To determine whether the ameliorative effects of AA on DNCB-induced deterioration of skin phenotype were accompanied by alterations in the histopathological structure of the skin, the thickness of the dermis and epidermis and the number of mast cells were measured in the skin of the DNCB-induced AD model after AA spreading. The thickness of the epidermis and dermis was higher in the DNCB+Vehicle-treated group than in the non-treated group. However, these levels were significantly ameliorated after AAC treatment when compared to those in the DNCB+Vehicle-treated group (Figure 9A). Additionally, the ameliorative effects of AAC on the thickness of the epidermis and dermis were completely reflected by the infiltration of immune cells. The increased number of mast cells was ameliorated in the DNCB+LAAC-, DNCB+MAAC-, and DNCB+HAAC-treated groups compared to that in the DNCB+Vehicle-treated group (Figure 9B). Therefore, these results suggest that the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype may be closely related to the alleviation of the histopathological structure of the skin in the DNCB-induced AD model. ## 2.7. Amelioration of NO-Producing System in DNCB-Induced AD Mice by AA Spreading To determine whether the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype are accompanied by alterations in the NO production system, the expression levels of iNOS, COX-2, and MAPK members were measured in the skin of the DNCB-induced AD model after AA spreading. First, the expression levels of iNOS and COX-2 proteins were increased in the DNCB+Vehicle-treated group compared to the non-treated group. However, these levels were remarkably ameliorated in the DNCB+LAAC-, DNCB+MAAC-, and DNCB+HAAC-treated groups (Figure 10A). In addition, these alteration patterns in the protein levels of iNOS and COX-2 were detected at the mRNA levels of both genes (Figure 10B). Furthermore, the amelioration of the expression levels of iNOS and COX-2 proteins was accompanied by the recovery of the activation of the MAPK signaling pathway. The increased levels of ERK, JNK, and p38 phosphorylation were remarkably ameliorated in the DNCB+AAC-treated groups compared to those in the DNCB+Vehicle-treated group (Figure 10C). Thus, these results indicate that the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype may be closely related to the alleviation of the NO production system by regulating the iNOS-mediated COX-2 induction pathway, including the MAPK signaling pathway. ## 2.8. Amelioration of Inflammatory Cytokines Secretion in DNCB-Induced AD Mice by AA Spreading To examine whether the ameliorative effects of AA on DNCB-induced deterioration of skin phenotype were accompanied by alleviation of inflammatory cytokine secretion, the expression levels of six cytokines, including TNF-α, IL-1β, IL-4, IL-5, IL-6, and IL-10, were measured in the skin tissues of DNCB+AAC-treated mice. Most of them showed similar response patterns after AAC spreading. The mRNA levels of six cytokines were higher in the DNCB+Vehicle-treated group than in the non-treated group. However, they were significantly ameliorated in the DNCB+AAC group compared to the DNCB+Vehicle-treated group, although dose-dependent responses were not clearly observed (Figure 11). Therefore, these results suggest that the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype may be related to the alleviation of inflammatory cytokine transcription. ## 2.9. Amelioration of Inflammasome Activation in DNCB-Induced AD Mice by AA Spreading Finally, we investigated whether the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype are accompanied by the alleviation of inflammasome activation. To achieve this, the expression levels of key regulators, including NLRP3, ASC, cleaved Cas-1, and Cas-1, were analyzed in the skin tissue of DNCB+AAC-treated mice. Their levels were higher in the DNCB+Vehicle-treated group than in the non-treated group. However, these levels were remarkably decreased in all DNCB-treated groups after spreading AAC for 28 days (Figure 12). Therefore, the above results indicate that the ameliorative effects of AA on DNCB-induced deterioration of the skin phenotype may be associated with the alleviation of inflammasome activation. ## 3. Discussion Inflammatory responses stimulated by pathogens, toxic compounds, and damaged cells can remove harmful factors and initiate the healing mechanism and lead to tissue damage in various organs, including the brain, heart, lung, and liver [25]. Therefore, mitigation of this response can be considered an effective strategy to recover tissue homeostasis and ameliorate inflammatory diseases [26]. As part of these studies, a treatment strategy using AA has recently received considerable attention because it is being studied for its therapeutic efficacy and mechanism of action in several inflammation-related diseases, such as inflammatory bowel disease, rheumatoid arthritis, and psoriasis [27]. In this study, the optimal isolation condition including amount of HCl (2.49 mL), reflux extraction time (61.7 min), and amount of ethanolamine (7.35 mL) was firstly established using RSM. Under these conditions, the purity and yield of AA were enhanced to $99.33\%$ and $58.61\%$. Additionally, anti-AD effects and related mechanisms of AA were investigated in a DNCB-treated mouse model. Our results provide novel scientific evidence that AA with high purity was isolated in high yield under RSM-optimized conditions, and that this AA may contribute to the amelioration of DNCB-stimulated AD phenotypes through the regulation of the iNOS-induced COX-2 mediated pathway and inflammatory cytokine production. Rosin is an important non-timber forest material that is naturally derived from the oozed colophony of pine trees [28,29]. The main source of abietane acid is rosin (colophony), which is the residue of the distillation of pine resins. The acid part of rosin is composed of AA, its equilibrium isomers such as levopimaric, palustric, and neoabietic acids, and dehydroabietic acid, as well as some other non-abietanic compounds [30,31,32,33]. The main ingredients of rosin are terpene-based neutral compounds (10–$20\%$) and abietic-type resin acids (80–$90\%$), with the main component (approximately $50\%$) being AA [34,35]. A study proposed the process of isolating AA from rosin via isomerization, amination, and crystallization [11]. They obtained AA with a purity and yield of $98.52\%$ and $54.93\%$, respectively. However, the recrystallization of the amine salts was repeated three times. In this study, the isomerization and reaction-crystallization for AA was optimized with a certain amount of HCl (2.49 mL), reflux extraction time (61.7 min), and ethanolamine (7.35 mL) using RSM. After the crystallization of AA, preparative HPLC was performed. Finally, the purity and yield of AA were improved to $99.33\%$ and $58.61\%$, respectively, although the AA isolation process was simplified. HAase is a hyaluronic acid (HA) hydrolyzing enzyme that is related to physiological regulatory processes and pathological conditions, including inflammation and allergic responses [36,37]. The purified AA inhibited HAase activity in a dose-dependent manner with an IC50 value of 1719 μg/mL (Figure 2A). During inflammation and tissue damage, HAase cleaves HA into fragments of lower molecular weight, thus inducing pro-inflammatory immune responses [38]. It has been reported that AA from Pimenta racemose var. grissea exerted anti-inflammatory activity against edema and had a partial ability to prevent the production of some inflammatory mediators [39]. Therefore, the inhibitory activity of AA on HAase may play an important role in the pathological processes of AD pathogenesis. The anti-oxidant activities of AA were evaluated by measuring its radical scavenging effects on DPPH, ABTS, and NO radicals. The concentrations required to scavenge $50\%$ of the initial DPPH, ABTS, and NO radicals were 109.14 μg/mL, 49.82 μg/mL, and 166.49 μg/mL, respectively. In addition, a study reported that IC50 values of DPPH and hydroxyl radicals toward AA of *Isodon wightii* were calculated as 660.36 μg/mL and 467.43 μg/mL [40]. The anti-oxidant activities of other abietane diterpenoids, such as carnosol, isorosmanol, carnosic acid, rosmanol, epirosmanol, and galdosol from *Salvia officinalis* L. and inuroyleanol from S. barrelieri, have been reported in the literature [41,42]. It has been suggested that the anti-oxidant mechanism of abietane diterpenoids in nonpolar environments involves formal hydrogen transfer, whereas the single-electron transfer mechanism of anion states in aqueous environments is favored [43]. These results indicate that AA serves as an effective free radical scavenger. LPS is well known as a potential activator of monocytes and macrophages because it induces an acute inflammatory response by stimulating the secretion of a vast number of inflammatory cytokines in many types of cells [44,45]. Based on these properties, LPS-stimulated cell models have been widely used to evaluate the anti-inflammatory effects of AA or natural products containing AA. First, AA isolated from *Pimenta racemosa* var. grisea (Myrtaceae) significantly prevented the production of NO, Prostaglandin E2 (PGE2), TNF-α, and IL-1β in LPS-stimulated peritoneal macrophages after treatment with 10 and 100 μM concentrations [39]. In addition, the protein expression of TNF-α and COX-2 through the regulation of peroxisome proliferator-activated receptor gamma (PPARγ) in LPS-stimulated peritoneal macrophages was suppressed by 25 and 50 µM of AA and induced similar effects on the production of inflammatory mediators including IL-1β, IL-6, Macrophage inflammatory protein (MIP)-2, and TNF-α in LPS-stimulated RAW264.7 cells after treatment with 20, 40, and 80 µmol/L of AA [16,46]. The enhancement of NO, PGE2, iNOS, COX-2, IL-1β, IL-6, and TNF-α production stimulated by LPS was inhibited by low concentrations of AA (5, 10, 20, and 40 µmol/L) in LPS-stimulated RAW264.7 cells [47]. In this study, we evaluated the potential anti-inflammatory effects of AA on AD symptoms. The levels of various inflammatory mediators were remarkably ameliorated by 10, 20, and 40 µM AA. These results are similar to those of previous studies that examined the inhibition of inflammatory mediators in LPS-stimulated macrophages after treatment with different concentrations of AA derived from different sources. Furthermore, our results suggest that AA isolated from rosin under conditions optimized by RSM has similar effects on the inflammatory response to those isolated by previously reported methods [39,46,47]. The therapeutic efficacy of AA has been studied in several animal models of inflammatory disease. The anti-allergic effects of AA were investigated in ovalbumin (OVA)-induced asthmatic mice after treatment with 10, 20, and 40 mg/kg. OVA-induced airway hyper-responsiveness, inflammatory cell infiltration, NO production, OVA-specific IgE production, cytokine secretion, and NF-κB activation were attenuated by treatment with AA isolated from P. racemosa var. grisea [22]. In addition, the wound healing effects of AA isolated from pine resin (Resina Pini) were analyzed in an ICR model with a 5 mm full-thickness excisional skin wound after treatment with 0.8 µM for 10 days based on angiogenic potential, including cell migration, tube formation, and activation of ERK/p38 in human umbilical vein vascular endothelial cells (HUVECs). Wound closure was accelerated in the AA-treated group compared with that in the control group [15]. A similar improvement effect of AA was detected in IMQ-induced psoriasis-like inflammation in a BALB/c mouse model after treatment with 40 mg/kg/day AA for 7 days. Sodium abietate decreased Psoriasis Area Severity Index (PASI) scores, ameliorated the balance of Th17/Treg cells in the spleen, decreased inflammatory cytokine secretion, and recovered the alteration of gut microbiota [20]. In this study, we investigated the mitigating effects and action mechanisms of AA, newly isolated from rosin, in an AD model as part of a study to identify novel functions of AA. Significant amelioration effects on skin thickness, dermatitis score, immune organ weight, IgE concentration, the histopathological structure of the skin, iNOS-induced COX-2 mediated pathway, and secretion of inflammatory cytokines were detected in DNCB-spread BALB/c mice after treatment with AAC for 28 days. Therefore, these results in DNCB-spread BALB/c models suggest a novel therapeutic role for AA, which has not been previously investigated. Furthermore, the results of the present study suggest that AA can successfully ameliorate inflammatory diseases. ## 4.1. RSM and Central Composite Design (CCD) Analysis RSM and CCD analysis was employed to maximize the extraction yield and improve the purity of AA from rosin. The experimental design and data analysis were performed using with a design Expert 8 program (State-Easy Co., Minneapolis, MN, USA). The ranges and coded levels of the process variables were the amount of HCl added (X1, 0.5–3.0 mL), reflux extraction time (X2, 20–90 min), and amount of ethanolamine added (X3, 0–20 mL). The dependent values were the extraction yield and purity of AA. The RSM design consisted of 17 combinations and the levels of each factor are listed in Supplementary Table S1. During optimization of the extraction yield and the purity of AA, the response could be related to chosen factors by the full quadratic model. The analysis of variance (ANOVA) was used to evaluate the significance and regression analysis was performed on the data of response variables. The quality of fit the polynomial model was expressed by the regression coefficients (R2), and its statistical significance was checked by an F test in the same program. ## 4.2. Isolation and Purification of AA from Rosin Rosin from *Pinus merkusii* was purchased from Resin Chemicals Co., Ltd. (Guangzhou, China). Freeze-dried rosin was powdered to a size of 100 µm. AA was isolated and purified under the condition optimized by RSM and CCD analysis based on the previous method [11]. Briefly, AA was purified through a series of isomerization, reaction-crystallization, and purification step (Figure 13). The amine salt of AA obtained under optimal conditions was further purified using preparative high performance liquid chromatography (HPLC) (LC-forte/R, YMC Co., Kyoto, Japan). This was carried out under isocratic conditions with $0.05\%$ formic acid in water/methanol using a YMC Triart Prep C18-S column (250 × 10.0 mm, 10 μm; YMC Co.). Purified AA was used in the present study. Voucher specimens of dried AA (WPC-22-001) were deposited at the Functional Materials Bank (FMB) of the Pusan National University (PNU)–Wellbeing RIS Center. ## 4.3. HPLC, LC-MS, and FTIR Analysis HPLC was performed to evaluate the purity of AA isolated from rosin. A HPLC system (iLC3000, Interface Engineering Co., Ltd., Seoul, Republic of Korea) with a photodiode array detector (PDA; S3210, BMS Co., Ltd., Seoul, Republic of Korea) was used. Chromatographic separation was carried out using a YMC-Triart C18 column (4.6 × 250 mm, 5 µm; YMC Co.). The mobile phase consisted of $0.1\%$ formic acid in water (Solvent A) and methanol (Solvent B). The mobile phase was methanol/water/formic acid ($\frac{87}{12.95}$/0.05), the flow rate was 0.8 mL/min, and 20 µL of the sample was injected. Compounds separated by chromatography were detected using PDA. Data acquisition and preprocessing were performed using the Clarity™ chromatography software (DataApex, Prague, Czech Republic). Liquid chromatography was carried out using an ACQUITY UPLC BEH C18 (2.1 × 100 mm, 1.7 μm) column (Waters, Milford, MA, USA). Mass spectrometric detection was performed using an Agilent 1290 Infinity HPLC system (Agilent Technologies, Waldbronn, Germany) coupled with a hybrid quadrupole time-of-flight (Q-TOF) mass spectrometer (TripleTOF 4600; AB Sciex Pte. Ltd., Framingham, MA, USA). The source parameters were as follows: gas temperature, 300 °C; gas flow, 9 L/min; nebulizer pressure, 45 psig; sheath gas temperature, 350 °C; sheath gas flow, 11 L/min; and negative mode ([M–H]− ions). The scan source parameters were a VCap 4000 V and a fragmentor voltage of 175 V. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectra were measured on an FTIR spectrometer (Nicolet iS50, Thermo Fisher Scientific Inc., Waltham, MA, USA) interfaced with an ATR device on its Monolithic Diamond ATR Crystal. Spectra were recorded in the mid-infrared (MIR) region between 4000 and 400 cm−1 (2.5–25 μm). The data obtained data were analyzed using OMNIC™ FTIR Software (Thermo Fisher Scientific Inc.). The background spectrum of the air was recorded under the same instrumental conditions before each sample was read. ## 4.4. Assay for Hyaluronidase (HAase) Inhibition Activity HAase inhibition activity was measured using the colorimetric Morgan–Elson assay with slight modification to measure the quantity of N-acetylglucosamine generated from sodium hyaluronate [48]. Each sample dissolved in dimethyl sulfoxide (DMSO; Duchefa Biochemie, Haarlem, the Netherlands) (100 mg/mL) was diluted with 0.1 M sodium acetate buffer (pH 3.5) for the test. A 12 µL sample diluted with 0.1 M sodium acetate and 12 µL of HAase (10 mg/mL) was mixed and incubated in a water bath at 37 °C for 20 min. To activate HAase, 12 µL of 12.5 mM calcium chloride was added and incubated at 37 °C for 20 min. Subsequently, 24 µL of sodium hyaluronate (6 mg/mL) was reacted with the sample mixture at 37 °C for 40 min. Both HAase and sodium hyaluronate are soluble in 0.1 M sodium acetate buffer. A total of 0.4 N potassium tetraborate and 0.4 N NaOH (12 µL) were added to quench the HAase reactions. To completely terminate HAase activity, the samples were placed in boiling water for 3 min and then on ice. Finally, 360 µL of p-dimethylaminobenzaldehyde (DMAB) solution (0.4 g of DMAB reagent in 35 mL of glacial acetic acid and 5 mL of 10 N HCl) was added to the reaction mixture with a vortex and incubated in an incubation water bath at 37 °C for 20 min. All tubes in the test were measured using a microplate reader (Tecan Sunrise, Tecan, Hombrechtikon, Switzerland) at 540 nm after centrifugation for a few seconds. The percentage of HAase activity was determined using the following equation:HAase activity (%) = (Abssample/Abscontrol) × 100 ## 4.5. Free Radical Scavenging Activity Assay The scavenging activity of AA against 1,1-diphenyl-2-picrylhydrazyl (DPPH) radicals was measured using a previously reported method [49,50]. After preparing DPPH solutions of different concentrations, 100 μL of the AA solution was mixed with the same volume of the DPPH solution, and this mixture was incubated at room temperature for 30 min in the dark. The absorbance of each mixture was measured at 540 nm wavelength using a VersaMaxTM plate reader (Molecular Devices, Sunnyvale, CA, USA). The scavenging activity of AA against DPPH radicals was represented as the half-maximal inhibitory concentration (IC50) value, which is defined as the concentration of AA inducing a $50\%$ loss in DPPH radical scavenging activity. The scavenging activity of AA against 2,2′-azino-bis (3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) radicals was determined as previously reported [51]. A total of 25 μL of 11 different concentrations of AA (1–500 µg/mL) was mixed with 250 μL of ABTS working solution and incubated at room temperature for 4 min. The absorbance of the reaction mixture was read at 734 nm using a UV-visible (UV–VIS) spectrophotometer (Thermo Fisher Scientific Inc.). Finally, the ABTS radical scavenging activity of AA was represented as the half-maximal IC50 value. The scavenging activity of AA against nitric oxide (NO) radicals was determined as reported in a previous study using the modified Jaiswal method [52,53]. Briefly, 100 µL of AA solution was mixed with 400 µL of 10 mM sodium nitroprusside and incubated at room temperature for 2.5 h. This mixture was reacted with 200 µL of Griess reagent for 30 min. Absorbance was measured at 540 nm using a VersaMaxTM plate reader (Molecular Devices). The scavenging activity of AA against NO radicals was represented as the half-maximal IC50 value. ## 4.6. Cell Culture and Viability RAW264.7, a macrophage cell line from tumor in male mouse induced with the Abelson murine leukemia virus, were selected to investigate the anti-inflammatory effects of AA because they were sensitive to the stimulation of LPS. Additionally, RAW264.7 cells were kindly provided by the Nutritional Immunology Laboratory at PNU (Prof. HM Kim). The cells were cultured in Dulbecco’s Modified Eagle’s medium (DMEM; Thermo Scientific Inc.) containing $10\%$ fetal bovine serum (FBS), 2 mM L-glutamine, 100 U/mL penicillin, and 100 μg/mL streptomycin (Thermo Scientific Inc.). RAW264.7 macrophages were cultured in a humidified incubator at 37 °C under a $5\%$ CO2 atmosphere. To determine the optimal concentration of AA, RAW264.7 macrophages (3 × 104 cells) were seeded into each well of a 96-well plate. When the cells reached 70-$80\%$ confluence, they were treated with various concentrations of AA (10, 20, 40, and 80 μM), dissolved in 1× phosphate-buffered saline (PBS) buffer, for 24 h. Supernatants were discarded after incubation for 24 h, followed by the addition of 200 μL of fresh DMEM and 50 μL of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) solution (20 mg/mL) in 1× PBS to each well, and subsequently incubated at 37 °C for 4 h. Formazan precipitates in the cells were dissolved in DMSO (Duchefa Biochemie), and the absorbance of each well was determined at 570 nm using a VersamaxTM microplate reader (Molecular Devices). Based on the above results, the optimal concentrations of AA were determined to be 10, 20, and 40 μM (Supplementary Figure S1). The optimal concentration of lipopolysaccharide (LPS) was determined using the method used to determine the optimal concentration of AA. After treatment with four concentrations of LPS (0.25, 0.5, 1, and 2 μg/mL) for 24 h, the viability of RAW264.7 macrophages was analyzed with MTT and NO assays. Based on these results, the optimal concentration of LPS was determined to be 1 μg/mL (Supplementary Figures S2 and S3). To determine the anti-inflammatory effects of AA, RAW264.7 macrophages cultured in the same manner as above were treated with LPS (1 μg/mL) for 1 h and consecutively three concentrations of AA, namely a low (LAA, 10 μM), medium (MAA, 20 μM), and high (HAA, 40 μM) concentration of AA. After further incubation for 24 h, the viability of the cells was measured by a MTT assay, as described above. The Vehicle-treated group received the same volume of DMSO solvent, but the positive (Po)-treated group received only 10 μM of standard AA (BioFront Technologies, Tallahassee, FL, USA). The NO concentration in the supernatant from each cell of the subset group was analyzed. Furthermore, the morphological characteristics of RAW264.7 macrophages for each treatment group were observed at 20× magnification using a light microscope (Leica Microsystems, Wetzlar, Germany). ## 4.7. Measurement of NO Concentration The level of nitrite, a stable reaction product generated from NO with molecular oxygen, was used as an indicator of NO production. The NO concentration in the culture supernatant of RAW264.7 macrophages was measured using Griess reagent (Invitrogen Co., Carlsbad, CA, USA) as described previously [50]. Briefly, RAW264.7 macrophages were preincubated with LPS (1 μg/mL) for 2 h and then treated with 1× PBS or AA (10, 20, and 40 μM) for 12 h. After collecting the supernatants, 100 μL of each was mixed with 100 μL of modified Griess reagent (Invitrogen Co.) in 96-well plates and incubated for 5 min. The absorbance of each well was measured at 540 nm using a VersamaxTM microplate reader (Molecular Devices). A standard curve with increasing concentrations of sodium nitrite was generated in parallel and used for quantification. ## 4.8. Experimental Design of the Animal Study The PNU Institutional Animal Care and Use Committee (IACUC) reviewed and approved the protocol for the AD animal model study (approval no. PNU-2022-0236). The mice were housed at the PNU-Laboratory Animal Resources (LAR) Center accredited by the Korean Food and Drug Administration (KFDA; unit 000231) and the Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC International; unit 001525). Male BALB/c mice (8-weeks-old) were purchased from Samtako BioKorea (Osan, Republic of Korea). Drinking water and a standard irradiated chow diet (Samtako BioKorea Co.) were provided ad libitum throughout the experimental period. All mice used in this study were reared under specific pathogen-free conditions (SPF) (50 ± $10\%$ relative humidity and 23 ± 2 °C temperature) in a strict light/dark cycle. Briefly, 8-week-old BALB/c mice ($$n = 42$$) were assigned to either a non-treated group ($$n = 7$$) or a 2,4-dinitrochlorobenzene (DNCB) spread group ($$n = 35$$). The second group was further divided into five treatment groups: vehicle cream (DNCB+Vehicle-treated group), steroid cream (LIDOMEX KOWA Ointment $0.3\%$; Kowa Company Ltd., Nagoya, Japan) (DNCB+Steroids-treated group), low concentration AA cream (DNCB+LAAC-treated group), medium concentration AA cream (DNCB+MAAC-treated group), and high concentration AA cream (DNCB+HAAC-treated group). For the first sensitization, all mice in the DNCB-treated group received a $1\%$ DNCB solution (150 μL) in acetone-olive oil (AOO, 3:1 ratio) for 3 days. After a 4-day stationary phase, $0.5\%$ DNCB solution (150 μL) in AOO was spread onto the dorsal skin three times a week for 14 days to induce a second sensitization. During this period, a cream containing vehicle, steroid or AA was spread on the same DNCB-spread skin region once a day. This cream base was prepared by mixing corn oil (C8267, Sigma-Aldrich Co., St Louis, MO, USA), dH2O, and olive wax (Orangeflower, Tokyo, Japan) (20 g: 40 g: 4 g). The DNCB+LAAC-, DNCB+MAAC-, or DNCB+HAAC-treated groups were topically spread with three types of creams containing 10, 20, or 40 mg/kg/d of AA after sufficiently drying the DNCB solution, whereas the DNCB+Steroids-treated group was spread with cream containing 50 μg/kg/day of steroid, which is the reference drugs under identical conditions. The DNCB+Vehicle group received a base cream containing $1\%$ DMSO (Duchefa Biochemie). After the final treatment, mice from all groups were sacrificed with CO2 and several tissue samples, including dorsal skin, spleen, and lymph node, were collected for weighting, histopathology, Western blot, and quantitative real-time PCR (RT-qPCR) analyses (Figure 14). ## 4.9. Measurement of Spleen Weight and Lymph Node Size After collecting spleen and lymph nodes from all mice, the spleen weight was measured using an electronic balance (Mettler Toledo, Greifensee, Switzerland). The size of each lymph node was determined using 64-bit Java 8 (NIH, Madison, WC, USA). ## 4.10. Determination of Dermatitis Score and Skin Thickness The severity of DNCB-sensitized dorsal skin was evaluated using the SCORing Atopic Dermatitis (SCORAD) index [54]. Dermatitis scores of 0 (no lesion) to 3 (severe) were assigned based on the degree of erythema, edema, papulation, excoriation, and lichenification observed on the dorsal skin. Skin thickness was measured on the last day of the experiment using a thickness gauge (Digimatic Indicator; Matusutoyo Co., Tokyo, Japan). ## 4.11. Histopathological Analysis After collecting dorsal skin tissue from BALB/c mice, it was fixed using $10\%$ neutral buffered formaldehyde (pH 6.8), dehydrated in an alcohol dilution series, trimmed with a sharp knife, and embedded in paraffin wax. Dorsal skin tissue sections were deparaffinized with xylene (DaeJung Chemicals, Siheung, Republic of Korea) and rehydrated using an alcohol dilution series (100–$70\%$). After washing with distilled water, skin tissues were stained with hematoxylin and eosin (H&E; Sigma-Aldrich Co.) and toluidine blue (TB; Sigma-Aldrich Co.). Histopathological changes were observed at 100× magnification using a Leica application suite (Leica Microsystems). The thickness of the epidermis and dermis as well as the number of mast cells and eosinophils was measured using the Leica Application Suite (Leica Microsystems). ## 4.12. Enzyme-Linked Immunosorbent Assay (ELISA) of IgE Immunoglobulin E (IgE) concentration in the serum of BALB/c mice was determined using an IgE ELISA kit (Invitrogen Co.), according to the manufacturer’s instructions. Briefly, the same volume (50 μL) of serum samples and standards diluted with a dilution solution was added to antibody-coated wells and subsequently incubated for 2 h at room temperature. The wells were then washed three times with a washing solution (50 mM Tris, 0.14 M NaCl, $0.05\%$ Tween 20, pH 8.0), followed by the addition of 50 μL biotin-conjugated avidin (1000-fold dilution) to each well and incubation for 2 h at room temperature. After washing, horseradish peroxidase-conjugated antibodies (2000-fold dilution) were added to each well and incubated for 1 h at room temperature. The enzyme reaction was initiated by adding tetramethylbenzidine (TMB) substrate solution in the dark for 20 min. Finally, the reaction was terminated by adding an acidic solution (reaction stopper, 2 M H2SO4), and the absorbance of the yellow product was measured spectrophotometrically at 450 nm using a VersamaxTM microplate reader (Molecular Devices). ## 4.13. Western Blot Analysis Total protein from RAW264.7 macrophages and homogenates of mouse dorsal skin tissues was obtained using Pro-Prep Protein Extraction Solution (iNtRON Biotechnology, Seongnam, Korea) according to the manufacturer’s protocol. After centrifugation at 13,000 rpm for 5 min, the protein concentration of the supernatant was determined using a PierceTM bicinchoninic acid (BCA) Protein Assay Kit (Thermo Fisher Scientific Inc.). They were separated by 4-$20\%$ sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for 2 h, followed by transfer to nitrocellulose membranes (AmershamTM ProtranTM, GE Healthcare, Chicago, IL, USA) at 40 V for 2 h. Membranes were then incubated overnight at 4 °C with the following primary antibodies: iNOS (Cell Signaling Technology, Danvers, MA, USA), COX-2 (Cell Signaling Technology), SAPK/JNK antibody (Cell Signaling Technology), p-SAPK/JNK (Thr183/Tyr185) antibody (Cell Signaling Technology), p$\frac{44}{42}$ MAPK (ERK$\frac{1}{2}$) antibody (Cell Signaling Technology), p-p$\frac{44}{42}$ MAPK (ERK$\frac{1}{2}$; Thr202/Tyr204) antibody (Cell Signaling Technology), p38 MAPK antibody (Cell Signaling Technology), p-p38 MAPK (Thr180/Tyr182) antibody (Cell Signaling Technology), NLRP3 (Cell Signaling Technology), ASC/TMS1 (Cell Signaling Technology), Caspase-1 (Cas-1, Cell Signaling Technology), and anti-β-actin antibody (Cell Signaling Technology). Next, the membranes were washed with washing buffer (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, and $0.05\%$ Tween 20) and incubated with 1:1000 diluted horseradish peroxidase (HRP)-conjugated goat anti-rabbit IgG (Cell Signaling Technology) at room temperature for 1 h. Finally, membrane blots were developed using the EZ-Western Lumi Femto Kit (Dogen, Seoul, Korea). The chemiluminescence signals originating from specific bands were detected using FluorChemi®FC2 (Alpha Innotech, San Leandro, CA, USA). ## 4.14. Quantitative Real-Time-PCR (RT-qPCR) Analysis RT-qPCR was used to measure iNOS, COX-2, tumor necrosis factor (TNF)-α, IL-1β, IL-4, IL-5, IL-6, and IL-10 mRNA levels as previously described [50]. First, total mRNA was purified from RAW264.7 macrophages and dorsal skin tissues of the subset groups using TRIzol reagent (Favorgen Biotech, Ping-Tung, Taiwan), according to the manufacturer’s protocol. After determining the total RNA concentrations, complementary DNA (cDNA) was synthesized using Superscript II reverse transcriptase (Thermo Fisher Scientific Inc.), and RT-qPCR was performed using the cDNA template (2 μL) and 2× Power SYBR Green (7 μL; Toyobo Life Science, Osaka, Japan) containing specific primers (Supplementary Table S2). RT-qPCR was performed for 40 cycles of denaturation at 95 °C for 15 s, annealing at 70 °C for 60 s, and extension at 70 °C for 60 s. Fluorescence intensities were measured at the end of the extension phase of each cycle. Threshold values for sample fluorescence intensities were set manually and reaction cycles in which the PCR products exceeded these fluorescence intensity thresholds during the exponential phase were considered threshold cycles (Ct). The expression of iNOS, COX-2, TNF-α, IL-1β, IL-4, IL-5, IL-6, and IL-10 was quantified relative to that of the housekeeping gene β-actin, based on a comparison of the Ct values at constant fluorescence intensity [55]. ## 4.15. Statistical Analysis One-way ANOVA was used to determine the statistical significance between the Vehicle+LPS-treated group and the AA+LPS-treated group, as well as between the DNCB+Vehicle-treated group and DNCB+AAC-treated group, and a p-value less than 0.05 was reported as statistically significant. All values in the results are presented as mean ± standard deviation (SD). ## 5. Conclusions In the present study, we attempted to establish the optimal condition for AA isolation as well as to demonstrate the novel therapeutic effects of AA against AD using an animal disease model. To achieve this objective, the conditions for isomerization and crystallization were applied to RSM and CCD analysis, and the anti-inflammatory effects of AA were confirmed in LPS-stimulated RAW264.7 macrophages. The purity and yield of AA from rosin were significantly improved to $99.33\%$ and $58.61\%$ compared to the previous methods under a certain amount of HCl (2.49 mL), reflux extraction time (61.7 min), and ethanolamine (7.35 mL). In addition, anti-AD effects and mechanisms—including the dermatitis score, IgE concentration, skin histopathological structure of the skin, iNOS-induced COX-2 mediated pathway, and the secretion of inflammatory cytokines—were investigated in DNCB-treated BALB/c mice (Figure 15). The results of the present study provide the first scientific evidence that AA has the potential to ameliorate AD symptoms and identify molecular targets related to the condition. 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--- title: Diet Quality, Microbial Lignan Metabolites, and Cardiometabolic Health among US Adults authors: - Nicholas A. Koemel - Alistair M. Senior - Tarik Benmarhnia - Andrew Holmes - Mirei Okada - Youssef Oulhote - Helen M. Parker - Sanam Shah - Stephen J. Simpson - David Raubenheimer - Timothy P. Gill - Nasser Laouali - Michael R. Skilton journal: Nutrients year: 2023 pmcid: PMC10054147 doi: 10.3390/nu15061412 license: CC BY 4.0 --- # Diet Quality, Microbial Lignan Metabolites, and Cardiometabolic Health among US Adults ## Abstract The gut microbiome has been shown to play a role in the relationship between diet and cardiometabolic health. We sought to examine the degree to which key microbial lignan metabolites are involved in the relationship between diet quality and cardiometabolic health using a multidimensional framework. This analysis was undertaken using cross-sectional data from 4685 US adults (age 43.6 ± 16.5 years; $50.4\%$ female) participating in the National Health and Nutrition Examination Survey for 1999–2010. Dietary data were collected from one to two separate 24-hour dietary recalls and diet quality was characterized using the 2015 Healthy Eating Index. Cardiometabolic health markers included blood lipid profile, glycemic control, adiposity, and blood pressure. Microbial lignan metabolites considered were urinary concentrations of enterolignans, including enterolactone and enterodiol, with higher levels indicating a healthier gut microbial environment. Models were visually examined using a multidimensional approach and statistically analyzed using three-dimensional generalized additive models. There was a significant interactive association between diet quality and microbial lignan metabolites for triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, insulin, oral glucose tolerance, adiposity, systolic blood pressure, and diastolic blood pressure (all $p \leq 0.05$). Each of these cardiometabolic health markers displayed an association such that optimal cardiometabolic health was only observed in individuals with both high diet quality and elevated urinary enterolignans. When comparing effect sizes on the multidimensional response surfaces and model selection criteria, the strongest support for a potential moderating relationship of the gut microbiome was observed for fasting triglycerides and oral glucose tolerance. In this study, we revealed interactive associations of diet quality and microbial lignan metabolites with cardiometabolic health markers. These findings suggest that the overall association of diet quality on cardiometabolic health may be affected by the gut microbiome. ## 1. Introduction Cardiometabolic risk factors such as hypertension, elevated fasting blood sugar, dyslipidemia, and abdominal obesity have increased in prevalence over the past two decades [1,2]. Collectively, cardiometabolic disorders were responsible for more than 4.8 million deaths among the US working-age (ages 25–64) population between 1990 and 2017 [3]. A spectrum of modifiable risk factors, including environment, lifestyle, and diet, have been identified for cardiometabolic disorders. From a nutrition standpoint, there are many components of diet quality that can impact cardiometabolic health, including fiber, sodium, fatty acids, added sugars, polyphenols, and antioxidants [4]. Adherence to higher overall diet quality has been shown to improve overall cardiometabolic health [5,6]. It is well established that diet quality and microbial metabolism interact to influence multiple processes relevant to cardiometabolic health [7,8]. The gut microbiota is involved in the production and release of metabolites to systemic tissue, extraction of nutrients, synthesis of specific vitamins, alteration of gastrointestinal hormones, and nerve function [9,10,11]. Microbial metabolites have been further implicated in host metabolic regulation of inflammation [12], lipid metabolism [13], and type 2 diabetes risk [14]. Previous studies reported that the gut microbiome plays an important role in the protective effects observed from consuming healthy dietary patterns, such as a Mediterranean diet [13] or an anti-inflammatory diet [15]. Plant foods are rich sources of polyaromatic compounds via lignans and flavonoids found in their cell walls [16]. Lignans have been of particular interest as substances responsible for the beneficial effect of consuming nuts, fruits, vegetables, whole grains and overall plant-based diets. The gut microbiota plays an important role in this benefit by converting the dietary plant lignans to produce more bioactive enterolignans, such as enterolactone and enterodiol. On the other hand, unhealthy foods containing high amounts of saturated fat, refined sugars, emulsifiers, and sodium have been shown to elicit negative effects on microbial health [17]. Diets containing large amounts of processed foods have been linked to lower microbial diversity [18], reduced abundance of beneficial taxa [19], and ultimately a lower capacity to produce cardioprotective microbial metabolites such as enterolignans [20]. The bidirectional association between both healthy (plant-based) and unhealthy dietary components with the gut microbiome suggests a complex interplay with cardiometabolic health. However, the degree to which overall diet quality, gut microbiota function, and cardiometabolic disorders interact has not been fully defined. The National Health and Nutrition Examination Survey (NHANES) offers the opportunity to explore these relationships on a larger scale using a cross-sectional design. In the absence of microbial taxonomic composition or various other microbial metabolites, we explored enterolactone and enterodiol, which serve as a surrogate marker of gut microbiota function. Diet quality was evaluated using the Health Eating Index 2015 (HEI) in order to capture both healthy and unhealthy components of the diet. To better quantify and visualize the associations with cardiometabolic health, we applied a multidimensional approach that has previously demonstrated the ability to capture relationships not achievable by traditional univariate analyses [21,22,23]. In the present study, we hypothesized that microbial lignan metabolites would support a potential effect-modifying role of the gut microbiome on the relationship between diet quality and cardiometabolic health. ## 2.1. Study Population This study examined data from the NHANES dataset collected annually in the US by the National Center for Health Statistics. This ongoing cross-sectional survey aims to assess the nutritional intake and overall health of those living in the US. NHANES data were collected from 1999 to 2010 for participants aged 20 and older. Dietary data were collected by a trained nutritional professional via two separate dietary recalls. An initial 24 h recall was collected during the in-person interview and the second recall was conducted 3–10 days later by telephone. Additionally, participants who reported having cardiovascular disease ($$n = 668$$), cancer ($$n = 511$$), diabetes ($$n = 523$$), or related medication ($$n = 4788$$), were excluded from the primary analysis (Figure S1). ## 2.2. Urinary Enterolignans Enterolactone and enterodiol were measured from urine samples collected at the initial interview in those who had fasted a minimum of 9 h and immediately stored at −20 °C until processing. High-performance liquid chromatography was then used to quantify the concentration of enterolactone and enterodiol in the urine. Antibiotic consumption has the potential to influence urinary enterolignan concentration by destroying the intestinal microflora [24], so individuals who reported taking antibiotics within a month of the collected enterodiol or enterolactone sample were excluded ($$n = 9$$) [25]. Enterodiol and enterolactone values were log-transformed to address skewness. ## 2.3. The Healthy Eating Index The most recent HEI was developed in 2015 to measure overall diet quality and presents a composite measure of conformance to the 2015–2020 Dietary Guidelines for Americans [26]. The HEI is a 100-point scale, with a higher score indicating better overall diet quality. The adequacy components include total fruit [5], whole fruits [5], total vegetables [5], greens and beans [5], whole grains [10], dairy [10], total protein foods [5], seafood and plant proteins [5], and fatty acids (ratio of the sum of polyunsaturated and monounsaturated fatty acids to saturated fatty acids—10). The moderation components include refined grains [10], sodium [10], added sugars [10], and saturated fats [10]. ## 2.4. Cardiometabolic Health A sample of participants was selected for measurement of fasting serum glucose, insulin, hemoglobin A1c (HbA1c), total cholesterol (Total-C), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides. An oral glucose tolerance test (OGTT) was administered using a calibrated dose of glucose drink (TrutolTM, Thermo Scientific, Waltham, MA, USA) providing on average 75 g of glucose. Postprandial glucose was measured 2 h after the consumption of the glucose drink. Body fat percentage was estimated via bioelectrical impedance. Systolic and diastolic blood pressure was measured 3–4 times via sphygmomanometer and the average of the measurements used in the analysis. Height and weight were collected by a trained professional following standardized operating procedures, with body mass index (BMI) calculated as weight divided by height in meters squared (kg/m2). ## 2.5. Demographic and Lifestyle Covariates All demographic and lifestyle covariates were self-reported via questionnaires. Race and ethnicity were categorized as either non-Hispanic white, non-Hispanic black, Hispanic, or other. Level of education was categorized as less than high school, high school, or some college and above. Socioeconomic status was calculated using household income to poverty ratio. Participants were classified as smokers if they reported smoking >100 cigarettes in their lifetime. Alcohol consumption was categorized as “drinkers” and “nondrinkers,” where those who drank a minimum of 12 drinks within any given year prior to the assessment were considered drinkers. Physical activity was determined using self-reported metabolic equivalents of weekly moderate to vigorous leisure activity. In the case of a missing value, the mean value of the covariate was utilized. ## 2.6. Statistical Analysis For the present study, individuals with potential over- or underreporting for dietary energy intake were excluded (males < 800 or >4200 kcal/day and females < 600 or >3500 kcal/day; $$n = 8087$$). Participants were also excluded if consuming macronutrients greater or fewer than three standard deviations from the mean ($$n = 387$$). Associations of dietary quality, enterolactone, enterodiol, and cardiometabolic health markers were explored using generalized additive models (GAMs). GAMs are a dynamic form of multivariable regression that can be used to test for and visualize complex nonlinear associations [27]. Models include smooth terms that handle more complex dimensions of data and varying scales. For each cardiometabolic marker, a series of GAMs including additive and interactive associations was implemented to sequentially explore the complex relationship between HEI score, total energy intake, and either enterolactone or enterodiol (Table S1). The most complex model contained a three-dimensional smooth term that included HEI score, total energy intake, and either enterolactone or enterodiol. Total energy intake was included in the smooth term as an adjustment approach [28] while simultaneously allowing for us to explore visual differences at varying energy intakes. A series of models was then designed to sequentially adjust for confounding variables as additive terms. Model one was adjusted for age, sex, and socioeconomic status. Model two further was adjusted for sociodemographic characteristics, including race/ethnicity and education. Model three was the fully adjusted model and further adjusted for lifestyle factors, such as alcohol consumption, smoking, BMI, and physical activity. All models were constructed using the “gam” function of the mgcv package in R statistical software (v. 1.8–41; R Core Team; Vienna, Austria) [29,30]. Associations were visualized using three-dimensional response surfaces, where each cardiometabolic health marker was plotted as a response surface at the 25th, 50th, and 75th percentile of total energy intake. Response surfaces show the outcome on a scale with warmer colors denoting higher values and cooler colors denoting lower values. A statistically significant three-dimensional term for the exposures of interest can be interpreted such that the association between HEI with cardiometabolic health depends on the urinary enterolignan and total energy intake. To explore the degree to which cardiometabolic health outcomes are related to HEI across a spectrum of microbial lignan metabolite levels, we display the response surfaces at the 50th percentile of total energy intake. Additional figures are provided in the online supplement presenting the associations at the 25th, and 75th percentile of total energy intake. Values were estimated using generalized crossed validation and checked for overfitting. Interaction between sex with each biomarker was explored using the “by” term in the “gam” function of mgcv. The Akaike information criterion (AIC) was used as a measure for model comparison, with lower values indicating better fit relative to the increase in model complexity. A difference in AIC > 2 was considered evidence of a better overall model fit [31]. Sex-stratified analyses were also undertaken for each of the cardiometabolic health markers. A sensitivity analysis using waist circumference instead of BMI was conducted to act as a better indicator of central adiposity. ## 3.1. Participant Characteristics Participant characteristics are presented in Table 1. This analysis included 4685 US adults (43.6 ± 16.5 years; $50.4\%$ female). Participants were predominantly non-Hispanic white ($46.6\%$) and overweight with an average BMI of 28.5 ± 6.5 kg/m2. ## 3.2. Generalized Additive Model Exploration The series of potential interactive and additive models we used for exploring cardiometabolic health markers is shown in Table S1. Marginal differences were observed when comparing deviance explained and AIC values for the various models. Notably, triglycerides and oral glucose tolerance test were the only biomarkers that favored the more complex three-way interactive model. ## 3.3. Blood Lipids The association of microbial lignan metabolites and HEI with blood lipids at the 50th percentile of energy intakes is shown in Figure 1 and model coefficients are displayed in Table 2. Results at the 25th and 75th percentile of energy intakes are displayed in Figures S2–S5. There was a statistically significant association with enterolactone and enterodiol displayed for triglycerides (all p ≤ 0.002), LDL cholesterol (all p ≤ 0.04), and HDL cholesterol (all $p \leq 0.001$). Urinary enterolactone levels appeared to be inversely associated with plasma triglycerides in people with HEI above the mean, with the highest triglyceride levels being present at <1 μmol/L (log-transformed) enterolactone and the lowest triglycerides at around 4 μmol/L (log-transformed). Enterodiol showed a potential interactive association with HEI, evidenced by the bending contour lines particularly prominent at higher levels of HEI and enterodiol (Figure 1A). These associations appeared similar across energy intakes, albeit that higher overall triglycerides were observed at the 25th percentile of energy intake (Figure S2). LDL cholesterol was primarily associated with HEI for both enterolactone and enterodiol (Figure 1B). Across energy intakes, the association remained similar, but the lowest LDL cholesterol values were observed with higher energy intake coupled with higher HEI and enterodiol. The inverse was apparent for enterolactone, where the lowest LDL cholesterol was evident in those with the lowest energy intake coupled with the highest HEI and enterolactone (Figure S3). Visually, HDL cholesterol followed an interactive association for both enterolactone and enterodiol (Figure 1C). This appeared similar across energy intakes, although at the upper level of energy intake, HEI appeared to have a slightly stronger positive association with HDL (Figure S4). We did not identify any association with total cholesterol in the fully adjusted model (Figure S5 and Table 2). When adjusting for waist circumference instead of BMI, all associations remained the same except for LDL and enterolactone, which become nonsignificant (Table S2). Male and female stratified results for cardiometabolic health markers are shown in Figures S6 and S7; Tables S2 and S3. When formally comparing the AIC values, there was strong support of a sex difference between blood lipid models. We found a positive association for enterodiol and triglycerides for both males and females (p ≤ 0.001). Visually, males and females had a similar response surface to the pooled analysis for the association of enterolactone with triglycerides; however, this only reached statistical significance in females ($$p \leq 0.008$$). HDL cholesterol was statistically significant in both males and females ($p \leq 0.001$), with little difference in the response surface compared to the pooled analysis. Evidence for an interaction with sex was revealed for triglycerides (Table S4). ## 3.4. Glycemic Control The relationship between energy intake, microbial lignan metabolites, and HEI with markers of glycemic control is shown in Figure 2 and model coefficients are displayed in Table 2. Enterolactone revealed a weak interactive association with HEI for fasting insulin levels (Figure 2A). The highest fasting insulin appeared in those with the lowest HEI and enterolactone levels. Enterodiol associations were more complex with the highest insulin at low HEI and enterodiol, but this became less apparent beyond an enterodiol of 2 μmol/L (log-transformed). These associations also displayed differences across energy intake, where the highest fasting insulin was observed at lower energy intake coupled with lower HEI and lower enterodiol. At higher energy intake, the association became more HEI dominated. For enterolactone, the highest fasting insulin was apparent at higher energy intakes, but at lower HEI and lower overall enterolactone (Figure S8). In the fully adjusted model, OGTT was significantly associated with enterodiol ($$p \leq 0.03$$) and had a near-significant association with enterolactone ($$p \leq 0.08$$). Enterolactone and enterodiol both displayed a strong negative association with OGTT responses, with near-vertical contour lines across the enterodiol and enterolactone spectrum (Figure 2B). For enterodiol and enterolactone, the overall association was stronger at lower energy intakes (Figure S9). There was no significant association identified for fasting glucose or HbA1c (Figures S10 and S11; Table 2). For waist circumference sensitivity, all associations remained the same except the association between OGTT and enterodiol, which became nonsignificant (Table S2). In the sex-stratified analysis, there was strong support for a sex difference between models of glycemic control comparing the model AIC values (Figures S6 and S7; Tables S2 and S3). Fasting glucose was significant only with enterodiol in males ($$p \leq 0.03$$). The response surface revealed a robust negative association between enterodiol levels and fasting glucose independently of HEI. Males had a significant association with HbA1c, but only for enterodiol ($$p \leq 0.007$$). Females had a significant association with both enterolactone and enterodiol with insulin ($p \leq 0.001$), with response surfaces suggesting a strong negative association with HEI. There was no evidence of an interaction by sex in any of the markers of glycemic control (Table S4). ## 3.5. Adiposity and Blood Pressure The relationship between energy intake, microbial lignan metabolites, HEI with adiposity and blood pressure is shown in Figure 3 and model coefficients are displayed in Table 2. Adiposity had a significant interactive association with HEI and both enterodiol ($$p \leq 0.02$$) and enterolactone ($$p \leq 0.007$$). Adiposity was lowest in participants who had high HEI in combination with high levels of enterolactone (Figure 3A). For enterodiol, adiposity had a stronger HEI association, where the lowest adiposity was observed in those with the highest HEI (Figure 3B). At lower energy intakes, higher adiposity was observed in individuals with low enterolactone despite higher HEI scores. However, at higher energy intake, the association appears to become slightly more HEI-dominated (Figure S12). A significant interactive association was detected for both enterodiol and enterolactone with systolic blood pressure ($p \leq 0.001$). Visually, systolic blood pressure was highest in those with low HEI and low enterolactone or low enterodiol. Diastolic blood pressure was also significantly associated with enterolactone ($$p \leq 0.005$$) and enterodiol ($$p \leq 0.007$$), displaying a near-identical relationship, as seen with systolic blood pressure (Figure 3C). Both systolic and diastolic blood pressure showed similar associations across energy intakes, but with a stronger association with enterodiol and enterolactone at lower energy intakes (Figures S13 and S14). There were no significant changes for adiposity and blood pressure in the waist circumference sensitivity analysis (Table S2). There was strong support of a sex difference between models of adiposity and blood pressure when comparing AIC values (Figures S6 and S7; Tables S2 and S3). Systolic blood pressure was significantly associated with both enterolactone ($$p \leq 0.003$$) and enterodiol for males ($$p \leq 0.04$$). In females, only enterodiol was significantly associated with systolic blood pressure ($$p \leq 0.04$$). Only females demonstrated a significant association with diastolic blood pressure and microbial lignan metabolites (enterolactone: $$p \leq 0.04$$; enterodiol: $$p \leq 0.03$$). Both markers visually displayed an interactive association similar to the pooled analyses. There was no evidence of an interaction by sex for adiposity or blood pressure (Table S4). ## 4. Discussion Using a large sample of US adults, we explored the potential associations between diet quality and microbiome lignan metabolites with cardiometabolic health across low, medium, and high levels of energy intake using three-dimensional visualization. Across all energy intake levels, gut microbiome metabolites, and the HEI were interactively associated with most cardiometabolic markers evaluated in this study. Generally, we found that higher levels of enterodiol or enterolactone in combination with greater adherence to the HEI were associated with more optimal cardiometabolic health. Numerous studies have provided evidence that diet quality plays a role in cardiometabolic health [32,33]. The HEI provides a measure of adherence to the Dietary Guidelines for Americans and encompasses multiple dimensions of diet quality, including high-quality plant-based food items and dietary components related to unhealthy foods. The HEI emphasizes a higher consumption of fruit, vegetables, whole grains, and nuts and legumes while limiting sodium, refined grains, added sugar, and saturated fat [26]. Adherence to a diet with a high HEI score is associated with protective effects against obesity, diabetes mellitus, dyslipidemia, and hypertension [34,35,36]. Experimental evidence supports that the relationship between both beneficial [13] and detrimental components [32] of diet quality with cardiometabolic health is partially mediated through the gut microbiome. Unlike the complex interplay identified in this analysis, various studies have investigated the independent role of the diet or the gut microbiome on cardiometabolic health [37]. An altered gut microbiome composition has been well documented to influence the development of metabolic disorders such as obesity, diabetes mellitus, dyslipidemia, and hypertension [38,39,40]. The potential mechanisms have been summarized recently by Kazemian et al. [ 41]. Such an association can be through indirect (via the immune system) and direct (via metabolites such as enterodiol and enterolactone) pathways [39,40]. Microbial lignan metabolites have several biological functions, such as antioxidant and ligand activity [42]. This includes increasing hepatic LDL cholesterol receptor activity [43] and acting as an antagonist of platelet-activating factor [44]. Together, these metabolites provide several potential mechanisms for reducing the risk of cardiometabolic diseases. Understanding the interplay between diet and gut microbiome metabolites on cardiometabolic diseases is of public health and clinical importance. These results highlight this importance by demonstrating the potential magnitude to which the gut microbiome may modify the relationship between diet quality and cardiometabolic health outcomes. Moreover, gut health may be an influential characteristic to consider when aiming to optimize cardiometabolic health with dietary modifications. In line with our results, Asnicar et al. revealed numerous relationships between microbes, dietary nutrients, and several dietary indices, suggesting that the microbiome modulates the effect of the diet on both fasting and postprandial cardiometabolic health [45]. Moreover, a recent study on overall dietary lignan intake and cardiometabolic risk in men ($$n = 911$$) reported that both gut microbial species and plasma enterolactone levels accounted for a significant proportion of the association observed [46]. Of the relationship between dietary lignan intake and metabolic health, microbial species alone explained $19.8\%$ ($95\%$ CI: 7.3–$43.6\%$), while species and enterolactone levels collectively explained $54.5\%$ ($95\%$ CI: 21.8–$83.7\%$) of the relationship. The interplay of diet quality and gut microbiome metabolites on cardiometabolic health is biologically plausible, as diet may potentially modulate production of gut microbiome metabolites by altering the gastrointestinal microbiota composition. Previous studies have shown an increased gut microbial diversity among people with higher fiber intake [47]. In contrast, digestible simple sugars inhibit the colonization of beneficial commensal microbial species in the murine gut and promote the development of obesity [48]. Our findings also identified the potential of sex-specific differences. Specifically, response surfaces were slightly different for females and males, suggesting the beneficial associations between enterolactone and enterodiol with cardiometabolic markers may be more pronounced in males compared to females. These findings accord with previous studies that demonstrate an influential effect of biological sex on the physiology and pathology of cardiometabolic diseases [49]. Other studies have also reported sex differences in the association between gut microbiome and cardiometabolic disease [50]. The mechanisms are not fully understood, although studies suggest a complex bidirectional interaction between the microbial community and sex hormones [51]. ## Strengths and Limitations This study has several strengths, including the analysis of a large sample of US adults and the use of objective laboratory values of urine enterolignan levels and serum cardiometabolic marker measurements. To our knowledge, this is the first study to incorporate a multidimensional framework to visualize the relationship between diet, microbial lignan metabolites, and cardiometabolic health. Unlike traditional epidemiological approaches, this technique enables us to visually capture the complex relationships and how they differ in magnitude for each cardiometabolic marker. However, this study also has several limitations. The complex NHANES survey design weights could not be applied in this study because the R package used does not allow it, thus preventing these results from being generalized to the entire US population. However, it has been suggested that weighted analyses can be inefficient due to the large variability in assigned weights [52]. The unweighted analysis can yield correct estimates when models are adjusted for the auxiliary variables used to define the weights (i.e., age, sex, and ethnicity). Another limitation is the cross-sectional design of NHANES such that the results cannot support causal inferences about the relationships between diet, gut microbiome metabolites, and cardiometabolic health. In addition, reverse causality is possible given the cross-sectional design. As discussed, several previous longitudinal studies have demonstrated individual associations between adherence to the HEI with enterodiol and enterolactone and cardiometabolic diseases. Diets with a higher HEI score often include more plant-based food items with a greater overall lignin content. Furthermore, the relationship between HEI and lignin-containing food items may have partially influenced some of the observed results. In addition, the dietary consumption data used to calculate the HEI was collected via 24 h recalls and may not represent the usual dietary intake of individuals, as under- or overreporting frequently occurs. Lastly, this study did not consider the consumption of dietary supplements. ## 5. Conclusions This study applied a novel multidimensional approach to explore the relationship between diet quality, microbial lignan metabolites, and cardiometabolic health among US adults. We revealed that enterolactone and enterodiol affect the relationship of diet quality with blood lipids, glycemic control, adiposity, and blood pressure. 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--- title: The microRNA Cargo of Human Vaginal Extracellular Vesicles Differentiates Parasitic and Pathobiont Infections from Colonization by Homeostatic Bacteria authors: - Paula Fernandes Tavares Cezar-de-Mello - Stanthia Ryan - Raina N. Fichorova journal: Microorganisms year: 2023 pmcid: PMC10054151 doi: 10.3390/microorganisms11030551 license: CC BY 4.0 --- # The microRNA Cargo of Human Vaginal Extracellular Vesicles Differentiates Parasitic and Pathobiont Infections from Colonization by Homeostatic Bacteria ## Abstract The disturbed vaginal microbiome defined as bacterial vaginosis (BV) and the parasitic infection by *Trichomonas vaginalis* (TV), the most common non-viral sexually transmitted pathogen, have well-established adverse effects on reproductive outcomes and susceptibility to infection and cancer. Molecular mechanisms underlying these associations and the failure of antibiotic therapy to mitigate adverse consequences are not fully elucidated. In an in vitro human vaginal colonization model, we tested the hypothesis that responses to TV and/or BV-bacteria will disrupt the micro(mi)RNA cargo of extracellular vesicles (EV) with the potential to modify pathways associated with reproductive function, cancer, and infection. miRNAs were quantified by HTG EdgeSeq. MiRNA differential expression (DE) was established in response to TV, the BV signature pathobiont *Prevotella bivia* and a homeostatic *Lactobacillus crispatus* with adjusted $p \leq 0.05$ using R. *Validated* gene targets, pathways, protein-protein interaction networks, and hub genes were identified by miRWalk, STRING, Cytoscape, and CytoHubba. In contrast to L. crispatus, TV and the BV pathobiont dysregulated a massive number of EV-miRNAs, over $50\%$ shared by both pathogens. Corresponding target pathways, protein interaction clusters and top hub genes were related to cancer, infectious disease, circadian rhythm, steroid hormone signaling, pregnancy, and reproductive tissue terms. These data support the emerging concept that bacteria and parasitic eukaryotes disturbing the human vaginal microbiome may impact reproductive health through EV-miRNA dysregulation. ## 1. Introduction The influence of the human microbiome on health or disease is an evidence-based scientific consensus [1,2,3,4]. The intricate relationship between human host cells and a diverse multispecies community has been shaped throughout evolution and is key to understanding how a dysbiotic environment challenges human health. The lower and upper portions of the human female reproductive tract (FRT) are differentially colonized [5], while the lower FRT (including the vagina and uterine cervix) is more diversely populated by commensal and regular residents [6]. The vaginal microbiota has been classified by microbiome sequencing into five distinct community state types (CST) based on the predominance of certain lactobacillus species or bacterial pathobionts [7]. Conceptually, the ‘core microbiome’ [8] of a healthy vagina is featured by the predominance of three species of the genus Lactobacillus (L. crispatus—CSTI, L. gasseri—CSTII and L. jensenii—CSTV) [9] and by their ecological relationships with additional biotic components, plus intrinsic and exogenous factors. L. crispatus, L. gasseri, and L. jensenii can deliver a mucosal environment protective against ascendance of pathogens to the upper FRT [10]. Disturbances in this ecosystem may lead to a dysbiotic environment (CST-IV, 7–10 Nugent score and pH > 5), such as bacterial vaginosis (BV) syndrome, characterized by the reduction in lactobacillus species and majority of obligate anaerobic polymicrobial spectrum [6] where *Prevotella bivia* is the most common BV-associated pathobiont bacteria [11,12] prevailing along with Gardnerella vaginalis, and *Atopobium vaginae* [7]. Sequencing of the cervical microbiome also ranked the L. crispatus-dominated CST as the least proinflammatory, and the P. bivia-dominated as the most proinflammatory, hence, pathogenic CST [13]. BV is linked with an increased risk of developing urogenital cancer, obstetric complications, and acquiring sexually transmitted infections (STIs) [6], including human papillomavirus (HPV) [14,15], human immunodeficiency virus (HIV) [16,17] and *Trichomonas vaginalis* (T. vaginalis) [18], the causative agent of trichomoniasis. Trichomoniasis is the leading global cause of non-viral STIs [19]. T. vaginalis may cause subclinical to asymptomatic infections in roughly $50\%$ of women and over $70\%$ of men, which contributes to underestimating global rates of infection and collaborates with a sustained transmission chain [20]. Like BV, T. vaginalis-infected individuals are at higher risk of acquiring other STIs, including HIV, and developing cervical and prostate cancer [20]. T. vaginalis infections also share with BV adverse effects on obstetrical outcomes, e.g., preterm birth (PTB), low birth weight, and premature rupture of membranes [20,21,22]. Although curable, T. vaginalis and BV-associated poor pregnancy outcomes may persist after antibiotic treatment and pathogen elimination [20,23]. The causation of the persistence of perinatal adversities after parasite clearance is uncertain. Multiple mechanisms of treatment failure have been suggested including innate immunity dysregulation due to endosymbiotic T. vaginalis virus (TVV) shed by the parasite during antibiotic treatment [24] and modification of the vaginal microbiome by the parasite which may result in persistent BV [6,25,26]. We hypothesize that a homeostatic failure following T. vaginalis infection could be at least in part driven by the host epigenome dysregulated by both the parasite and BV pathobionts. A key element of the epigenome regulated by host-microbe interactions is represented by the human micro(mi)RNA transcriptome (miRNome). miRNAs are small single-strand (~22nt long) non-coding RNAs known to negatively modulate gene expression at the post-transcriptional level. The canonical way of miRNA-led post-transcriptional regulation is by promoting mRNA degradation or translational repression [27] by base paring the 5′-proximal seed region (nucleotide 2 to 8) of the miRNA with mRNA 3′UTR [28,29], ultimately leading to gene silencing [29]. miRNA expression is sensitive to myriad pathologies; therefore, investigating such dysregulation would provide opportunities to understand the molecular mechanism underlying health and disease, identify miRNA:mRNA therapeutic targets of high importance, and relevant biological process. Although miRNA expression may be cell/tissue-specific, they eventually will be exchanged between cells to exert paracrine regulation. MiRNAs also stably circulate in many body fluids in the form of protein complexes or encased in extracellular vesicles (EV)—groups of right-side-out membranous vesicles which differ in size and cellular biogenesis origin. Due to its specific and selected cargo—a cocktail of proteins, lipids, nucleic acid, and glycans—EVs are mediators of same-species and cross-kingdom cell-cell communications [30], and hence, lend themselves as players of post-transcriptional and potentially epigenetic regulation directed by EV-contained miRNAs (EV-miRNAs). A growing number of studies have aimed to characterize the interplay of EVs in relevance to parasite-host interactions [31], including T. vaginalis [32,33,34,35]. However, there is a lack of studies on EV-miRNAs released by the human vaginal epithelium in response to parasitic infection and no comparative causative evaluation of vaginal pathogens and homeostatic bacteria. In this study we tested experimentally the hypothesis that colonization of human vaginal cells by T. vaginalis and/or BV-associated bacteria will disrupt the EV-miRNAs cargo, with the potential to target molecular pathways underlying some of the long-lasting systemic effects and reproductive disorders. Using a well-validated human in vitro infection model, we identified: [1] EV-miRNAs differentially released by vaginal epithelial cells upon disruptive (T. vaginalis or P. bivia) versus homeostatic (L. crispatus) colonization suggesting causality; and through in silico miRNA target prediction [2] genes and pathways of failed homeostasis along with disrupted protein-protein interaction networks with highest connectivity and hence highest potential to discover novel approaches to treatment and prevention of disease. ## 2.1. Experimental Model Human vaginal epithelial cells (Vk2/E6E7) derived from a healthy tissue following vaginal repair surgery [36] were grown (6 × 105 cells/mL) to 80–$90\%$ confluency in 6-well plates in antibiotic-free keratinocyte serum-free medium (KSFM) as described [37] and exposed to antibiotic-free KSFM control or monocultures of T. vaginalis (8 × 105 CFU/mL), L. crispatus (7 × 106 CFU/mL) and P. bivia (7 × 106 CFU/mL) at 35 °C in Mitsubishi AnaeroPack chambers (Fisher) mimicking the human vaginal microenvironment [37]. The T. vaginalis clinical isolate (UR1) was chosen for these experiments for its well-characterized pathogenicity, including lipophosphoglycan composition [38,39,40,41], immune properties [24,35,38,39,42,43,44,45,46], and carriage of endosymbiont Trichomonasvirus species [24,42,44,46], thereby representing a common clinical infection. L. crispatus (#223-2-10) and P. bivia (#1–17) were previously isolated from human vaginal swabs [47] and confirmed to have homeostatic or respectively, disruptive immune impact on the vaginal epithelium [37,42,48,49]. After 24 h incubation, cell culture supernatants were collected for EV isolation and cells were harvested for cell viability and colonization assessment. Reproducible bacterial colonization was ascertained by epithelial-cell attached colony-forming units as described [37]. Trichomonas viability and motility were confirmed by microscopic observation from total counts obtained from supernatant pellets, epithelial monolayer washings and after epithelial monolayer trypsinization [24]. Epithelial cell viability was confirmed by microscopic evaluation as well as by Trypan blue exclusion test using an automated cell counter and repeated measures of percent viability for each condition were compared by ordinary one-way ANOVA, and Tukey’s multiple comparison test (GraphPad Prism 9.4.1 for Windows, GraphPad Software, San Diego, CA, USA). EVs pellets were collected from biological quadruplicates of each of the 4 exposures (medium, T. vaginalis, L. crispatus and P. bivia) in 3 independent experiments resulting in 48 biological replicates individually tested in 3 miRNA assay runs. In a fourth independent experiment, each exposure was repeated in 12 individual epithelial cell cultures and a single pool of 12 was generated for each exposure/experimental condition. Each of these pools was split into 6 aliquots (two of each tested in each independent miRNA run) resulting in 24 technical replicates for assessing technical reproducibility of the miRNA expression profiling between runs. ## 2.2. Small Extracellular Vesicles Isolation and Characterization Cell culture supernatants were centrifuged at 1000× g for 5 min at 4 °C and filtered through a 0.22 µm membrane. Filtered supernatants were mixed in a 2:1 v/v ratio with the Total Exosome Isolation Reagent for cell culture medium (Invitrogen, Carlsbad, CA, USA) and incubated for 16 h at 4 °C followed by centrifugation using a fixed angle rotor at 10,000× g for 60 min at 4 °C. ZetaView (Particle Metrix, Meerbusch, Germany) was used to assess size and concentration of EVs and transmission electron microscopy (TEM) with immunogold labelling of CD63 was used to confirm the presence of exosomes in the EVs samples as previously described [35] (Supplementary Figure S1A). For miRNAs expression profiling, supernatants were removed, EV pellets were resuspended in 35 µL of HTG lysis buffer, and frozen at −80 °C until analyzed for the global human miRNA transcriptome. ## 2.3. Whole Human miRNA Transcriptome Profiling The miRNA content in the experimental EV preparations was profiled using the high-fidelity HTG EdgeSeq platform (HTG Molecular Diagnostics Inc, Tucson, AZ, USA) which couples an RNA extraction-free nuclease protection assay with next generation sequencing to quantify the whole human miRNA transcriptome (miRNome). The platform has been rigorously evaluated in multiple disease conditions and by comparison to other sequencing methods [50,51,52,53,54,55]. HTG EdgeSeq Whole Transcriptome (WT) miRNA assay used for this study contained 2102 probes, including 13 housekeeper genes, 5 negative controls genes from *Arabidopsis thaliana* aintegumenta (ATN), and 6 positive process control. Quality control (QC) was performed based on the background values of the ANT genes. ANT were averaged for each sample and a grand mean was calculated by taking the average of these averaged ANT values. The difference between each averaged ANT value and the grand mean, Δmean (ΔMean = averaged sample mean—grand mean) and standard deviation (SD) of the Δmean were calculated for each sample. The acceptable Δmean values are those within ±2XSD average ANT. The majority of samples (71 of 72) passed the QC test and were used to generate miRNA data. For WT miRNA assay, 25 µL of each lysate was run on an HTG EdgeSeq Processor in 3 individual plates (blocks) of 24 samples, using the HTG EdgeSeq miRNA WT assay. Samples were randomized within each plate to avoid any potential location bias. Each plate contained a technical duplicate of each pool for each of the four exposures and a randomized set of biological quadruplicates. Following the processor step, samples were individually barcoded using a 16-cycle PCR reaction to add adapters and molecular barcodes. Barcoded samples were individually purified using AMPure XP beads and quantitated using a KAPA Library Quantification kit to generate a library pool. The library was sequenced on an Illumina MiSeq using a V3 150-cycle kit with two index reads. PhiX was spiked into the library at $5\%$ as a standard procedure for Illumina sequencing libraries. Data were returned from the sequencer in the form of demultiplexed FASTQ files. The HTG EdgeSeq Parser was used to align the FASTQ files to the probe list to collate the data. ## 2.4. miRNA Transcriptome Bioinformatics and Statistical Analysis Bioinformatics and statistical analyses were performed using R (V3.3.0). Normalization was conducted in DESeq2 (version 1.14.1) using the regularized log approach. The differential expression analysis of the EdgeSeq miRNA data was completed using the DESeq2 package (version 1.8.1) available from Bioconductor [56]. The DESeq2 package provides methods for estimating and testing differential expression using negative binomial generalized linear models. Empirical Bayes methods were used to estimate dispersion and log2 fold change (FC) with data-driven prior distributions. The DESeq2 model corrected for library size using the median ratio method [57]. Dispersions were estimated with the Cox Reid-adjusted profile likelihood method [58], and Log2 FC was estimated via Tikhonov/ridge regularization with a zero-centered normal prior distribution with variance, calculated using the observed distribution of maximum likelihood coefficients. DESeq2 performs independent filtering on probes prior to testing and application of the false discovery rate p-value adjustment to increase power. Differential expression analyses were conducted using multiple regression accounting only for treatment, such that p-values were calculated comparing a full model (all treatment groups) to a reduced model containing only the intercept for each probe individually using a hierarchical likelihood ratio test (hLRT). To account for multiple tests, p-values from the hLRT were adjusted using the Benjamini & Yekutieli approach at an adjusted significance level of 0.05. Results were plotted as the log2 FC of the largest absolute value (x-axis) against the adjusted log10 p-value (y-axis) by probe. For the volcano pots, probes included were filtered by adjusted $p \leq 0.05$ and log FC > 2. Multidimensional scaling (MDS) was used to evaluate similarities and differences in the EV-miRNome of non-colonized (control) versus colonized vaginal cells and the batch effect. This assessment was performed using the R prcomp package, without centering or scaling using the regularized log normalization, to create principal components explaining variance. Expression heatmaps were calculated based on the regularized log normalized data. Pairwise correlations were calculated using the Kendall tau coefficient and correlation heat maps were generated to visualize the pair-wise comparisons of technical replicates to demonstrate reproducibility over all run blocks/batches. ## 2.5. miRNA-Target Genes Prediction and Gene Set Enrichment Analysis Differentially expressed (DE) miRNAs (adjusted p-value < 0.05) were selected to generate lists of shared and non-shared EV-miRNAs by Venn diagram analysis [59], miRNA-target genes prediction and pathway-enrichment analysis. Putative miRNA-target gene pairs were predicted using miRWalk database (release_2022_01) [60]. Data returned validated miRNA-target genes trough stringent prediction criteria using three combined algorithms (TargetScan, miRDB, and miRTarBase). The target gene list was uploaded into STRING (V11.5) [61] to construct protein-protein interaction (PPI) networks and pathway-enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) and TISSUES databases. To this end, we applied the data settings highest confidence interaction score > 0.9 and limited the number of interactions to the queried proteins; except for groups with a small number of predicted targets (17 predicted targets for EV-miRNAs down-regulated by both T. vaginalis and P. bivia, and 3 predicted targets for EV-miRNAs up-regulated by P. bivia) where we used number of interactions = no more than 5. PPI network clusters were built using Markov Clustering (MCL) algorithm (granularity = 4). Bubble charts were plotted by strength of the enrichment effect as the log10 observed/expected (O/E) ratio, where ‘observed’ is the number of queried proteins that are annotated in a given term and ‘expected’ accounts for the number of the proteins expected to be annotated in the same term considering a random network of the same size. The size of the bubbles represents the number of validated targets in each pathway, and color gradient reflects the level of the false-positive discovery rate (FDR) significance (−log10). The bubble charts and Venn diagram image were generated using the SRPlot platform. ## 2.6. Protein-Protein Interaction Network Analysis To obtain a system-level perspective of the biological networks underlining a common mechanism for both pathogens, we merged the PPI networks previously identified for EV-miRNAs DE by both P. bivia and T. vaginalis. To this end, PPI networks were merged using Cytoscape (v3.9.1), visualized with yFiles organic layout, and the top-3 clusters were identified by applying MCL algorithm, (granularity = 4). Topological betweenness centrality analysis of the merged network was conducted to screen for the top-10 hub proteins (CytoHubba v0.1) ranked using the maximal clique centrality (MCC) as a scoring method [62]. The betweenness centrality defines the hub proteins (nodes) as the genes which serve the highest number of times as the shortest paths connecting two nodes in the network. This analysis captures the importance of genes by identifying central proteins, which are highly connected and therefore represent bottlenecks in the flow of communication within the network. The centrality estimative strategy is helpful in the search for potential therapeutic targets [63]. ## 3.1. Non-Colonized and Colonized Human Vaginal Epithelial Cells Release Exosomes EVs isolated from the infection model showed positive staining for tetraspanin-30 (CD63) surface protein (Supplementary Figure S1A), with median size average of 147 nm (Supplementary Figure S1B) and range consistent with characteristics of endocytic origin, i.e., exosomes. The cell viability of biological replicates was high (mean 89.3 ± $1.1\%$ SEM), with no significant variation noted between experimental conditions ($$p \leq 0.6053$$) (Supplementary Figure S1C). TEM visualization and nanotracking showed no contamination with apoptotic bodies defined as particles with size 1–5 µm [64]. Colonization by T. vaginalis induced the highest number of EVs released in the infection model, when compared to baseline and the other experimental conditions (Figure S1B). ## 3.2. miRNAs-Containing Extracellular Vesicles from Colonized Human Vaginal Epithelial Cells Identified Pathogenic and Healthy Signatures MSD analysis of the EV-miRNAs transcriptome profiling of all biological and technical replicates revealed two main clusters, which grouped L. crispatus- colonized with non-colonized vaginal cells separately from the single T. vaginalis and P. bivia cluster. These two clusters explained $97\%$ of the variance as a single principal component (Figure 1A,B). This pattern identified similarities among pathogenic colonization and contrasted it with homeostatic bacteria consistent with our leading hypothesis. No obvious batch effect was observed (Figure 1A, runs/blocks 1–3), with pools and individual samples in all runs representing very similar patterns of expression (Figure 1B) and with cluster similarities assembled within the corresponding biological groups. A global heatmap expression profile of the EV-miRNAs resembled the MDS analysis, with 2 major clusters representing a “healthy” versus “non-healthy” (pathogen-triggered) expression profile (Figure 1C). The heatmap of pairwise-correlated (Kendall tau) replicates also demonstrated consistent clustering within the experimental groups with no significant run/block variations (Figure 1D). Volcano plots of pairwise comparisons illustrate differences between the homeostatic L. crispatus colonization and pathogenic colonization by T. vaginalis and P. bivia. No substantial differences were seen between L. crispatus-colonized and non-colonized vaginal cells (Figure 2A). L. crispatus downregulated only two EV-miRNAs (hsa-miR-3197 and hsa-miR-6845-5p, log2 FC > 2), both with poor annotation, and upregulated one miRNA (hsa-miR-1273e, log2 FC < 2), which has been removed from the most recent miRNA database (miRBase R22.1). In contrast, colonization by T. vaginalis and P. bivia triggered a striking perturbation in the EV-miRNA cargo compared to non-colonized vaginal epithelial cells (Figure 2B,C) and were distinguished from each other mostly by downregulated miRNAs (Figure 2D). Overall, we identified 938 DE EV-miRNAs induced by T. vaginalis and 735 DE P. bivia miRNAs with adjusted $p \leq 0.05$ (Supplementary Tables S1 and S2). ## 3.3. Vaginal Epithelial Cell Colonization by T. vaginalis and the BV-Pathobiont Identified EV-miRNA Targeted Genes and Pathways Associated with Cancer, Viral Infections, and Potential Reproductive Tract Tissue Recipients Venn diagram analysis of EV-miRNAs differentially expressed (adjusted p-value < 0.05) in response to T. vaginalis and/or P. bivia illustrates four intersecting (shared) and four unique (non-shared) miRNA categories (Figure 3A, Supplementary Table S2). Consistent with our hypothesis for a synergistic relationship between T. vaginalis and BV, most DE miRNAs in our model ($$n = 615$$) were shared between T. vaginalis and P. bivia acting in the same direction of dysregulation, with overlapping sets of 228 up-regulated and 387 down-regulated DE miRNAs. On its own, T. vaginalis induced the up- or down-regulation of 75 and 236 miRNAs, respectively, while P. bivia—23 and 85 miRNAs, respectively. Additionally, 12 discrepantly dysregulated miRNAs were modulated by both pathogens, but in opposite directions. Next, we identified validated miRNA target genes and pathways enriched for each of the eight individual (unique) or overlapping (shared) categories described in Figure 3A. miRWalk identified 17 validated target genes for the shared down-regulated miRNA set and 1174—for the shared up-regulated miRNA set (Supplementary Table S3). No validated targets were observed for the 12 discrepantly dysregulated miRNAs. *The* genes targeted by the shared and uniquely dysregulated miRNAs were used to find enriched pathways in KEGG and to construct PPI networks. Moreover, because EV enable cell-cell communication, we included the database TISSUES in our search strategy to determine potential EV recipients of interest. Shared down-modulated EV-miRNAs specified a total of 20 significant KEGG pathways (false discovery rate, FDR < 0.05). Five of those have been associated with infectious disease (malaria, Chagas disease, leishmaniasis, hepatitis B and HTLV-1) and five with cancer, corresponding to $50\%$ of the total pathways (Figure 3B). Overall, TGFBR2 accounted for most enriched pathways in KEGG. Additionally, TISSUES identified suprachiasmatic nucleus as potential tissue-target, pinpointing genes, specially CRY2, associated with circadian regulation, a top-1 pathway (FDR < 0.0022) also identified by KEGG (Figure 3B). *Target* genes for shared up-regulated miRNAs revealed 106 KEGG pathways (Supplementary Table S4, Figure 3C) and 39 terms in TISSUES (Figure 3C) (FDR < 0.005). Approximately, $30\%$ of these shared KEGG enriched pathways are related to both cancer and viral infection. TISSUES underlined 13 ($33\%$) terms associated with the female reproductive tract plus pregnancy, and 4 terms ($10\%$) related with the central nervous system. Non-shared EV-miRNAs dysregulated by P. bivia identified 3 downregulated and 83 upregulated target proteins (Supplementary Figure S2A,B and Table S3). The targets for up-regulated miRNAs were enriched in 16 KEGG pathways, highlighting 6 ($37.5\%$) pathways in cancer (Supplementary Figure S2A). Targets for down-regulated miRNAs were not informative (Supplementary Figure S2B). Additionally, T. vaginalis unique up-/down-regulated EV-miRNAs identified 148 and 94 targets, respectively (Supplementary Figure S2C,D and Table S3). Targets from the up-regulated miRNAs identified 40 KEGG pathways (FDR < 0.05), including 16 ($40\%$) terms in cancer and 9 ($22.5\%$) terms in viral infection. Furthermore, the 25 terms in TISSUES specified were linked to cancer (8/$32\%$), the female genital tract and fetus (8/$32\%$), and the central nervous system (2/$8\%$) (Supplemental Figure S2C). miRNAs downregulated by T. vaginalis were less informative yet underlined the female reproductive system (TISSUES, FDR = 0.00039) (Figure S2D). Altogether, terms and pathways individually found for each pathogen largely reiterate the pattern reported for the shared up/down-regulated networks, implicating cancer, the female reproductive tract, and infectious diseases. ## 3.4. miRNA Dysregulation by Parasitic and BV-Associated Organisms Targets Steroid Hormone Receptor Signaling and Pathways Associated with Cancer, Viral Infections, and Potential Reproductive Tract Tissue Recipients To explore the synergism of the networks determined by the EV-miRNAs DE by both T. vaginalis and P. bivia, we merged the two validated-targets constructed PPI networks obtained from up- and down-regulated EV-miRNAs and screened for top 10 hub genes. The merged network comprehended 1184 nodes and 1710 edges ($$p \leq 1.0$$−16), of which the top-3 clusters contained a total of 72 proteins, 46 of them associated with terms on female genital tract (Figure 4A, Supplementary Table S5). The 10 hub genes identified from the global merged network are protein targets determined by the shared up-regulated miRNAs set, and we found them to be associated with signal transduction (MPK1, MPK14, PIK3R1, SMAD4, YWHAZ), gene transcription (STAT3), cell division (CDC42), ubiquitination (UBE2I), and steroid hormone receptors/transcription factors (ESR1, NR3C1) (Figure 4B, Table 1). The PPI between the hub genes is depicted according to the centrality score (Figure 4B), and respective miRNA-targeted hub genes (Figure 4C, Table 1). We found 21 EV-miRNAs modulating the hub genes, varying by the number of miRNAs per mRNA-target (Table 1) and the number of 3′UTR target sites in any of the transcripts, including splicing variants (Figure 4C and Table 1). The top 10 hub genes were ranked in importance for the merged network by centrality score (representing essential proteins in the network, which can be therapeutic targets) each showing a high degree of PPI interaction (number of links to given node ranging from 53 to 24) (Table 1) and each occurring in multiple terms related with the urogenital and female reproductive tract in TISSUES (Supplementary Table S6). The hub gene, which was targeted by the highest number of T. vaginalis- and BV pathobiont-upregulated EV-miRNAs and ranked third in importance for the merged network, was the estrogen receptor 1 (ESR1, Table 1), which is central for the reproductive female physiology [65]. The top ranking also identified the potential downregulation of other genes involved in the ESR1 pathway (Supplemental Figure S3), including signal transduction MAPK1/ERK2 and the enzyme PIK3R1 (and Table 1). In addition, among the shared upregulated EV-miRNAs was hsa-miR-18a-5p, which targets both ESR1 and isoforms of the glucocorticoid receptor (GR) gene NR3C1 (GRα and GRγ), acting to decrease their levels. NR3C1 was ranked seventh by centrality score in the pathogen-dysregulated PPI network (Table 1). ## 4. Discussion The experimental data presented here support our hypothesis conceptualized in Figure 5. To our knowledge, this study is the first to investigate the effect of T. vaginalis infection on host miRNAs released in EVs in the context of vaginal infections as potential pathogenic determinant. T. vaginalis is an extracellular protozoan parasite that adheres to the vaginal and cervical epithelial cells and subverts host immune defenses by signaling through its surface lipophosphoglycan and release of endosymbiont virus (TVV) and exosomes [32,33] loaded with specific protein cargo, which can be modified by TVV [35]. For our first proof of concept study, we chose a strain that harbors TVV to represent most primary T. vaginalis clinical isolates worldwide [66]. Our study is also the first to investigate EV-miRNAs differential expression in response to axenic P. bivia vaginal colonization and to contrast that to L. crispatus colonization. P. bivia is an abundant pathobiont of the vaginal microbiome community state CST-IV, subtype A [67], which presents BV-related characteristics, and a close to 2-fold increased risk of acquiring T. vaginalis infection [18]. Both pathogens, T. vaginalis and P. bivia, uphold clinical relevance associated with poor perinatal outcomes, urogenital cancer, and increased susceptibility to viral STIs [6]. We found that all miRNAs dysregulated by T. vaginalis and or P. bivia, remained at baseline equilibrium after colonization by L. crispatus. In fact, the lactobacillus challenge was associated with DE of only two miRNAs with poor annotation and no assigned function by the latest mRNA databases. These findings provide further molecular proof for the previously proposed beneficial role of L. crispatus in vaginal health [6,10]. While EVs produced by vaginal Lactobacillus isolates have been reported to have a protective effect against HIV-1 transmission, in part, by inhibiting viral attachment/entry due to diminished exposure of viral envelope [68], the individual components of the EV cargo responsible for the causation of the reported protective effects are still to be determined. Our experimental study provides a causative proof for clinical findings of disturbed vaginal miRNome. In our model, host EV-miRNAs expression profile of 2078 miRNA probes strikingly distinguished homeostatic from pathobiont human vaginal epithelial cells colonization, both PCA and heat-map analyses clustering together on one side T. vaginalis and P. bivia and on the other side—L. crispatus and baseline vaginal cells. A Swedish study of 56 reproductive age women surveying only 798 miRNAs identified 10 miRNAs overexpressed in non-Lactobacillus dominated microbiome communities with specificity over $95\%$ in receiver operating characteristics (ROC) analysis [69]. All of those miRNAs proposed to have a high diagnostic potential (except miR-4532 which was later determined to not be a true miRNA) including miR-23a-3p, miR-130a-3p, miR-22-3p, miR-1290, miR-15a-5p, miR-1537-3p, miR-222-3p, miR-27a-3p, and miR-148a-3p, were upregulated by the pathogens in our model (7 upregulated by both T. vaginalis and P. bivia, one by T. vaginalis alone and one by P. bivia alone, Supplementary Table S2). The top 2 dysbiotic vaginal miRNAs with a predictive value validated in another cohort of 32 women (miR-23a-3p and miR-130a-3p), were present in our dataset among the dysregulated miRNAs targeting four different 3′UTR sites of the ESR1, which was identified as one of the top 10 hub genes in the PPI network analysis discussed below. These clinical findings support our conceptual framework and the relevance of our experimental model linking vaginal microbes to miRNA dysregulation. Our in silico analysis of miRNA-predicted pathways and PPIs applied a stringent and conservative approach focusing on the 3′UTR targeting sites validated and confirmed by three algorithms. The miRNA pairing with 3′UTR sites follows the canonical pathway of miRNA regulation where overexpressed miRNAs downregulate their targets and down-expressed miRNAs allow their targets expression, without assumptions about ‘on/off’ switch, tuning, or neutral effects on protein levels [70]. It is noteworthy that T. vaginalis and P. bivia caused a massive, shared repression of 387 EV-miRNAs; however, miRWalk in silico analysis of miRNA targets was more informative for the set of 236 up-regulated EV-miRNAs, suggesting unknown roles for most EV-miRNAs identified as downregulated. EV-miRNAs targets identified by miRWalk were used to build up PPI networks and to find, by GSEA, a germane group-based gene set with a higher likelihood of identifying either attractive therapeutic targets or biological processes relevant to our hypothesis. In addition, to obtain a global perspective of EV-miRNAs targets, we merged PPI networks from shared up- and down-regulated EV-miRNAs and identified top-3 clusters of the PPI, which showed 46 out of 72 proteins (~$63.8\%$) related with FGT terms in TISSUES. Furthermore, utilizing profiles of EV-miRNAs modulated by both pathogens, GSEA showed distinctive proteins and pathways mainly associated with cancer. Our findings were consistent with the so far sparse evidence of clinical relevance of miRNAs to FGT cancer. A clinical study of cervical cancer reported hsa-miR-21 and hsa-miR-146a to be overrepresented in exosomes from cervicovaginal lavages [71], and miR-92a-5p and miR-155-5p were pointed out as biomarkers for early detection of cervical cancer using pap smear samples—considering the nature of the samples, this data may reflect the collective of miRNAs from cells plus exosomes [72]. In our data, hsa-miR-21-5p and hsa-miR-92a-3p (the hsa-miR-92a-5p passenger strand) were up-regulated by both T. vaginalis and P. bivia and hsa-miR-146a-5p was up regulated by P. bivia. While in silico analysis fails to correlate hsa-miR-21-5p with proteins assigned to cancer pathways, it links hsa-miR-146a-5p to cancer by targeting ERBB4, a protein enriched in two KEGG terms associated with cancer (‘ErbB signaling pathway’ and ‘proteoglycans in cancer’). Viral infection-associated cancer pathways were predicted by shared up-regulated networks as well as EV-miRNAs up-regulated by T. vaginalis only. Thus, our experimental findings and predictions agree with clinically identified miRNAs and observational studies associating BV and trichomoniasis with viral cancer [14,15,20,73,74]. A merged PPI network was used to find the top-10 hub genes and their respective targeting EV-miRNAs because network nodes with higher betweenness centralities (hubs), connecting different distinct functional modules, are more likely to be essential than high-degree nodes [75] and have a higher potential to be therapeutic targets [63]. By employing this approach, we found 10 hub genes involved with cell signaling (MPK1, MPK14, PIK3R1, SMAD4, YWHAZ), cell division (CDC42), and ubiquitination (UBE2I), along with gene transcriptional factors (STAT3, ESR1, and NR3C1) where two of them are also hormone steroid receptors, ESR1(ERα) and NR3C1 (GR). The steroid receptors might be of special relevance to our hypothesis due to proposed roles of estrogens in collaborating with lactobacilli-dominated microbiome [76], and ESR1 and NR3C1 as genetic factors of PTB [77], and GR epigenetic modification linked to poor perinatal clinical outcomes [78,79]. Among the hub genes, ESR1 is the transcript (variants 1–4 and 7) targeted by the highest number of miRNAs and presents the highest number of targeted 3′UTR sites. The redundancy in targeting ESR1 may reflect the importance for both pathogens in controlling this receptor in EVs recipient cells and, thus, manipulating the conspicuous role of estrogens in the FGT, a conjecture that warrants further investigation. ESR1 is mainly expressed in uterus, ovaries, breast, kidney, liver, white adipose tissue, and bones. It is highly homologous to ESR2 (ERβ) which, in turn, is found in male and female reproductive organs, central nervous system (CNS), cardiovascular system, lung, immune system, colon, and kidney [80]. In addition, ESR1 plays an important role in many immune cells and cancer [81], a connection that needs further elucidation in the context of T. vaginalis and BV-associated cancer in reproductive systems. Estrogens have known anti-inflammatory properties [82]. Therefore, the decreased levels of ESR1 due to 3′UTR pairing with miRNAs differentially upregulated by T. vaginalis and BV bacteria may contribute to exacerbating inflammation-driven comorbidities, cancer, adverse pregnancy outcomes. It may also shift balance to proinflammatory activation in other low-estrogen conditions such as menopause. Additional attention deserves NR3C1, which has been linked to spontaneous preterm birth [77] and was identified in our dataset as a hub gene with the isoforms GRα and GRγ targeted by hsa-miR-18a-5p, an EV-miRNA upregulated by both T. vaginalis and P. bivia. Glucocorticoid receptors comprehend a large cohort of protein isoforms that arise from alternative splicing of one single gene (NR3C1) and alternative translational initiation mechanisms. GR may act to repress or induce gene expression depending on the receptor isoform, cell type and promoter context, which will ultimately dictate distinct responses to glucocorticoids [83]. Both isoforms are largely expressed and functional; however, they regulate a specific set of glucocorticoid-responsive genes [84], suggesting their downregulation may result in different outcomes based on the isoform itself and EV-recipient cells. NR3C1 methylation status has been pointed to as a factor for adverse experiences in perinatal period, where hypermethylation of certain CpG sites correlates with perinatal stress occurrence [79,85]. NR3C1 methylation leads to attenuation of GR expression, impairing the negative feedback loop of the hypothalamic-pituitary-adrenal (HPA) axis, resulting in an increase in glucocorticoid levels—such as cortisol—which in turn may affect the fetus’ brain development [86]. Interestingly, NR3C1 seems to be convergent to insulin growth factor 2 (IGF2) in the context of cell responses to stress [86]. IGF2 signals through insulin-like growth factor 1 receptor (IGFR1), activating PI3K/MAPK intracellular signaling. IGF and its receptors are involved in fetus and proper placenta development [87]. Here we found IGFR1 and PI3K as part of cluster 2 and MAPK proteins as part of cluster 1, hence, we hypothesize that downregulation of NR3C1 and IGFR1 axis, and respective signaling molecules, may help to explain long-lasting adverse prenatal events associated with P. bivia and T. vaginalis infection, pointing to a possible post-transcriptional regulation by EV-miRNAs in addition to CpG methylation. EVs act in recipient cells, possibly targeting bystander cells or traveling to reach long-distance cells; thus, it is plausible that EV-miRNAs dysregulated by vaginal pathogens could target surrounding tissues, such as the cervix, and distant ones such as the uterus, placenta, and fetus. In our dataset we found enrichment of validated targets in tissues related to the FRT, pregnancy (embryo, fetus, placenta, and embryonic structures), and brain (‘CNS’, ‘brain’ and ‘nervous system’), which support our hypothesis and assign candidate proteins to enlighten possible pregnancy poor outcomes linked with BV. It is worth mentioning that progesterone, a low affinity agonist to GR, maintains pregnancy and favors maternal immune tolerance to fetus via GR dependent mechanism [88], raising the question of how GR downregulation may impact some of the progesterone activity during pregnancy. The relevance of the remaining hub genes identified by our analysis of dysbiosis and T. vaginalis dysregulated miRNAs (SMAD4, UBE2I, STAT3, CDC41 and YWHAZ) remains to be investigated in the clinical context of T. vaginalis, BV and associated cancer and pregnancy complications. Of note, among the top 10 hub genes, STAT3 was the transcript with the highest number of predicted 3′UTR target sites, being a target of hsa-miR-125a-5p. STAT3 is transcriptionally hyperactive in numerous tumor cells and serves as an immune checkpoint in immune-associated tumor cells [89,90]. Serum exosomal studies from cervical cancer and healthy women pinpointed this miRNA as a potential biomarker with diagnostic value [91]. Circadian rhythm was the top-1 KEGG term respective to shared down-regulated EV-miRNAs network. Interestingly, ESR1 and ESR2 have been found to regulate circadian rhythm in mice [92]. Although our in silico analysis did not implicate ESR1 in circadian pathway, we found other clock genes targeted by miRNAs dysregulated by T. vaginalis and P. bivia including PER2, CLOCK, and CRY2. The literature is limited on ESR and circadian rhythm; so far it seems there is a link between ESR1-induced CLOCK expression in breast cancer cells [93]. Furthermore, the same network identified KEGG terms related with protozoan infection, such as malaria, Chagas disease and leishmaniosis, pointing to a convergent set of genes (TGFB1, TGFB3, and TGFBR2) related with those infections and BV. It has been appreciated that sex-associated hormones have a role in the susceptibility to some protozoan infections [94]. Yet, ESR1 and NR3C1 were not associated with terms in the protozoan dataset; instead, we found TGFB1 and TGFB3—expected to be up-regulated—associated with the three protozoans mentioned above, and TGFBR2 only linked with Chagas diseases. TGFBR2 is a predicted target for both up- and down-regulated set of EV-miRNAs, requiring more investigations regarding gene expression regulation. ## 5. Conclusions Our data support the main hypothesis and emerging concept that parasitic eukaryotes and bacterial pathogens disturbing the human vaginal microbiome may impact reproductive health by modifying the EV-miRNAs cargo. Our data provide a causative proof for a homeostatic role of L. crispatus and in contrast—a host transcriptome disruptive role of the common vaginal parasite T. vaginalis and the BV-signature pathobiont P. bivia. In silico analysis of the experimental EV-miRNA transcriptome patterns predicted perturbing effects of pathogenic colonization in networks and pathways closely related with steroid hormone receptors functioning in the female reproductive physiology. While emerging clinical science supports the role of vaginal bacteria in altering the miRNA cargo released in the cervicovaginal secretions [69] and suggests that miRNAs dysregulation, which we experimentally linked to P. bivia and T. vaginalis, may contribute to risks of gynecologic cancers associated with these pathogens, more research is needed to validate their miRNA-mediated impact on protein networks within cancer cells and tissues. 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--- title: Is the combination of linagliptin and allopurinol better prophylaxis against post-contrast acute kidney injury? A multicenter prospective randomized controlled study authors: - Ahmed Fayed - Ahmed A. Hammad - Dina O. Abdulazim - Hany Hammad - Mohamed Amin - Samir Elhadidy - Mona M. Salem - Ibrahim M. Abd ElAzim - Lajos Zsom - Eva Csongradi - Karim M. Soliman - Usama A. Sharaf El Din journal: Renal Failure year: 2023 pmcid: PMC10054158 doi: 10.1080/0886022X.2023.2194434 license: CC BY 4.0 --- # Is the combination of linagliptin and allopurinol better prophylaxis against post-contrast acute kidney injury? A multicenter prospective randomized controlled study ## Abstract ### Background Patients with diabetic kidney disease (DKD) are at increased risk to develop post-contrast acute kidney injury (AKI). Diabetic patients under dipeptidyl peptidase 4 inhibitors (DPP4Is) experience a lower propensity to develop AKI. We speculated that linagliptin as a single agent or in combination with allopurinol may reduce the incidence of post-contrast AKI in stage 3–5 chronic kidney disease (CKD) patients with underlying DKD. ### Methods Out of 951 DKD patients eligible for this study, 800 accepted to sign informed consent. They were randomly allocated to 4 equal groups that received their prophylaxis for 2 days before and after radiocontrast. The first control group received N-acetyl cysteine and saline, the 2nd received allopurinol, the 3rd group received linagliptin, and the 4th received both allopurinol and linagliptin. Post-procedure follow-up for kidney functions was conducted for 2 weeks in all patients. ### Results 20, 19, 14, and 8 patients developed post-contrast AKI in groups 1 through 4, respectively. Neither linagliptin nor allopurinol was superior to N-acetyl cysteine and saline alone. However, the combination of the two agents provided statistically significant renal protection: post-contrast AKI in group 4 was significantly lower than in groups 1 and 2 ($p \leq 0.02$ and <0.03, respectively). None of the post-contrast AKI cases required dialysis. ### Conclusion Linagliptin and allopurinol in combination may offer protection against post-contrast AKI in DKD exposed to radiocontrast. Further studies are needed to support this view. ### Trial registration ClinicalTrials.gov NCT03470454 ## Introduction AKI is a common complication of radiocontrast exposure, especially in patients carrying underlying risk factors [1]. Among the non-modifiable risk factors, diabetes mellitus and CKD carry the highest risk [2]. The role of enhanced hypoxia and subsequent excess formation of reactive oxygen species (ROS) in the renal tissue following the administration of iodinated contrast media was demonstrated in many in vitro and in vivo studies [3]. A previous meta-analysis indicated that allopurinol might be an effective intervention compared with hydration and N-acetyl cysteine to prevent post-contrast AKI [4]. The preventive effect of allopurinol may be more remarkable in high-risk patients [5]. DPP4Is were not tried as preventive agents against post-contrast AKI. DPP4Is were found associated with a decreased risk of AKI among diabetic patients [6]. DPP4Is down-regulate the expression of the proinflammatory cytokines such as TNFα, IL-1β, IL-6, and chemokines such as MCP-1, hence; could be a potential mode of prevention of contrast-induced nephropathy [7]. In this randomized prospective study, we looked for the possible effect of linagliptin as a single agent or in combination with allopurinol to prevent post-contrast AKI in diabetic nephropathy patients. ## Methods This trial was conducted between April 2018 and May 2020 in the Critical Care and Internal Medicine Departments of Cairo University, Fayoum University, and Theodor Bilharz Research Institute. The study protocol was revised and approved by the Ethics Committee of the Internal Medicine and Critical Care Departments at Cairo University, while the board review was approved by the Faculty of Medicine, Fayoum University research committee. Written consent was obtained from each patient or the patient’s next of kin. All procedures carried out in this study involving human subjects adopted the ethical principles of the Institutional Research Committee as well as the Helsinki Declaration of 1964 and its corresponding modifications or equivalent ethical standards. The trial registration number at ClinicalTrials.gov was NCT03470454. We excluded patients who met any of the following criteria: those on other DPP4 inhibitors, glucagon-like peptide receptor agonists, sodium-glucose transporter-2 inhibitors; already on long-time linagliptin, febuxostat, or allopurinol therapy; those with a low HbA1c (<$7\%$) due to concerns about possible hypoglycemic events and patients with heart failure. The eligible patients were at least 30 years of age. All patients were maintained on statin treatment as part of their standard of care treatment. Metformin, renin-angiotensin-aldosterone antagonists, and diuretics were stopped once the patients were recruited to the study and reinstituted after the final analysis. 800 patients were randomized according to the type of radiologic intervention into four groups using Adaptive Randomization (outcome-adaptive randomization program for clinical trials from the M.D. Anderson Cancer Center, University of Texas). All the patients received the planned intervention 48 h before and 48 h after the radiocontrast administration. Baseline serum creatinine was obtained 72 h before the planned intervention and before the administration of any protective protocol. Follow-up serum creatinine was obtained 72 h after contrast administration. Group 1 was given 200 mg of N-acetyl cysteine orally every eight hours, as well as 100 mL/h of 0.9 g/dL saline solution 6 to 12 h before and after the contrast imaging technique, or 1 to 1.5 mL/kg/h of saline solution for 12 h before and up to 24 h after the procedure. Subjects in group 2 received 300 mg of allopurinol daily [5], group 3 received linagliptin 5 mg daily [7] and group 4 received linagliptin 5 mg and allopurinol 300 mg daily (Figure 1). **Figure 1.:** *Study flow chart.* The baseline demographic, clinical characteristics, and initial laboratory investigations that were collected are presented in Table 1. **Table 1.** | Variables | Variables.1 | Group 1 (n = 200) | Group 2 (n = 200) | Group 3 (n = 200) | Group 4 (n = 200) | p Value | | --- | --- | --- | --- | --- | --- | --- | | Age (Years) (Mean ± SD) | Age (Years) (Mean ± SD) | 48.9 ± 7.3 | 49 ± 7.6 | 48.04 ± 6.5 | 48.98 ± 6.9 | 0.47 | | BMI (Kg/m2) (Mean ± SD) | BMI (Kg/m2) (Mean ± SD) | 25.3 ± 1.9 | 24.6 ± 2.7 | 26.4 ± 1.9 | 25.5 ± 1.7 | <0.00001a | | Smokers (Number (%)) | Smokers (Number (%)) | 101 (50.5) | 99 (49.5) | 121 (60.5) | 97 (48.5) | <0.00001a | | Hypertension (Number (%)) | Hypertension (Number (%)) | 118 (59) | 125 (62.5) | 137 (68.5) | 126 (63) | 0.014a | | Duration of Diabetes mellitus (Years) (Mean ± SD) | Duration of Diabetes mellitus (Years) (Mean ± SD) | 7.09 ± 3.5 | 7.15 ± 2.2 | 6.4 ± 1.5 | 6.9 ± 1.9 | 0.0188a | | Laboratory data before contrast | Laboratory data before contrast | Laboratory data before contrast | Laboratory data before contrast | Laboratory data before contrast | Laboratory data before contrast | Laboratory data before contrast | | S. Urea (mg/dL) (Mean ± SD) | S. Urea (mg/dL) (Mean ± SD) | 66.1 ± 21.8 | 76.9 ± 21.04 | 70.3 ± 22.4 | 74.6 ± 22.7 | 0.002a | | Creatinine (mg/dL) (Mean ± SD) | Creatinine (mg/dL) (Mean ± SD) | 2.4 ± 0.4 | 2.4 ± 0.4 | 2.4 ± 0.4 | 2.6 ± 0.5 | 0.001a | | Estimated GFR (mL/min/1.73 m²) (Mean ± SD) | Estimated GFR (mL/min/1.73 m²) (Mean ± SD) | 28.3 ± 6.7 | 28.5 ± 7.9 | 27.7 ± 7.4 | 24.8 ± 6.6 | 0.001a | | Stage of CKD | Stage 3 CKD (Number (%)) | 69 (34.5) | 71 (35.5) | 68 (34) | 40 (20) | 0.0005a | | Stage of CKD | Stage 4 CKD (Number (%)) | 131 (65.5) | 127 (63.5) | 132 (66) | 156 (78) | 0.0005a | | Stage of CKD | Stage 5 CKD (Number (%)) | 0 (0) | 2 (1) | 0 (0) | 4 (2) | 0.0005a | | Urine ACR (mg/g) (Mean ± SD) | Urine ACR (mg/g) (Mean ± SD) | 113.6 ± 29.4 | 116.2 ± 30.1 | 113.3 ± 32.9 | 116.5 ± 33.7 | 0.714 | | Uric acid (mg/dl) (Mean ± SD) | Uric acid (mg/dl) (Mean ± SD) | 6.4 ± 1.2 | 7.7 ± 0.6 | 5.5 ± 1.4 | 7.7 ± 0.7 | 0.0001a | | HbA1c (Mean ± SD) | HbA1c (Mean ± SD) | 6.5 ± 0.4 | 6.5 ± 0.4 | 6.4 ± 0.4 | 6.4 ± 0.4 | 0.064 | | Patients with HbA1c ≤6.5% (Number (%)) | Patients with HbA1c ≤6.5% (Number (%)) | 129 (64.5) | 101 (50.5) | 118 (59) | 113 (56.5) | 0.064 | The primary endpoint was the development of post-contrast AKI, defined as a decrease of GFR by or greater than $30\%$ relative to baseline or an increase in serum creatinine that is greater than 0.3 mg/dl relative to baseline or $30\%$ over baseline 72 h after the administration of the contrast. A secondary endpoint was the maximum absolute change in serum creatinine and GFR during the study period. GFR was estimated using the MDRD 4-variable GFR Equation (GFR in mL/min per 1.73 m2 = 175 x SerumCr−1.154 x age−0.203 x 1.212 (if the patient is black) x 0.742 (if female)). Table 2 summarizes the different radiologic procedures performed as well as the types and amounts of radiocontrast agents used. Change in any of the studied parameters was calculated as a change in percentage [{(post-level-basal level)/basal level} X 100]. **Table 2.** | Variables | Group 1 (n = 200) | Group 2 (n = 200) | Group 3 (n = 200) | Group 4 (n = 200) | p Value | | --- | --- | --- | --- | --- | --- | | Type of imaging with contrast | Type of imaging with contrast | Type of imaging with contrast | Type of imaging with contrast | Type of imaging with contrast | Type of imaging with contrast | | Therapeutic Coronary Angiography (Number (%)) | 74 (37) | 72 (36) | 71 (35.5) | 72 (36) | 0.82887 | | Diagnostic Coronary Angiography (Number (%)) | 43 (21.5) | 37 (18.5) | 59 (29.5) | 56 (28) | 0.82887 | | CT Coronary Angiography (Number (%)) | 21 (10.5) | 25 (12.5) | 26 (13) | 21 (10.5) | 0.82887 | | High Resolution CT Chest (Number (%)) | 44 (22) | 40 (20) | 34 (17) | 36 (18) | 0.82887 | | CT Abdomen (Number (%)) | 18 (9) | 26 (15) | 10 (5) | 15 (7.5) | 0.82887 | | Type of the nonionic contrast used | Type of the nonionic contrast used | Type of the nonionic contrast used | Type of the nonionic contrast used | Type of the nonionic contrast used | Type of the nonionic contrast used | | Iohexol (Omnipaque) (Number (%)) | 105 (52.5) | 91 (45.5) | 95 (47.5) | 97 (48.5) | 0.99987 | | Iopromide (Ultravist) (Number (%)) | 95 (47.5) | 109 (54.5) | 105 (52.5) | 103 (51.5) | 0.99987 | | Volume of contrast | Volume of contrast | Volume of contrast | Volume of contrast | Volume of contrast | Volume of contrast | | Volume (mL) (Mean ± SD) | 114.5 ± 30.2 | 115.1 ± 29 | 112.6 ± 31.2 | 111.4 ± 30.9 | 0.58773 | | 75mL (Number (%)) | 42 (21) | 33 (16.5) | 53 (26.5) | 55 (27.5) | 0.58773 | | 100mL (Number (%)) | 79 (39.5) | 90 (45) | 70 (35) | 72 (36) | 0.58773 | | 150mL (Number (%)) | 79 (39.5) | 77 (38.5) | 77 (38.5) | 73 (36.5) | 0.58773 | | Laboratory data 72 h after contrast injection using the Kruskal-Wallis test | Laboratory data 72 h after contrast injection using the Kruskal-Wallis test | Laboratory data 72 h after contrast injection using the Kruskal-Wallis test | Laboratory data 72 h after contrast injection using the Kruskal-Wallis test | Laboratory data 72 h after contrast injection using the Kruskal-Wallis test | Laboratory data 72 h after contrast injection using the Kruskal-Wallis test | | Post-contrast AKI (Number (%)) | 20 (10) | 19 (9.5) | 14 (7) | 8 (4) | 0.092 | | Percent change in urea (Mean ± SD) | −11.5 ± 10.6 | −6.1 ± 4.6 | −16.9 ± 10.2 | −21.4 ± 11.3 | <0.0001a | | Percent change in creatinine (Mean ± SD) | −1.9 ± 10.3 | −0.15 ± 9.7 | −2.01 ± 10.7 | −6.3 ± 6.8 | 0.0033a | | Percent change in GFR (Mean ± SD) | 3.6 ± 12 | 1.3 ± 11.3 | 3.8 ± 11.8 | 7.5 ± 11.01 | <0.0001a | | Percent change in uric acid (Mean ± SD) | −8.03 ± 8.8 | −18.4 ± 4.4 | −5.3 ± 7.2 | −22.5 ± 6.2 | <0.0001a | | Percent change in Urine ACR (Mean ± SD) | −4.4 ± 3.4 | −6.7 ± 5.6 | −19.2 ± 16.2 | −24.4 ± 14.4 | <0.0001a | | Post contrast AKI (Chi square,confidence interval 95%) | Post contrast AKI (Chi square,confidence interval 95%) | Post contrast AKI (Chi square,confidence interval 95%) | Post contrast AKI (Chi square,confidence interval 95%) | Post contrast AKI (Chi square,confidence interval 95%) | Post contrast AKI (Chi square,confidence interval 95%) | ## Statistical analysis The data collected were verified, coded, entered, and analyzed with IBM Statistical Package for Social Science (SPSS) Statistics 22 software. The mean and standard deviation of continuous variables were calculated. For qualitative variables, frequency and percentage were used. The Mann-Whitney test was used to compare groups. A comparison between more than 2 independent groups was evaluated using the Kruskal-Wallis test (Table 2). For qualitative data, bivariate associations were examined using the chi-square test. P-values < 0.05 were considered statistically significant. ## Results Patients selected for this study carry a very high risk to develop AKI upon exposure to radiocontrast. According to the risk score proposed by Mehran et al. [ 8] and updated by Barrett and Parfrey, [9] the total risk score to develop post-contrast AKI in the studied patients ranged between 6 and 12. Demographic and baseline laboratory data of the studied patients were summarized in Table 1. The significant discrepancy in body mass index and kidney function at entry was not intentional. Consequently, we relied on the differences in the individual laboratory parameters before versus after radiocontrast administration (Table 2). Twenty cases ($10\%$) in group 1, nineteen ($9.5\%$) in group 2, fourteen ($7\%$) in group 3, and eight ($4\%$) in group 4 matched the definition of post-contrast AKI. There is no significant difference in the incidence of post-contrast AKI between group 3 versus group 1, group 2, or group 4 (Table 2). Following the administration of renoprotective medications, the distinct groups showed a slight improvement in kidney function tests. The improvement in serum urea was the most evident in all groups and was most pronounced in group 4. Here, the percentage of decline in blood urea nitrogen was significantly greater than in the other three groups. The improvement in serum creatinine was the least in group 2, while the improvement in the glomerular filtration rate was maximal in group 3. On the other hand, a maximal antiproteinuric effect was observed in group 4 (Table 2). The significant hypouricemic effect is likely related to the use of allopurinol in groups 2 and 4. ## Discussion In addition to diabetes, preexisting CKD is the strongest risk factor for the development of post-contrast AKI [10–12]. Although periprocedural intravenous crystalloid infusion is still the primary intervention recommended by the American College of Radiology and the European Society of Cardiology to mitigate the risk of post-contrast AKI, this approach carries considerable risk to patients with underlying heart disease or systemic hypertension [13]. N-acetyl cysteine is usually used together with isotonic saline in post-contrast AKI prevention protocols due to its known antioxidant effect, low cost, ease to use, and appreciable safety. When N-acetyl cysteine was used without hydration therapy, it did not reduce the risk of post-contrast AKI [14], while its addition to saline led to conflicting results [15,16]. When allopurinol was used instead of acetylcysteine in several trials, it potentiated the renoprotective effect of hydration therapy [5,17,18]. This effect is probably consequent to the mitigation of the stimulatory effect of intracellular uric acid on nicotinamide adenine dinucleotide phosphate (NADPH) oxidase. The activation of NADPH oxidase causes increased intracellular oxidative stress, mitochondria injury, ATP depletion, and the activation of nuclear factor kappa-B (NF-κB) [19,20]. We did not encounter studies of allopurinol without hydration therapy. Although the use of DPP4Is is associated with a decreased incidence of AKI among diabetic patients [6], the literature lacks studies on the possible renoprotection these agents can offer to patients exposed to radiocontrast. The present study aimed to look for the preventive effect of DPP4I linagliptin in comparison to standard periprocedural hydration plus N-acetyl cysteine, allopurinol, or the combined use of linagliptin and allopurinol. DKD with overt proteinuria is often accompanied by avid sodium retention [21]. Hence, it seems unlikely that DKD patients need fluid infusion to prevent post-contrast AKI. Based on this assumption, we did not add fluid therapy to linagliptin or allopurinol. The results of the current study confirm that neither linagliptin nor allopurinol is inferior to intravenous fluid therapy. Moreover, the combination of linagliptin and allopurinol was superior to both fluid therapy and the separate use of these two agents. Accordingly, this is the first study to demonstrate the applied prophylactic therapy implying synergism between these two agents. In animal studies, DPP4Is significantly reduce the markers of tubular necrosis and proinflammation markers in uninephrectomized rats exposed to ischemia-reperfusion injury [22,23]. These anti-inflammatory and anti-apoptotic actions of linagliptin, when combined with the antioxidant impact of allopurinol, could result in a renoprotective effect. Lastly, the results of the present study should interrupt the long-term inertia in the field of post-contrast AKI prevention [24]. The small sample size & short period of observation in the current investigation were the major limitations of the study. This study is an uncontrolled observational cross-sectional study, and as such, its findings may contain biases that are challenging to identify or correct. Future studies should verify the results of this study, look into the effects of higher doses of either allopurinol or DPP4I versus the combination of these two agents, and explore novel antioxidant, anti-inflammatory, and anti-apoptotic medications, either independently or in combination. ## Conclusion Linagliptin and allopurinol in combination may offer protection against post-contrast AKI in DKD exposed to radiocontrast. Further studies are needed to support this view. ## Ethical approval This material has not been published previously, in whole or part, and is not under consideration for publication elsewhere. This paper has no tables or figures that would require permission to reprint. The authors have no conflict of interest to declare. All authors participated in the preparation of this manuscript, fulfilled the criteria for authorship, and approved the paper in the current format. The study conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in the prior approval by the institution’s human research committee. This study was not supported by any grant. The trial registration number at ClinicalTrials.gov was NCT03470454. ## Disclosure statement No potential conflict of interest was reported by the author(s). ## References 1. Cho E, Ko GJ.. **The pathophysiology and the management of Radiocontrast-Induced nephropathy**. *Diagnostics* (2022) **12** 180. PMID: 35054347 2. Mehran R, Nikolsky E.. **Contrast-induced nephropathy: definition, epidemiology, and patients at risk**. *Kidney Int Suppl* (2006) **100** S11-S15 3. Pisani A, Riccio E, Andreucci M. **Role of reactive oxygen species in the pathogenesis of radiocontrast-induced nephropathy**. *Biomed Res Int* (2013) **2013** 1-6 4. 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--- title: 'Understanding virtual primary healthcare with Indigenous populations: a rapid evidence review' authors: - Kayla M. Fitzpatrick - Meagan Ody - Danika Goveas - Stephanie Montesanti - Paige Campbell - Kathryn MacDonald - Lynden Crowshoe - Sandra Campbell - Pamela Roach journal: BMC Health Services Research year: 2023 pmcid: PMC10054202 doi: 10.1186/s12913-023-09299-6 license: CC BY 4.0 --- # Understanding virtual primary healthcare with Indigenous populations: a rapid evidence review ## Abstract ### Background Virtual care has become an increasingly useful tool for the virtual delivery of care across the globe. With the unexpected emergence of COVID-19 and ongoing public health restrictions, it has become evident that the delivery of high-quality telemedicine is critical to ensuring the health and wellbeing of Indigenous peoples, especially those living in rural and remote communities. ### Methods We conducted a rapid evidence review from August to December 2021 to understand how high quality Indigenous primary healthcare is defined in virtual modalities. After completing data extraction and quality appraisal, a total of 20 articles were selected for inclusion. The following question was used to guide the rapid review: *How is* high quality Indigenous primary healthcare defined in virtual modalities? ### Results We discuss key limitations to the delivery of virtual care, including the increasing cost of technology, lack of accessibility, challenges with digital literacy, and language barriers. This review further yielded four main themes that highlight Indigenous virtual primary healthcare quality: [1] limitations and barriers of virtual primary healthcare, [2] Indigenous-centred virtual primary healthcare, [3] virtual Indigenous relationality, [4] collaborative approaches to ensuring holistic virtual care. Discussion: For virtual care to be Indigenous-centred, Indigenous leadership and users need to be partners in the development, implementation and evaluation of the intervention, service or program. In terms of virtual models of care, time must be allocated to educate Indigenous partners on digital literacy, virtual care infrastructure, benefits and limitations. Relationality and culture must be prioritized as well as digital health equity. ### Conclusion These findings highlight important considerations for strengthening virtual primary healthcare approaches to meet the needs of Indigenous peoples worldwide. ### Supplementary Information The online version contains supplementary material available at 10.1186/s12913-023-09299-6. ## Background The delivery of quality primary healthcare (PHC) for Indigenous people and communities must be prioritized by local and national governments in Canada [1–3]. When accessing health services, Indigenous peoples experience inequities that stem from a lack of local and Indigenous-centred services, feelings of mistrust towards the healthcare system due to harmful past experiences, and jurisdictional and governmental disputes surrounding responsibility for Indigenous healthcare resources and delivery [4–7]. It’s well documented that Indigenous peoples face many barriers when trying to access PHC, such as the long-standing issue of a lack of PHC providers that provide care in Indigenous communities, which has been further exacerbated by the COVID-19 pandemic [8, 9]. Compounding this, PHC services are usually provided by non-Indigenous practitioners who follow western biomedical approaches, which ignore traditional healing practices and can oftentimes be incongruent with Indigenous ways of knowing [10, 11]. One potential solution to help improve access to and quality of Indigenous PHC in Indigenous communities is through virtual health care modalities. Virtual care is the provision of health-related services and information using telecommunications-based technologies. For this review, we will refer to the terminology “virtual care” to include telemedicine, telehealth, and other virtual modalities to provide PHC. With the unexpected emergence of COVID-19, facilitation of virtual PHC has become more attainable and has the possibility to enhance the health and wellbeing of Indigenous peoples, especially those residing in rural and remote areas. Virtual care provides opportunities for specialty care (e.g., pediatricians) and for Indigenous PHC providers to be able to provide services in areas they may not have regular access to. However, there has been limited consultation with Indigenous communities in the development of these virtual care [12]. To ensure virtual care programs are aligned with community needs and acknowledge their specific cultural context, community engagement is an essential step in the creation of virtual PHC [12]. Indigenous-centred virtual care may offer a means to address existing healthcare gaps and enhance the health of Indigenous communities globally [12]. However, important to consider is the barriers Indigenous peoples face when accessing virtual care, including challenges with technology and lower broadband connectivity. Recent research highlights the consequences of inequitable access to virtual care, characterized as the ‘digital divide’ [13]. The digital divide is shaped by access and uptake of virtual PHC services and is often a contextual consideration for virtual care with Indigenous populations. Concerns surrounding the technological and cultural accessibility of virtual PHC services further highlight the need to explore virtual PHC [14] to ensure holistic aspects of health and self-management, health promotion and prevention are incorporated [2, 15, 16]. The rapid transition from in-person PHC service delivery to virtual modalities provides a critical opportunity to strengthen virtual care programs and services for Indigenous communities. The objective of this review is to synthesize the current evidence around virtual PHC services focused on Indigenous populations. This review examines the impacts and outcomes of virtual Indigenous PHC services, the barriers and enablers of successful Indigenous PHC virtual care, and existing virtual care frameworks. Moreover, environmental and contextual factors that impact Indigenous virtual PHC care are explored. ## Methods Given the urgent need to understand Indigenous virtual PHC in the context of COVID-19, a rapid review methodology was purposefully chosen. Rapid reviews allow for a timely synthesis of available evidence on a particular topic and are commonly used for healthcare decision makers, knowledge users and policy [17, 18]. Rapid reviews include the development of a focused research question, a less developed search strategy, evidence searches, and more simplified data extraction and quality appraisal of the identified literature, when compared to traditional systematic reviews [18]. This rapid review was initially conducted from August to December 2021 and informed by rapid review methods outlined by the National Collaborating Centre for Methods and [19]. The following question was used to guide the rapid review: *How is* high quality Indigenous PHC defined in virtual modalities? A protocol has been registered and is published on the Open Science Framework Registries (10.17605/OSF.IO/VTUH7). This protocol was published after the search was conducted and reviewed by the expert librarian (SC). This is important to note, as we acknowledge we did not follow the JBI best practice guidelines on scoping reviews which recommends publishing the protocol prior to the study [20]. ## Search strategy The search strategy was developed to identify healthcare quality indicators, cultural safety indicators, and Indigenous perspectives of virtual care. A search was executed by an expert searcher/librarian (SC) on the following databases: OVID Medline, Ovid EMBASE, and EBSCO CINAHL using controlled vocabulary (eg: MeSH, Emtree, etc) and keywords representing the concepts “Indigenous people, “quality of care”, and “telehealth/remote care”. Searches were adjusted appropriately for different databases. Searches were conducted on August 10, 2021 and updated on January 23, 2023. All databases were searched from inception to present. Modified versions of search filters from the University of Alberta Health Sciences Search Filters were applied to retrieve some concepts (1–10). Results [602] were exported to the Covidence systematic review program, where duplicates [163] were removed. Detailed search strategies are available in Appendix 1. ## Selection criteria The Population, Intervention, Comparator, Outcomes, and Design (PICOD) framework was employed to develop the eligibility criteria for this rapid review (Table 1). Publications were included in the review if they were [1] primary empirical studies (qualitative, quantitative, or mixed-methods), theoretical studies; reviews of empirical studies; implementation studies [2] focused on Indigenous peoples in Canada/USA/Australia/New Zealand (NZ) [3], focused on experiences of PHC for Indigenous populations in virtual modalities, and [4] interventions in virtual PHC delivery which included phone calls, text, video calls (e.g., Zoom, Facetime). Publications were excluded if they were [1] Indigenous populations outside of Canada/USA/Australia/NZ/circumpolar regions [2] thesis, commentaries, or opinion pieces [3] if the populations were non-Indigenous and [4] if the PHC modalities were not virtual interventions. Noteworthy, circumpolar regions was not included in our published protocol; however, circumpolar regions were included in our search strategy. Canada, USA, Australia, New Zealand and Circumpolar regions that are home to the Sami people in northern Europe have all experienced similar patterns of colonization and are currently facing very similar issues within the Indigenous populations [21, 22]. While each of these groups experience similar health issues with Indigenous populations, each healthcare system in each country differs in terms of privatized vs. public funding for healthcare. While this may be important context, it is important for us to note it was not something that we assessed or considered in this review. For title and abstract screening, each source was independently evaluated twice by authors (KM, MO, DG, PR). A full text review was conducted by authors (KM, MO, DG, KF, PC, PR) to verify which articles met inclusion criteria and any disagreements were resolved by discussion and with senior researchers (KF, PR) until a consensus was reached. See Fig. 1 for PRISMA [23] flowchart of publications included and excluded and appendix 2 for the PRISMA-S checklist. Table 1PICO(S) Statement Population Indigenous populations accessing PHC services in Canada/US/Australia/NZ/circumpolar region Intervention Interventions focused on experiences of PHC for Indigenous populations in online or telephone (virtual) modalities Comparison n/a Outcome Perspectives on high quality virtual PHC; Health care quality indicators; Cultural safety indicators Study design Primary empirical studies (qualitative, quantitative, or mixed methods), theoretical studies; reviews of empirical studies; implementation studies Fig. 1PRISMA Inclusion and Exclusion of Studies. (* Consider, if feasible to do so, reporting the number of records identified from each database or register searched (rather than the total number across all databases/registers). ** If automation tools were used, indicate how many records were excluded by a human and how many were excluded by automation tools.) ## Data extraction Each article was extracted twice by at least two different researchers (KF, DG, ML, PC, KM, PR) for consistency, and data was charted into a data extraction form in Microsoft Excel that included the source title, publication date, location, study characteristics, summary, and Critical Appraisal Skills Programme (CASP) quality appraisal (refer to Appendix 3 for the data extraction form). A summary of the data generated is available in Table 2 below and the full dataset generated from the extraction is available from the corresponding author on reasonable request. ## Data synthesis Originally, as outlined in our protocol, we intended to use thematic content analysis, however, as we progressed in this review, we did not feel that quantifying words, themes or concepts as used in content [24] was the best method to examine Indigenous virtual care and instead felt that data reduction would produce more descriptive and representative results. We therefore, utilized Maxwell’ [25] and Miles and Huberman’s [26] qualitative thematic analysis technique of descriptive and pattern coding. Open-coding by authors (KF, MO, PC) was completed and then categorized to identify patterns, similarities, and differences throughout the data. Themes were reviewed and verified by an Indigenous health services researcher (PR), a public health and health policy researcher (SM), and a PHC service researcher and an Indigenous PHC provider (LC). ## Quality assessment The quality of each study was evaluated using the CASP [27]. The CASP tool is designed as a pedagogic tool and there is no assigned score, if the answer is “yes” to the first $\frac{2}{3}$ questions then the article can be considered of poor [27]. Quality assessments were divided in half and independently completed by 2 reviewers (MO, DG); any conflicts were resolved through consensus. No studies were appraised to be of poor quality; therefore, no articles were excluded from the review based on the CASP evaluation. Due to the urgent nature of this review, grey literature was not included. ## Results In total, 21 studies met all criteria (Table 2) and included systematic reviews, RCT, qualitative studies, and case-control studies. Literature included work from Australia [7], Canada[7], New Zealand [5], USA [6] and circumpolar regions [2]. Systematic reviews included in our review found that involving Indigenous communities in the design, implementation, and evaluation would benefit virtual care programs and mitigate costs of healthcare overall. Most of the data collection for the qualitative studies evaluated addressed the research issue but there were discrepancies in the focus on ‘satisfaction only’ surveys and the inability to extrapolate results further. Case studies exploring telehealth models for the treatment of specific health needs were found to be beneficial, however, it is important to keep in mind that many of these studies do not consider the social determinants of health leading to a narrower definition of health. Many studies insisted on ensuring Indigenous perspectives are utilized to provide better quality of the virtual program or service. Table 2Data from included studiesAuthor (publication year)TitleSettingStudy DesignSampleMain PurposeCaffery, L. J. et al. [ 2018]How telehealth facilitates the provision of culturally appropriate healthcare for Indigenous AustraliansAustraliaQualitative Interviews9 healthcare staffTo explore how telehealth facilitates or impedes the provision of culturally appropriate healthcare to Indigenous Australians. Carswell, P. [2015]Te Whiringa Ora: person-centred and integrated care in the Eastern Bay of Plenty, New ZealandNew ZealandCase study: Participatory formative evaluation53 patients; mixof Maori andNew ZealandEuropeanTo understand how community-based programs can facilitate interdisciplinary care for patients and their families. Fraser, S. etal. [ 2017]Use of telehealth forhealth care of Indigenouspeoples with chronicconditions: a systematicreviewAustralia, New Zealand, Canada, USA, Circumpolar regionsSystematicreview32 articlesincludedTo explore the utility oftelehealth for Indigenouspeoples living withchronic health conditions. Gibson, K. L.et al. [ 2011]Conversations ontelemental health:listening to remoteand rural FirstNations communitiesCanadaQualitativeinterviews59 communitymembersTo explore experienceswith and perspectives oftelemental healthtechnologies from FirstNations communities. Ingemann, C.et al. [ 2020]Patient experiencestudies in the circumpolarregion: a scoping reviewCircumpolarnorthScopingreview96 articlesincluded forextractionTo investigate patientexperiences withinhealthcare across thecircumpolar north. Jones, L. etal. [ 2017]Development and Useof Health-RelatedTechnologies inIndigenous Communities:Critical ReviewCanada,Australiaand USACriticalreview34 articlesincludedTo examine literaturesurrounding the use,adaptation, anddevelopment of assistivehealth technologies forolder Indigenous adults. Mashru, J. etal. [ 2017]Management ofInfectious diseases inremote northwestern Ontario with telemedicinevideoconferenceconsultationsCanadaCase study:Descriptivestudy76 patientsTo describe theimplementation of atelemedicine-basedinfectious diseaseconsultation service andpatient satisfaction withthe service. Mendez, I. etal. [ 2013]The use of remotepresence for health caredelivery in a northernInuit community: afeasibility studyCanadaCase studyand qualitativeRobot wasactivated 252times in a 15month period(exact samplesize notprovided)To evaluate the feasibilityof the RP-7 robot inimproving the health ofInuit from a remotenorthern community. Mooi, J. K. etal. [ 2012]Teleoncology forIndigenous patients:The responses ofpatients and healthworkersAustraliaCase study:Descriptivestudy9 Indigenousparticipants, 2familymembers, 6healthcareworkersTo assess satisfaction withteleoncology and videoconsultations forIndigenous patients, theirfamilies, and health careworkers. Russell, S. etal. [ 2021]Validation of theKimberley IndigenousCognitive Assessmentshort form (KICAscreen) for telehealthAustraliaProspectivefield trial33 participantsTo examine the utility ofan Indigenous-specificdementia screening tool ina telehealth setting. Volpe, T. etal. [ 2014]Mental health servicesfor Nunavut childrenand youth: evaluatinga telepsychiatry pilotprojectCanadaPilot project25 communitiesTo examine the utility ofpsychiatric consultationservices usingvideoconferencingtechnology for healthand mental healthworkers in Nunavut. Sicotte, C. etal. [ 2011]Use of telemedicinefor haemodialysis invery remote areas: TheCanadian first nationsCanadaLongitudinalstudy19 individualsfrom 2 differentcommunitiesTo compare the heath careutilization of patientsreceiving telehaemodialysisservices between twocommunities. Doorenbos,A. Z. et al.[2011]Developing the NativePeople for CancerControl TelehealthNetworkUSACase Study:Participatoryformativeevaluation513 totalpatientencountersTo develop a telehealthnetwork deliveringpostdiagnosis cancer careand education services forpatients, families, andhealthcare providers. Smith, A. C.et al. [ 2012]A mobile telemedicineenabled ear screeningservice for Indigenouschildren in Queensland:activity and outcomes inthe first three yearsAustraliaRetrospectivereview1053 childrenregistered, 2111screeningassessmentscompletedTo assess service activityand outcomes of a mobiletelemedicine-enabledscreening services. Williams, M.et al. [ 2017]Face-to-face versustelephone delivery ofthe Green Prescriptionfor Maori and NewZealand Europeans withtype-2 diabetes mellitus:influence on participationand health outcomesNewZealandRandomizedControl Trial138 patients;mix of Maoriand NewZealandEuropeanTo compare the uptake andeffectiveness of twodifferent modes of deliveryfor the Green Prescriptionlifestyle program: face-toface vs. telephone-basedservices. Caffery, L. J.et al. [ 2018]Outcomes of usingtelehealth for theprovision of healthcareto Aboriginal andTorres Strait Islanderpeople: a systematicreviewAustraliaSystematicReview14 articlesincludedTo examine the reportedoutcomes of telehealthservices delivered toIndigenous Australians. Doorenbos,A. Z. et al.[2010]Satisfaction WithTelehealth for CancerSupport Groups inRural American Indianand Alaska NativeCommunitiesUSADescriptivestudy32 surveyrespondentsTo assess informationneeds and satisfaction withtelehealth support groupservices among cancersurvivors in ruralcommunities. Kruse, C. S.et al. [ 2016]Telemedicine Use inRural Native American Communities in theEra of the ACA: aSystematic LiteratureReviewUSASystematicreview15 articlesincludedTo explore the cost, quality,and accessibility oftelemedicine in rural NativeAmerican communities. Potnek, M. F.[2020]Urban AmericanIndian Clinic SmokingCessation ProgramUSACase-controlstudy5 programparticipantsTo implement a nursepractitioner-led smokingcessation pilot program in an urban health centre. Wikaire, E. etal. [ 2022]Reducing healthcareinequities for Māori usingTelehealth duringCOVID-19NewZealandQualitativeInterviews5 Māori healthprofessionals;12 MāoripatientsTo investigate Māoriexperiences of telehealthconsultations during theMarch 2020 COVID-19lockdown. Graham, F. etal. [ 2022]Stakeholder perspectivesof the sociotechnicalrequirements of atelehealth wheelchairassessment service inAotearoa/New Zealand: AQualitative AnalysisNewZealandQualitative Interviews1 Māori healthprofessional; 3Māoriwheelchairusers. To examine the designrequirements of a telehealthwheelchair assessmentservice from theperspectives of keystakeholders such aswheelchair users and theirfamilies, includingIndigenous (Māori) andhealth professionals. From the included studies, four themes emerged on virtual delivery of Indigenous PHC: [1] limitations and barriers of virtual PHC, [2] Indigenous-centred virtual PHC, [3] virtual Indigenous relationality, [4] Collaborative approaches to ensuring holistic virtual care. To understand how to begin to define high quality Indigenous virtual PHC, we will first discuss the limitations and barriers to virtual care to understand what factors should be considered to produce high quality and what factors to avoid. We will then describe the components of high quality Indigenous virtual care which include Indigenous-centred, relationality, collaboration, and holistic care. ## Theme 1: Limitations and barriers of virtual primary healthcare While virtual modalities are a promising solution to enable improved access to healthcare for Indigenous communities, there are several limitations and barriers that the authors highlighted for consideration. This included components such as challenges with a lack of face-to-face consultation, in addition to several cultural, technological, and educational barriers. With the inability to perform physical exams in the virtual space, one key issue identified was safety and whether or not a medical evaluation could be appropriately performed through a virtual [28–30]. In addition, the virtual setting limits opportunities to form trusting relationships between patient and [31, 32]. This can be problematic because building trust and rapport through relationships and community engagement is essential to ensuring the success and the provision of culturally safe health services to Indigenous [32, 33]. Noteworthy, some literature speaks to the history of Indian hospitals and ongoing systemic racism, and the long track record of distrust, particularly in the Canadian healthcare system with Indigenous populations, making rapport building and finding ways to build confidence between patient and provider even more of a priority [34]. Fraser and team [31] emphasized that “Indigenous people have the right to culturally safe care… this can be facilitated through respectful listening to and meaningful engagement with Indigenous peoples and communities…” ([31], p.11). Few studies looked at the development of implementation frameworks for Indigenous virtual healthcare programs and services. Without clear guidelines on how to engage with Indigenous communities in the virtual space to appropriately and effectively provide care, studies identified that there is an increased risk of harm and/or undue stress for patients [16, 35, 36] One study spoke to the lack of regional and national strategies and standards for the implementation of [37]. Adding to this, several studies pointed to the lack of cultural inclusion into frameworks and virtual care [31, 38, 39]. Similarly, Caffery and colleagues [40] discovered that there is a lack of evidence surrounding evaluation and evaluation frameworks for the delivery of virtual healthcare to Indigenous Australians which was confirmed by other [36] who discussed similar concerns in Canada, USA, and Australia. Another critical consideration is privacy of patients’ data as well as the privacy of a patient’s environment or space [37, 41]. Ensuring that virtual platforms are compliant with privacy regulations is a major ongoing challenge highlighted by several studies [28, 42]. Another consideration around privacy is related to relationships and trust with a provider which has been argued to be eroded in the virtual care environment [26, 27, 38]. Moreover, when considering the privacy of a patient’s environment, addressing complex trauma in the virtual setting is more difficult. Overcrowding and housing is a common problem in some Indigenous communities and can be problematic for individuals who are in particularly challenging living conditions to find a private location in their [43, 44]. Barriers associated with technology were noted often in the included articles. Many Indigenous communities experience lower socioeconomic status, may not have access to technology platforms and are commonly located in geographically rural areas with varying levels of bandwidth and internet [30–32, 45, 46]. As highlighted in the literature, the technology requires expensive equipment and training that is needed upfront [37]. Technology also requires sustainable long-term funding to be maintained, which is a common challenge within Indigenous communities and with virtual care programs that are being delivered from short-term research grant [32, 33, 37, 41]. In addition to technology, internet access, and infrastructure barriers, ‘digital literacy’ or the ‘digital divide’ which is a gap in access to digital technologies and infrastructure were cited as a major barrier which may be greater in at-risk [29, 41]. Other evident barriers to virtual care modalities included the time and expertise required to train healthcare staff about how virtual care technology works and to explain virtual care procedures to [31]. Due to the digital divide, telemedicine education and training are required for both providers and patients [46]. In addition, challenges were noted for virtual care providers in regards to adjusting to new procedures and practices in the day-to-day workflow [35]. A few studies found that the promotion of virtual care programs or knowledge of programs in community was also limited, again highlighting the importance of community engagement to increase awareness and buy-in from community [16, 46]. Further, lack of integration of traditional languages in virtual care technologies created barriers to access, which were cited in one article [31]. Lastly, virtual technologies are not accessible for all patients, such as those with medical disabilities (e.g., hearing loss, vision loss, dementia) [47]. The intersection of race, class, and health status all contribute to challenges experienced when implementing Indigenous virtual PHC which must be considered when designing programs of this nature and future research will be needed to better understand these intersections. While many barriers were identified, researchers described promising ways to mitigate some of these barriers and enhance virtual PHC for Indigenous populations. ## Theme 2: Indigenous-centred virtual primary healthcare The majority of the articles included in this review were identified as being Indigenous-centred, meaning the program was developed with an Indigenous focus, while only one was Indigenous-led, meaning Indigenous communities and/or leaders led the design and implementation of the intervention. Consequently, all virtual care research and programs reviewed were not developed by and led by Indigenous communities (e.g., health centres), but rather developed in partnership with Indigenous communities and/or leadership. Several sources shared that the key components to successful Indigenous-centred virtual care implementation were engagement, community support, and partnership development, which in some cases, included training of local Indigenous [33, 38]. Indigenous-centred virtual PHC help to mitigate the barriers that were highlighted above such as trust. A few studies highlighted the inclusion of Indigenous healthcare staff to support virtual care programs. The inclusion of Indigenous staff ensured Indigenous voices and values were a core component in the development and implementation of the virtual care [32, 39]. For example, one study described the positive impact of having a traditional healer present during the virtual care [40]. Another study discussed the grounding of their program in holistic and traditional principles (Whānau Ora) of the local Indigenous [33]. A piece of literature also supported investment in cultural competence with the additional inclusion of a trauma-informed lens as a way to ensure the virtual care programs were appropriate for Indigenous-centered care [33]. Several of the studies were developed through partnerships with governmental health bodies (e.g., Alberta Health Services) and Indigenous leadership in communities and/or organizations [36, 38, 39, 41]. One example described how researchers spent a considerable amount of time over several years, and continue to engage with local partners in all stages of implementation and [38]. It was evident that the studies with strong Indigenous partnerships also had a greater emphasis on culture in their virtual programs and [36, 38]. For example, one review described how a group in the USA prioritized meaningful engagement with partners and community, which resulted in the invention of the term “tele-spirituality” [36]. Tele-spirituality “describes consultations related to traditional medicine or ceremonial practices” ([36], p. 5). When virtual programs prioritize Indigenous voices, their uptake and overall sustainability are enhanced, as the community feels ownership over what they have [36]. On the contrary, the studies with less emphasis on Indigenous engagement or partnership were not as connected to respective Indigenous cultures, which could potentially signify a lack of cultural safety in the [39, 41]. Another example in the USA supporting American Indian health programs described how a telemedicine program did not include culture and that community was not consulted, and thereby, the lack of culture and Indigenous perspective was highlighted as a priority area for future [39]. ## Building relationships and trust Relationality is a core concept for Indigenous communities worldwide [28], with relationships being described as the ‘spiritual and cultural foundations of Indigenous peoples,’ [48]. With the delivery of PHC in a virtual space, the emphasis on relationality was emphasized in articles and needs to be prioritized as patients and providers are unable to interact face to [30]. As identified by Carswell [33] building trust is a crucial step to enhancing the relationality between Indigenous patients and their healthcare providers. Two articles described how taking time to build mutual trust and understanding with Indigenous patients was integral to promoting adherence to their virtual PHC [29, 49]. Another article described how Indigenous patients “need to trust the service is providing something valuable to the patients,” which should be done through continual relationship building with healthcare providers [33]. A key enabler to strengthening relationality is building capacity within community. One article shared how continuous community engagement in the development and implementation of virtual PHC services provided an opportunity to build critical skills for community [41]. However, none of the articles mentioned concrete plans for capacity building that would otherwise enable Indigenous communities to sustain the virtual care programs over time. ## Enhancing digital access Indigenous patients need to feel confident about the technology and its infrastructure to ensure ease and comfort in navigating virtual care services. As mentioned earlier, one review highlighted how studies have reported that Indigenous peoples have privacy and confidentiality concerns surrounding communication technologies, which causes discomfort in navigating telehealth [31]. To address these concerns and barriers, one article highlighted the importance of providers taking time to address worries and explain how patient information is being protected with Indigenous patients [45]. Improving digital literacy is another way to ensure the success of virtual care programs. As highlighted above in theme 1, the “digital divide” has resulted in communities lacking the necessary infrastructure (e.g. quality internet service, broadband, ample cell towers) to sustain telehealth [30, 36]. Kruse [32] and team underscored the importance of funding and resource allocation toward improving technological infrastructure and enhancing digital literacy within Indigenous communities to prevent sustainability barriers [32]. Otherwise, the utility of telehealth may prove to be inadequate and underutilized. ## Improved continuity of PHC and medical specialist outreach Many Indigenous peoples reside in geographically rural and remote areas, which poses barriers to accessing timely PHC services. Telehealth provides a crucial opportunity to improve PHC access and delivery for Indigenous peoples by improving continuity of care and by enhancing accessibility for Indigenous patients seeking specialized care services. Articles highlighted how virtual care clinics increased opportunities for PHC to connect Indigenous clientele with medical specialists, who would otherwise rarely conduct in-community visits [28]. Furthermore, for some communities, specialist appointments conducted via telehealth eliminated transportation costs that would have been incurred if patients needed to travel to larger urban centres to receive that specialist medical care in-[28]. Some articles highlighted that another benefit to virtual specialist care is that it provides a continuity of care, which enables patients to receive consistent care from their [16], rather than the limited interactions during those infrequent physician visits to community. ## Theme 4: Collaborative approaches to ensuring holistic virtual care Holistic care goes beyond the physiological metrics and examines the foundational relationships between physiological, psychological, social, spiritual, and cultural [50]. This collaborative strategy for addressing health [42] is considered integral to promoting quality healthcare for Indigenous [12, 51]. Only half of the articles mentioned the holistic aspects of care [28, 32, 37–41, 45–47, 52, 53], which adds to the literature described by Purdie et al., [ 51] and Fraser et al., [ 31] exposing existing gaps in Indigenous healthcare research from a holistic perspective. One good example mentioned the importance of integrating virtual care into holistic frameworks and addressed varied cultural conceptualizations of health and wellness, but stated that these aspects were not the focus of the [16]. Another article specifically elaborated on the importance of creating or maintaining aspects of holistic care in a virtual care [33]. Several critical and scoping reviews described that holistic care is essential to the delivery of comprehensive [31, 35, 36]. Fraser and team [31] conducted a systematic review on telehealth for Indigenous peoples with chronic disease and emphasized a clearly defined contemporary Aboriginal model of holistic care by Helen [50]. This included cultural, spiritual, social, emotional and physical dimensions and is influenced by traditional and contemporary components described as “the intersection of both the layers and dimensions which creates the interconnectedness for a whole of life approach to Aboriginal wellbeing” ([50], p. 8). Successful incorporation of holistic care was often related to receiving information in one’s language and/or having a good [35, 54–60], but also focussed on shifting the provision of healthcare from treating the individual to an interdependent [33, 36]. Community-based decision making, involving patients in assessment processes, improving overall patient health literacy within Indigenous [49], and developing technology that includes family and [42, 61], all while incorporating culture and tradition into [16] can support a shift from individual self-management to a whole of community [33], leading to more holistic and integrative care. Diversifying points of access to services leads to an increase in program uptake, can demonstrate the inherent value of the service, and may increase the likelihood of engaging multiple [54], which leads to better health [51]. Some literature highlighted that western and colonial approaches to providing healthcare often compartmentalize and separate interrelated aspects that influence health [31], including access to services, the treatment of illness, and the definition of health [36]. ## Discussion The objective of this review was to synthesize the current evidence around virtual PHC services focused on Indigenous populations to be able to understand how quality Indigenous PHC is defined in virtual modalities. Our results show that for Indigenous virtual PHC to be of high quality it must be designed, implemented and evaluated in ethical and culturally-safe ways. This is increasingly important as more services shift to virtual delivery modalities in response to the COVID-19 pandemic and beyond. Moreover, we highlighted that virtual care is not inherently more appropriate or safer for Indigenous people than in-person delivery and the risk remains that virtual care can replicate current harmful systems of oppression of Indigenous people in the health system [62–66]. It is therefore important to consider Indigenous-led and Indigenous-centred virtual services that enable healthcare services to be both culturally safe and trauma-informed, in order to provide high quality care to Indigenous clients. This is encouraging for new virtual models of care to be designed in such a way that is congruent with the Truth and Reconciliation Commission of Canada’s Health Related Call to [67] and the United Nations Declaration on the Rights of Indigenous People outlining the importance of self-determination as an Indigenous determinant of [68]. Telemedicine is a useful tool for virtual healthcare delivery beyond the current pandemic context, as individuals living in rural and remote areas or those needing alternative accommodations could benefit from the continuity of virtual [69]. The range of technology-driven health services varies from telephone or virtual [69–73], text [74–76], store and forward [77, 78], web-based interventions and supports to the use of a remote presence robotic technology (RPRT)[37, 69]. Regardless of the modality used, it is imperative that the quality of virtual care meets or exceeds standards of in-person care and includes cultural and contextual considerations to ensure its success with Indigenous [79]. The digital divide is shaped by access and uptake of virtual care services and is often a contextual consideration for virtual care with Indigenous populations. Concerns surrounding the technological and cultural accessibility of virtual care services further highlight the need to explore patient experiences with virtual PHC through key [14] to ensure a focus on incorporating holistic aspects of health and self-management, health promotion and [2, 15, 16]. Further research is needed to examine how digital exclusion is experienced by diverse population groups, and across intersecting factors of gender, sex, age, geography, disability, race, ethnicity and [80]. One could argue that using a telephone for a phone call versus a video call is easier to access and better understood. Video conferencing takes more infrastructure, education, and time to set up; however, video conferencing provides enhances opportunities for relationship and rapport building. For an intervention, service, or program to be Indigenous-centred, Indigenous leadership and users need to be partners in the development, implementation and evaluation of the intervention, service or program. In terms of virtual interventions, time must be allocated to educate Indigenous partners on digital literacy, virtual care infrastructure, benefits, and limitations. Research shows that clear guidance and support with technological infrastructure for health facilities and staff needs to be considered to ensure the successful delivery of Indigenous virtual healthcare and sustainable [79]. This requires an understanding of how to provide culturally competent and culturally safe care while being aware of digital determinants of health. For many Indigenous populations, experiences and impacts of digital determinants of health will be inherently intertwined with ongoing processes and policies of colonialism as the primary driver of Indigenous health [67] and so structural change must also be driven at the policy and legislative levels. The digital determinants of health relate to our findings as it includes concepts such as access to digital resources, digital health literacy, beliefs about the potential for digital health to be helpful or harmful, values and cultural norms for use of digital resources, and integration of digital resources into a community and health [81]. Crawford and Serhal [81] developed a Digital Health Equity Framework which underscores the intersection of the digital determinants of health and digital health equity and the importance of using an ecological perspective when approaching digital health [81]. Indigenous virtual PHC initiatives can ensure digital health equity by identifying and addressing the potential gaps and needs within the digital determinants of health which have been highlighted in this review. For example, an Indigenous patient’s digital health care access and quality are shaped by their environment; in Canada, overcrowded homes are a reality in Indigenous communities which can result in a lack of privacy for patients, moreover, due to poverty, many may not have access to virtual care solutions at all [12]. If these factors are not considered when developing Indigenous virtual care interventions, quality of care will be negatively impacted, and digital health equity will therefore not be achieved. Worthy of mention here is a promising endeavour by the World Health Organization in the development of a strategy on digital health which will aim to “develop the infrastructure for information and communication technologies for health…[and] to promote equitable, affordable and universal access to their benefits” [80, 82]. One other positive step towards closing the digital divide was taken recently in Canada with the introduction of the Universal Broadband Fund, introduced by the Canadian Federal government in 2020. This was a C$1.75 billion investment to bring high-speed internet to rural and remote communities. As part of this initiative, up to C$50 million has been made available to support mobile internet projects that benefit Indigenous peoples in [80]. In addition to considering the digital determinants of health and digital health equity, a holistic approach to Indigenous virtual healthcare must be taken into account. This requires virtual care initiatives to also factor in relationality, spirituality, and self-determination. Further work needs to be done and directed by Indigenous people to understand how to best incorporate holistic approaches in a virtual environment. Virtual care training, digital literacy and cultural competence are often lacking in healthcare provider training. For healthcare workers who are expected to provide virtual healthcare to Indigenous populations, education about relationality, cultural humility, digital determinants of health and digital health equity should be incorporated into training as virtual healthcare interacts with economic, social, and cultural realities as well as with the social determinants of health. Moreover, attention must be paid to innovative ways to build trust and relationships with patients in a virtual space. One body of research has considered what is called “web-side” manner where healthcare providers are encouraged to ensure things such as their badge being visible, having the camera at eye level, and removing any background visual and audio [83]. Future studies should be conducted with a focus on culturally rooted perceptions of surveillance technologies used to support Indigenous patients, as this technology has the potential to replicate cycles of oppression and colonization leading to substantial barriers to virtual care. Co-design of virtual Indigenous PHC can help to mitigate these cycles and to be able to provide culturally safe and rooted care. Butler and her team described in 2022 that relevant co-design with First Nations Australians includes [1] First Nations Australians leadership [2] culturally grounded approach [3] respect [4] a benefit to First Nations communities [5] inclusive partnerships and [6] evidence-based decision making [84]. This is the first evidence review to the best of our knowledge that maps out the literature pertaining to Indigenous virtual PHC. Our results were limited to English language papers due to time and resource constraints. We do believe our search strategy was robust but as this was a rapid review the search was not comprehensive and did not provide quantitative measures of program effectiveness. As there is a steady shift to Indigenous virtual PHC modalities, it could be useful for scholars to continue this work to understand how Indigenous virtual PHC evolves. Future work could utilize a realist scoping review approach to provide information on how Indigenous virtual PHC is implemented and under what circumstances is it effective. Future work may also need to include translators to be more broadly inclusive of Indigenous experiences of virtual care beyond the regions included in this review and could provide valuable learnings from global Indigenous populations. ## Conclusion The use of virtual healthcare technology is a promising innovative solution to providing more equitable PHC for Indigenous populations. Indigenous virtual PHC must consider technology and infrastructure barriers, access, digital health literacy skills, and other factors that can impact engagement with virtual care modalities. This means looking beyond individual factors to the health system as a whole to reduce virtual healthcare disparities for Indigenous peoples. Relationality and culture must be prioritized as well as digital health equity. 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--- title: 'Factors associated with viral RNA shedding and evaluation of potential viral infectivity at returning to school in influenza outpatients after treatment with baloxavir marboxil and neuraminidase inhibitors during 2013/2014–2019/2020 seasons in Japan: an observational study' authors: - Jiaming Li - Keita Wagatsuma - Yuyang Sun - Isamu Sato - Takashi Kawashima - Tadashi Saito - Yasushi Shimada - Yasuhiko Ono - Fujio Kakuya - Nobuo Nagata - Michiyoshi Minato - Naoki Kodo - Eitaro Suzuki - Akito Kitano - Toshihiro Tanaka - Satoshi Aoki - Irina Chon - Wint Wint Phyu - Hisami Watanabe - Reiko Saito journal: BMC Infectious Diseases year: 2023 pmcid: PMC10054210 doi: 10.1186/s12879-023-08140-z license: CC BY 4.0 --- # Factors associated with viral RNA shedding and evaluation of potential viral infectivity at returning to school in influenza outpatients after treatment with baloxavir marboxil and neuraminidase inhibitors during 2013/2014–2019/2020 seasons in Japan: an observational study ## Abstract ### Background This study assessed the differences in daily virus reduction and the residual infectivity after the recommended home stay period in Japan in patients infected with influenza and treated with baloxavir (BA), laninamivir (LA), oseltamivir (OS), and zanamivir (ZA). ### Methods We conducted an observational study on children and adults at 13 outpatient clinics in 11 prefectures in Japan during seven influenza seasons from $\frac{2013}{2014}$ to $\frac{2019}{2020.}$ Virus samples were collected twice from influenza rapid test-positive patients at the first and second visit 4–5 days after the start of treatment. The viral RNA shedding was quantified using quantitative RT-PCR. Neuraminidase (NA) and polymerase acidic (PA) variant viruses that reduce susceptibility to NA inhibitors and BA, respectively, were screened using RT-PCR and genetic sequencing. Daily estimated viral reduction was evaluated using univariate and multivariate analyses for the factors such as age, treatment, vaccination status, or the emergence of PA or NA variants. The potential infectivity of the viral RNA shedding at the second visit samples was determined using the Receiver Operator Curve based on the positivity of virus isolation. ### Results Among 518 patients, 465 ($80.0\%$) and 116 ($20.0\%$) were infected with influenza A (189 with BA, 58 with LA, 181 with OS, 37 with ZA) and influenza B (39 with BA, 10 with LA, 52 with OS, 15 with ZA). The emergence of 21 PA variants in influenza A was detected after BA treatment, but NA variants were not detected after NAIs treatment. Multiple linear regression analysis showed that the daily viral RNA shedding reduction in patients was slower in the two NAIs (OS and LA) than in BA, influenza B infection, aged 0–5 years, or the emergence of PA variants. The residual viral RNA shedding potentially infectious was detected in approximately 10–$30\%$ of the patients aged 6–18 years after five days of onset. ### Conclusions Viral clearance differed by age, type of influenza, choice of treatment, and susceptibility to BA. Additionally, the recommended homestay period in Japan seemed insufficient, but reduced viral spread to some extent since most school-age patients became non-infectious after 5 days of onset. ### Supplementary Information The online version contains supplementary material available at 10.1186/s12879-023-08140-z. ## Background Influenza (the flu) is a respiratory infectious disease caused by influenza viruses that can cause seasonal epidemics annually. Seasonal epidemics are mainly caused by influenza A and B viruses. The World Health Organization (WHO) estimates that seasonal influenza results in 250,000 to 500,000 deaths annually [1], which is a severe burden on public health worldwide. Therefore, the effective treatment and control of the spread of influenza are crucial issues. Neuraminidase inhibitors (NAIs) have been widely used to treat influenza in Japan [2]. In 2000, oseltamivir and zanamivir were approved for influenza treatment, while peramivir and lanimivir were approved in 2010. In 2018, baloxavir marboxil (baloxavir), a cap-dependent endonuclease inhibitor with a strong antiviral effect, was approved for influenza A and B [3], with reports of a significantly reduced viral titer after treatment [4, 5]. However, in clinical trials, the viral RNA shedding of baloxavir was compared only with oseltamivir [5–7] and not with other NAIs, such as lanimivir or zanamivir. Therefore, it is necessary to compare its viral RNA shedding with other NAIs. Notably, it is reported that the emergence of antiviral-resistant viruses can delay viral clearance [8]. For NAIs, oseltamivir-treated patients developed resistance 0.4 to $4.0\%$ of post-treatment isolates from adults and in 3.0 to $37.0\%$ of isolates from children [9]. The viruses with NA gene substitution H275Y (NA/H275Y) are the most commonly resistant in A/H1N1pdm09, and the viral clearance was reported to be delayed [10]. Likewise, in baloxavir-treated patients, viruses with polymerase acidic (PA) gene substitutions of I38T/F/M were shed at a rate of $2.2\%$ in phase II studies and $9.7\%$ in phase III studies, and those viruses showed reduced susceptibility to baloxavir [5, 11]. In an open-label study limited to pediatric patients, viruses with PA gene substitutions of I38T/F/M shed at a rate higher than $23.4\%$ [12], and the subsequent observational studies reported 3.8–$41.0\%$ emergence of PA variants (such as PA/E23G/K, I38F/M/K/S/T, or E119D) after treatment [6, 13–17]. Additionally, the rebound of viral RNA shedding was observed in the patients who developed these PA variant viruses after baloxavir treatment [12, 16]. Thus, the emergence of antiviral resistance is to be considered when evaluating the viral clearance in patients who received anti-influenza treatment. Japanese schools have a mandated “stay at home” period when children are infected with influenza to avoid its spread. The School Health and Safety Act of Japan, enforced in 2012, stipulates that schoolchildren should stay at home for at least five days after the onset of illness, regardless of the timing of defervescence [18]. This 6 day-stay at home rule (including the day of onset) is applied not only to schoolchildren but also to students in high schools, colleges, universities and adults in many workplaces in Japan. However, few studies have evaluated the residual viral RNA shedding of patients after returning to school or workplace [19]. Therefore, evaluating the residual status of the influenza virus after five days of onset is necessary to determine the adequacy of the duration of school and workplace absence recommended in the School Health and Safety Act. In the present study, we assessed the differences in daily viral reduction calculated from two-point samplings in influenza outpatients after receiving treatment with either cap-dependent endonuclease inhibitor, baloxavir, or three NAIs (laninamivir, oseltamivir, and zanamivir). We also examined whether the emergence of viruses with reduced susceptibility to baloxavir or NAIs could affect viral RNA shedding. Furthermore, we evaluated the potential viral infectivity in influenza A or B infected patients after 5 days of onset by viral RNA shedding in the second visit samples, using the potentially infectious cut-off values estimated from the virus isolation to determine whether the recommended absentee time in the School Health and Safety *Act is* sufficient. ## Patient enrollment and treatment Patients with influenza-like symptoms (such as fever, sore throat, cough, sneeze, or general fatigue) who visited 13 outpatient clinics in 11 prefectures of Japan (Hokkaido, Niigata, Gunma, Tokyo, Chiba, Shizuoka, Kyoto, Nara, Yamaguchi, Kumamoto, and Nagasaki) between 2013 to 2020 were enrolled in this study. First, patients were screened using influenza rapid diagnostic test (RDT) kits (QuickNavi-Flu + RSV™; Denka Co., Ltd, Tokyo, Japan). Written informed consent was obtained from patients with influenza or their guardians before enrolment. Then the clinicians collected the first sample, and prescribed one of the five drugs (baloxavir, laninamivir, oseltamivir, peramivir, or zanamivir) based on the advice of clinicians and/or the preference of patients or their guardians. However, due to the small number of patients treated with peramivir, those who received this medication were not included in the analysis. The dosage of the four drugs followed the standard prescription course recommended in Japan (Additional file 1: Table S1) [2]. ## Collection of specimens and clinical data Nasopharyngeal swabs or nasal discharges were collected from the patients in pairs at the first clinic visit before the start of treatment (pre-treatment) and at the second visit 4–5 days after the first visit (post-treatment). Clinicians recorded the patients’ age, sex, vaccination status, and illness onset dates during the first and second clinic visits. Samples were placed in viral transport media and frozen at − 20 °C at the study sites. Then, the samples were sent to Niigata University (Niigata, Japan) and stored at − 80 °C for further virologic examination. ## Quantitative real-time PCR for viral RNA shedding measurement Viral RNA was directly extracted from the clinical samples collected during $\frac{2013}{2014}$ and $\frac{2018}{2019}$ season, using an Extragen II—DNA/RNA extraction kit (Tosoh Co., Ltd, Tokyo, Japan), and those collected in $\frac{2019}{2020}$ season using QIAamp Viral RNA Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions [14]. Viral RNA was then transcribed into complementary DNA (cDNA) using the Uni12 and Uni11 influenza A and B generic primers (Additional file 1: Methods) [14, 20]. Quantitative real-time PCR (RT-qPCR) targeting the M gene using TaqMan probes was carried out for the pre-and post-treatment clinical samples to detect viral RNA shedding of influenza A or B (Additional file 1: Methods). The detection limit was 0.447 log10 copies/µL (2.86 copies/µL) for influenza A and 0.462 log10 copies/µL (2.9 copies/µL) for influenza B [19]. ## Viral clearance calculation The daily viral reduction (viral clearance) in each patient was calculated from the viral RNA shedding in the paired first and second samples as follows:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Daily \,viral\, reduction=\frac{1}{t}\mathit{ln}\left(\frac{{\nu }_{0}}{{\nu }_{t}}\right)$$\end{document}Dailyviralreduction=1tlnν0νtwhere t is the number of days between the first and second visit, v0 and vt stand for the viral RNA shedding at the first (pre-treatment) and second visits (post-treatment), respectively [21]. ## Virus isolation to detect emergent NA/H275Y variant and to assess potential viral infectivity Clinical samples (100 μL) were inoculated in confluent Madin-Darby canine kidney (MDCK) cells during the $\frac{2013}{2014}$ and $\frac{2018}{2019}$ seasons and SIAT-MDCK cells in $\frac{2019}{2020}$ season propagated in 48-well plates to isolate the influenza viruses. Globally from 2018, isolating influenza A/H3N2 from MDCK cells became difficult; therefore, we changed the cells to MDCK-SIAT 1 that can proliferate A/H3N2 more easily [22, 23]. The 48-well plates were then incubated at 34 °C with $5\%$ CO2 and observed daily for 5 days to detect the specific cytopathic effect (CPE) [24]. In addition, the viral isolates were used to detect NA/H275Y variant in A/H1N1pdm09 in the first and second visit samples. Although there is a possibility that viruses with low fitness, such as antiviral-resistant viruses, may be lost during the virus isolation, we assumed that the virus isolation is useful to see whether the measured viral RNA shedding contains active viral particles. Thus, the positivity or negativity of the viral isolation was used to assess potential viral infectivity in the concordant clinical samples with their viral RNA shedding [25]. ## Screening of the NA/H275Y and PA/I38T variants by cycling probe RT-PCR assay For the rapid detection of the NA/H275Y variant in A/H1N1pdm09, after RNA extraction, a cycling probe real-time PCR developed by our group was implemented on virus isolates for both pre- and post-treatment samples as previously reported [26]. For screening PA/I38T variants in both A/H1N1pdm09 and A/H3N2, a different set of cycling probe real-time PCR assay targeting at PA gene was implemented on the pre- and post-treatment clinical samples, as previously reported [14, 27]. ## Genetic analysis to confirm NAIs or baloxavir-resistant variants Genetic sequencing was conducted using the Sanger method to confirm the presence of amino acid substitutions in NA and PA genes that confer resistance to baloxavir or NAIs (Additional file 1: Methods) [14, 27, 28]. Genetic sequencing of NA gene was conducted on all isolates generated on MDCK or MDCK-SIAT 1 cells throughout the study period, and that of PA gene on all clinical samples collected between $\frac{2018}{2019}$ and $\frac{2019}{2020}$ seasons [14, 27, 28]. ## Analysis of patient characteristics Patient characteristics were analyzed as follows: age group (0–5 years, 6–18 years, ≥ 19 years), sex (male or female), treatment (baloxavir, laninamivir, oseltamivir, or zanamivir), influenza vaccination status (unvaccinated or vaccinated), drug resistance substitution (NA/H275Y or PA variants), viral RNA shedding at the first and second visits, interval time (from onset to first and second visits), all divided for analysis by influenza A or B. For the variables under investigation, the mean ± standard deviation (SD), median (interquartile range [IQR]), and/or frequency (%) were described. Student’s t-test, χ2 test, and Mann–Whitney U tests were used for the statistical analysis. All statistical analyses in this study were performed using EZR version 1.54 (Saitama Medical Center, Jichi Medical University, Japan) [29]. A two-sided p-value of less than 0.05 was considered statistically significant. ## Viral clearance between influenza A and B The median values of daily viral reduction (i.e., viral clearance) were compared in the relevant categories of age groups, treatment groups, and influenza vaccination status using the Mann–Whitney U test to compare the difference between influenza A and B. Note that PA variants were detected only for influenza A, so the viral clearance was compared between those with or without emergent PA variants in influenza A, but not for influenza B. ## Univariate analysis of viral clearance by various factors The median value of viral clearance was compared among age groups (0–5 years, 6–18 years, ≥ 19 years), treatment groups (baloxavir, laninamivir, oseltamivir, or zanamivir), vaccination status (unvaccinated or vaccinated), and the emergence of PA variants (yes or no), all divided by influenza A or B for univariate analysis. Mann–Whitney test was used to compare two groups, and the Kruskal–Wallis test was used to compare three or more groups. Bonferroni correction was applied as a post hoc test for each pair after the Kruskal–Wallis test. ## Multivariate analysis of viral clearance The association between viral clearance and type of influenza (categorical variable), age group (categorical variable), treatment (categorical variable), vaccination status (categorical variable), the emergence of PA variants (categorical variable), and interval time from onset to first visit (continuous variable) were assessed using multiple linear regression analysis. We used the forced entry method for all examined variables (potential confounders) in the multivariate model. The maximum likelihood method was used for inference, and the estimates, including adjusted linear regression β coefficients, and standard error (SE), t-value, and p-value, were estimated. Goodness-of-fit was assessed by estimating the adjusted coefficient of determination (R2), F-value, and variance inflation factor (VIF). ## Assessment of residual viral RNA shedding at the time of returning to school We analyzed patients' residual viral RNA shedding and potential viral infectivity after 5 days of onset. The onset date was regarded as day 0. We used the receiver operator characteristic (ROC) curve to calculate the cut-off values for viral RNA shedding of potentially infectious influenza A or B viruses using EZR version 1.54 [29]. Viral RNA shedding (log10 copies/µL) of all clinical samples collected (first and second visits) were listed with their virus isolation status (yes or no) to estimate the potentially infectious cut-off value. The area under the curve (AUC) of the ROC curve was used to analyze the accuracy of viral RNA shedding to assess potential viral infectivity. AUC value above 0.80 is assessed as a test with good accuracy. The viral RNA shedding in the second visit samples that exceeded the cut-off value was regarded as potentially infectious. We divided the patients according to age, influenza type, and treatment. We calculated the proportion of patients with a detectable viral RNA shedding over the patients who had a second sampling five days after the onset (between 5 to 13 days after onset) in each group. Additionally, the proportion of potential infective virus for patients with and without PA variants was calculated in patients infected with influenza A who received baloxavir. Fisher’s exact test was implemented on two by two or two-by-multiple tables to evaluate proportions, and Bonferroni correction was implemented to adjust p-values for two by two pairs as a post hoc test for multiple comparisons. ## Ethics approval This study was approved by the Ethics Committee of Niigata University (no. # 1347, 2018–0317). The present study was conducted following the Declaration of Helsinki (revised in 2013). Written informed consent was obtained from all patients and legal guardians of minors before enrollment. ## Characteristics of the patients at baseline A total of 715 patients at baseline with paired first and second visits were enrolled, and 134 patients were excluded for the reason described in Fig. 1.Fig. 1Flowchart Of the 581 patients analyzed, 465 ($80.0\%$) were positive for influenza A (251 A/H1N1pdm09, 199 A/H3N2, and 15 subtypes unspecified) and 116 ($20.0\%$) were influenza B (Table 1). Over half of the patients were male ($54.6\%$, $\frac{317}{581}$), and the majority were 6–18 years old ($75.7\%$, $\frac{440}{581}$). Among the treatment groups, baloxavir ($39.2\%$, $\frac{228}{581}$), and oseltamivir ($40.1\%$, $\frac{233}{581}$) were prescribed to more patients than laninamivir ($11.7\%$, $\frac{68}{581}$) and zanamivir ($9.0\%$, $\frac{52}{581}$). In the vaccination group, over half were unvaccinated patients ($54.4\%$, $\frac{316}{581}$). There were no patients found to have NAI-resistant variant viruses (NA/H275Y) after oseltamivir treatment, but 21 ($4.5\%$) patients developed baloxavir-resistant variants viruses (PA/I38T, I38M, I38K, E23K, and E119Q) in the clinical samples of influenza A (9 A/H1N1pdm09 and 12 A/H3N2) after baloxavir treatment [14, 27, 28]. No PA variants were detected in influenza B-infected patients. Patients with PA variants (median 9.67 years [IQR 5.78 years]) were almost the same age as those without PA variants (median 10.33 years [IQR 4.17 years]). The proportion of influenza B infections was higher than influenza A infections among the unvaccinated ($69.8\%$ versus $50.5\%$) patients, but vice versa among the vaccinated ($30.2\%$ versus $49.5\%$; $p \leq 0.001$) (Table 1). The average viral RNA shedding at the first visit in influenza A infected patients (average ± SD; 4.2 ± 1.3 log10 copies/µL) was higher than in influenza B infected patients (3.5 ± 0.9 log10 copies/µL) ($p \leq 0.001$), but that of second visit was similar between patients infected with influenza A (1.0 ± 1.4 log10 copies/µL) and B (1.0 ± 1.3 log10 copies/µL) ($$p \leq 0.900$$). The interval time from onset to first visit in patients was a median of 1.0 days (IQR 0.0–1.0 days) for both influenza A and B but was statistically longer in influenza B ($$p \leq 0.008$$) (Table 1). The interval time from the onset to the second visit in patients was similar for influenza A and B, with a median of 5.0 days without statistical significance (IQR 4.0–5.0 days) ($$p \leq 0.966$$). The remaining baseline characteristics did not differ among the groups. Table 1Characteristics of the patients at baseline included in this studyCharacteristicsInfluenza AInfluenza Bpn = 465n = 116Age, average ± SD (years)12.5 ± 10.811.7 ± 10.80.509aAge group, n (%)0.175b 0–5 years69 ($14.8\%$)14 ($12.1\%$) 6–18 years345 ($74.2\%$)95 ($81.9\%$) ≥ 19 years51 ($11.0\%$)7 ($6.0\%$)Gender, n (%)0.104b Male262 ($56.3\%$)55 ($47.4\%$) Female203 ($43.7\%$)61 ($52.6\%$)Treatment, n (%)0.126b Baloxavir189 ($40.6\%$)39 ($33.6\%$) Laninamivir58 ($12.5\%$)10 ($8.6\%$) Oseltamivir181 ($38.9\%$)52 ($44.8\%$) Zanamivir37 ($8.0\%$)15 ($12.9\%$)Vaccination status, n (%) < 0.001b Unvaccinated235 ($50.5\%$)81 ($69.8\%$) Vaccinated230 ($49.5\%$)35 ($30.2\%$)Drug resistance substitution, n (%) NA/H275Y0 ($0.0\%$)0 ($0.0\%$) PA variants21 ($4.5\%$)NAViral RNA shedding, average ± SD (log10 copies/µL) First visit4.2 ± 1.33.5 ± 0.9 < 0.001c Second Visit1.0 ± 1.41.0 ± 1.30.860aInterval time, Median (IQR) (day) From onset to first visit1 (0–1)1 (0–1)0.008d From onset to second visit5 (4–5)5 (4–5)0.966dSD, standard deviation; NA, not availableaStudent’s t testbChi-square testcWelch’s t testdMann-Whitney U test ## The difference in viral clearance between influenza A and B The median values of estimated viral clearance between influenza A and B were compared under patient age groups, treatment groups, vaccination status, and the emergence of PA variants (only for influenza A) by the Mann–Whitney U test (Table 2).Table 2Median viral clearance between influenza A and B infected patientsCharacteristicsInfluenza AInfluenza BpaMedian (IQR)(log10/day)Median (IQR)(log10/day)Age group 0–5 years0.56 (0.38–0.85)0.28 (0.18–0.69)0.053 6–18 years0.76 (0.51–1.06)0.65 (0.38–0.92)0.029 ≥ 19 years0.87 (0.61–1.01)0.65 (0.55–0.86)0.398Treatment Baloxavir0.81 (0.52–1.12)0.77 (0.38–1.04)0.440 Laninamivir0.76 (0.45–1.06)0.37 (0.29–0.56)0.014 Oseltamivir0.63 (0.44–0.93)0.64 (0.48–0.86)0.636 Zanamivir0.90 (0.65–1.08)0.55 (0.27–0.77)0.018Vaccination status Unvaccinated0.72 (0.49–1.00)0.63 (0.35–0.89)0.029 Vaccinated0.77 (0.49–1.06)0.65 (0.47–0.87)0.189PA variants No0.73 (0.48–1.01)NA < 0.001 Yes0.42 (0.28–0.56)NAIQR, interquartile range; NA, not availablea Mann–Whitney U test In the age groups, the viral clearance of patients infected with influenza A was significantly faster than that of patients infected with influenza B for 0–5 years old (median 0.56 log10/day [IQR 0.47 log10/day] versus median 0.28 log10/day [IQR 0.51 log10/day]; $$p \leq 0.053$$) and 6–18 years old (median 0.76 log10/day [IQR 0.55 log10/day] versus median 0.65 log10/day [IQR 0.54 log10/day]; $$p \leq 0.029$$), respectively, but the clearance in patients ≥ 19 years did not differ between influenza A and B (median 0.87 log10/day [IQR 0.40 log10/day] versus median 0.65 log10/day [IQR 0.31 log10/day]; $$p \leq 0.398$$). Patients with influenza A infection who received laninamivir (median 0.76 log10/day [IQR 0.61 log10/day] versus median 0.37 log10/day [IQR 0.27 log10/day]; $$p \leq 0.014$$) or zanamivir (median 0.90 log10/day [IQR 0.43 log10/day] versus median 0.55 log10/day [IQR 0.50 log10/day]; $$p \leq 0.018$$) had faster viral clearance than influenza B infected patients, no difference was found between influenza A and B infected patients who received baloxavir (median 0.81 log10/day [IQR 0.60 log10/day] versus median 0.77 log10/day [IQR 0.66 log10/day]; $$p \leq 0.440$$) and oseltamivir (median 0.63 log10/day [IQR 0.49 log10/day] versus median 0.64 log10/day [IQR 0.38 log10/day]; $$p \leq 0.636$$). Unvaccinated patients infected with influenza A demonstrated significantly faster viral clearance than that infected with influenza B (median 0.72 log10/day [IQR 0.51 log10/day] versus median 0.63 log10/day [IQR 0.54 log10/day]; $$p \leq 0.029$$); however, no difference was observed between the two in the vaccinated group (median 0.77 log10/day [IQR 0.57 log10/day] versus median 0.65 log10/day [IQR 0.40 log10/day]; $$p \leq 0.189$$). Patients who did not develop PA variants after baloxavir treatment demonstrated significantly faster viral clearance than patients with emergent PA variants (median 0.73 log10/day [IQR 0.53 log10/day] versus median 0.42 log10/day [IQR 0.28 log10/day]; $p \leq 0.001$) (Table 2). The viral clearance between patients with PA variants and those without were compared within influenza A but not with influenza B. Patients without PA variants analyzed here included all four treatment groups, not only the baloxavir treatment group. In addition, patients with PA variants (median age 9.67 years [IQR 5.78]) were slightly younger than those without PA variants (median age 10.33 years [IQR 4.17]) in influenza A, but no significant difference was observed. Thus, it is unlikely that the age group affected the slower viral clearance of patients who shed PA variants. ## Assessment of influenza viral clearance of patients by age group, treatment, vaccination, and the emergence of PA variants The association between viral clearance and factors such as age, treatment, vaccination status, or the emergence of PA variants (only for influenza A) was evaluated in patients infected with influenza A or B (Fig. 2).Fig. 2Comparison of influenza viral clearance by age, treatment, vaccination groups with or without PA variants. a and b; Age groups, c and d; treatment groups, e and f; influenza vaccination status, and g; emergence of PA variants. Emergence of PA variants was not analyzed for influenza B because of no detection. a–d were analyzed using Kruskal–Wallis test, and Bonferroni correction was applied as a post-hoc test for each pair; e–g were analyzed using Mann–Whitney test. The p-value or no significance in the upper right corner of each figure was determined using Kruskal–Wallis test or Mann–Whitney test. The p-value above the two connected groups in the figure was determined using Bonferroni correction. BA, baloxavir; LA, laninamivir; OS, oseltamivir; ZA, zanamivir; NS, not significant The median viral clearance of patients 0–5 years was significantly slower than that of patients 6–18 years ($$p \leq 0.003$$) and ≥ 19 years old ($$p \leq 0.019$$) in influenza A (Fig. 2A and Table 2). No significant difference was found in viral clearance among age groups in influenza B infected patients, maybe due to the smaller number of cases in influenza B (Fig. 2B and Table 1). The median viral clearance of baloxavir and zanamivir-treated patients was significantly faster than that of oseltamivir in influenza A ($$p \leq 0.007$$, and $$p \leq 0.016$$, respectively) (Fig. 2C). In influenza B, the viral clearance of all four treatment groups did not have a statistical difference (Fig. 2D). Vaccination status did not affect the viral clearance in influenza A-infected patients or influenza B (Fig. 2E, F). Patients with PA variants showed significantly slower viral clearance than those without influenza A ($p \leq 0.001$) (Fig. 2G). ## Multiple linear regression analysis of influenza viral clearance Multiple linear regression analysis was performed to determine the association between viral clearance and influenza type, age group, treatment, vaccination status, the emergence of PA variants, and interval time from onset to first visit (Table 3).Table 3Multiple linear regression analysis of influenza viral clearanceVariablesPartial regression coefficientaSEtpVIFType1.056 Influenza AReferenceNANANA Influenza B– 0.1340.044– 3.0670.002Age group1.194 0–5 yearsReferenceNANANA 6–18 years0.1550.0522.9850.003 ≥ 19 years0.1700.0712.4050.016Treatment1.234 BaloxavirReferenceNANANA Laninamivir– 0.1670.058– 2.8830.004 Oseltamivir– 0.1540.041– 3.777 < 0.001 Zanamivir– 0.0750.064–1.1710.242Vaccination status1.053 UnvaccinatedReferenceNANANA Vaccinated0.0040.0350.1030.918PA variants1.072 NoReferenceNANANA Yes– 0.4680.094– 4.965 < 0.001Interval time from onset to first visit0.0260.0260.9790.3281.009SE, standard error; VIF, variance inflation factor; NA, not availablea Adjusted R2 = 0.077; $F = 6.403$ *Multivariable analysis* showed that viral clearance of patients infected with influenza B was slower by the difference of 0.134 log10/day ($$p \leq 0.002$$) than that of influenza A. Viral clearance of 6–18 and ≥ 19 years patients were faster by the difference of 0.155 log10/day, ($$p \leq 0.003$$) and 0.170 log10/day ($$p \leq 0.016$$), respectively, than that of 0–5 years old. The viral clearance of laninamivir treated patients was 0.167 log10/day slower ($$p \leq 0.004$$), and oseltamivir-treated patients were 0.154 log10/day slower ($p \leq 0.001$) than that of baloxavir, respectively. In contrast, the viral clearance of zanamivir-treated patients was 0.075 slower without significance ($$p \leq 0.242$$). The viral clearance of vaccinated patients did not differ from unvaccinated patients ($$p \leq 0.918$$). The viral clearance of patients who shed PA variants was 0.468 log10/day slower than that without PA variants ($p \leq 0.001$). For interval time from onset to the first visit, the viral clearance increased by 0.026 log10/day but without significance ($$p \leq 0.328$$). ## Residual viral RNA shedding and potential infectivity after 5 days of symptom onset To assess the relationship between potential viral infectivity and viral RNA shedding, we first determined the cut-off values for the infectious viral RNA shedding by ROC curve based on the positivity or negativity of virus isolation compared to the viral RNA shedding in each sample. The patient age group of 6–18 years old was focused, and those 0–5 years and > 19 years old were excluded because patients were mainly concentrated in this age group ($\frac{440}{581}$, $75.7\%$). As a result, 690 samples (first and second visits) from 345 patients of influenza A and 190 samples (first and second visits) from 95 patients of influenza B collected throughout the study period were analyzed. The calculated cut-off values were 2.628 log10 copies/µL for influenza A and 1.886 log10 copies/µL for influenza B. The AUC of ROC curves shows that viral RNA shedding accurately assesses potential viral infectivity, 0.861 for influenza A and 0.836 for influenza B, respectively (Fig. 3).Fig. 3Receiver operating characteristic curves for assessment of CPE using viral RNA shedding. A total of 690 samples from 345 patients with influenza A and 190 samples from 95 patients with influenza B, aged 6–18 years were analyzed. a, b Represent Influenza A and Influenza B, respectively Next, for the analysis of residual RNA shedding and potential infectivity after five days of symptom onset, patients who had a sampling interval between the first and the second with < 5 days or > 14 days were excluded ($$n = 125$$, $28.4\%$). A total of 315 patients 6–18 years old were divided by treatment groups (baloxavir, laninamivir, oseltamivir, and zanamivir) and type of influenza (A or B), and the proportion of viral RNA shedding above the potentially infectious cut-off value in the second visit samples was calculated (Fig. 4). *In* general, patients infected with influenza B ($\frac{21}{66}$, $31.8\%$) showed a significantly higher rate of the potential infective virus than influenza A after 5 days of onset ($\frac{35}{249}$, $14.1\%$, $p \leq 0.001$) (Additional file 1: Table S2). Among the four treatment groups, laninamivir treated patients ($\frac{12}{42}$, $28.6\%$) showed a higher rate of the potential infective virus than that of zanamivir in influenza A ($\frac{0}{20}$, $0.0\%$, $$p \leq 0.037$$). Similarly, laninamivir treated patients ($\frac{4}{7}$, $57.1\%$) seemed to have a higher rate of the potential infective virus in influenza B compared to other treatment groups; however, statistical difference was not observed because of the small number of patients (Fig. 4 and Additional file 1: Table S2). As was expected from the univariate analysis, influenza A-infected patients who shed emergent PA variants ($\frac{8}{13}$, $61.5\%$) after baloxavir treatment showed significantly higher rates of the potential infective virus than those without PA variants ($\frac{6}{101}$, $5.9\%$, $p \leq 0.001$) (Fig. 5).Fig. 4Changes in viral RNA shedding in patients with influenza A and B after treatment. a and e Patients treated with baloxavir; b and f, patients treated with laninamivir; c and g, patients treated with oseltamivir; d and h, patients treated with zanamivir. The red solid line in each figure represents the paired samples that showed potential infectivity in the second visit collected between 5 to 13th days after symptom onset in the patient. The cut-off value for viral RNA shedding in influenza A and B was 2.628 log10 copies/µL and 1.886 log10 copies/µL, respectively. The solid gray line represents those with negative potential infectivity below the cut-off. The vertical red dotted line represents the fifth day after symptom onset. The red numeric numbers represent the rate of positive infectivity in the upper part and the corresponding percentage in the lower partFig. 5Changes in viral RNA shedding in baloxavir-treated patients with or without PA variants. a Patients with PA variants after baloxavir treatment; b patients without PA variants after baloxavir treatment. The solid red line in each figure represents the paired samples that showed potential infectivity in the second visit collected between the 5th to 13th days after the patient's symptom onset. The cut-off value for viral RNA shedding in influenza A was 2.628 log10 copies/µL. The solid gray line represents those with negative potential infectivity below the cut-off. The vertical red dotted line represents the fifth day after symptom onset. The red numeric numbers represent the rate of positive infectivity in the upper part, and the corresponding percentage in the lower part ## Discussion To the best of our knowledge, this is the first study that collectively compared the viral reduction between a cap-dependent endonuclease inhibitor (baloxavir), and three NAIs (laninamivir, oseltamivir, and zanamivir), against laboratory-confirmed influenza A and B. Multiple linear regression analysis showed that the viral clearance was faster in older (≥ 6 years) patients with influenza A infection and were treated with baloxavir, but it is prolonged with the emergence of PA variants that confer reduced susceptibility to baloxavir (Table 3). In the age group of 6–18 years, approximately 10–$30\%$ of patients possessed potential viral infectivity from 5 days, and onward of onset, and the laninamivir treatment groups had a higher rate than the other three treatment groups for influenza A, but these differences were not apparent for influenza B due to the small number of cases (Fig. 4). The patients with PA variants retained higher viral infectivity than those without PA variants in baloxavir-treated influenza A patients (Fig. 5). The viral clearance of baloxavir was faster than that of NAIs, especially for oseltamivir and laninamivir (Table 3). Similar to our findings, a previous network meta-analysis indicated that baloxavir was more efficacious in controlling the viral RNA shedding than NAIs [30]. However, almost all past studies have compared only baloxavir with oseltamivir but not with other NAIs. A phase 2 randomized control trial in adults showed that by one day after treatment, the decline in infectious virus titers of baloxavir (average 3.36 log10 TCID50/mL) was significantly higher than that of oseltamivir (average 1.76 log10 TCID50/mL), and the reduction in viral RNA shedding was also faster in the baloxavir group than in the oseltamivir groups [5]. Similar results were observed in other studies with both adults and children [6, 7]. The faster viral reduction by baloxavir compared to another NAIs, including laninamivir, and not only to oseltamivir, is novel. Laninamivir is a one-time inhalation drug licensed in Japan [2]. Comparative study on viral kinetics for laminamivir with other drugs has not been conducted. Koseki et al. reported that the frequency of clinical biphasic fever for laninamivir was 5.8 times more than zanamivir in children 5–18 years, which may reflect the slower viral clearance in laninamivir treated children [31]. We have demonstrated the similar viral clearance between baloxavir and zanamivir, but the reason remains unclear due to a lack of research. We found that patient age was positively associated with viral clearance; that is, younger patients had a slower daily virus reduction than older patients. This result may be because children generally have lower pre-existing influenza-specific antibodies than adults [32]. Similar to our findings, a previous study about viral shedding of influenza A, showed that children generally shed a similar amount of virus as adults, but had a longer overall duration and lower rate of decline than adults [33]. Previous studies have shown that the duration of virus shedding is longer in younger patients [8, 34, 35], and that the median viral shedding time of patients < 13 years (median 11 days) is longer than that of patients aged ≥ 13 years (median 7 days) [36]. Additional studies showed that younger children tend to shed greater quantities of influenza virus than older children [37]. These results suggest that younger patients shed more virus and experience a slower daily virus reduction than older patients. We found that the daily viral reduction (viral clearance) in patients infected with influenza A was faster than influenza B using multiple linear regression analysis (Table 3). We calculated viral clearance using the viral RNA shedding of patients collected at two points during the clinical course, as reported by Rath et al., who showed similar findings regarding the viral clearance of influenza B (median 0.88 log10/day), which was slower than oseltamivir sensitive influenza A/H1N1pdm09 (median 1.36 log10/day) after oseltamivir treatment [21]. However, our study demonstrated similar viral clearance between patients infected with influenza A and B after oseltamivir treatment in univariate analysis (Table 2). One possible reason was the difference in age composition between the influenza A and B infected patients. In oseltamivir treatment group, the proportion of patients aged 0–5 years ($30.9\%$) in influenza A infection was much higher than that of influenza B ($7.7\%$). Since the daily virus reduction was slower in younger patients, the difference in viral clearance between influenza A and B infected patients in univariate analysis was not significant. Since we have a relatively sufficient number of influenza B ($$n = 52$$) infected patients compared to influenza A ($$n = 181$$) for oseltamivir treatment group to draw statistical difference, another possible reason may be related to susceptibility to drugs between influenza A and influenza B. Previous studies have shown that the susceptibility against influenza B compared to A is low in NAIs, 4–15-fold reduction with zanamivir and 3–15-fold with laninamivir, and that with oseltamivir is much larger, 15–45-fold change [38, 39]. On the other hand, the susceptibility of influenza B to baloxavir was just fourfold lower than that of influenza A [40], presumably resulting in smaller difference in viral clearance between influenza A and B after baloxavir treatment. Herein, we found slower viral clearance in patients infected with PA variants viruses in both uni- and multivariable analyses (Tables 2 and 3, Fig. 3). Additionally, the rate of viral RNA shedding that showed potentially infective virus also supported the slower viral clearance in PA variants than those without (Fig. 5). The PA variants are reported to exhibit reduced susceptibility to baloxavir, and associated with a transient rise in virus titer and prolongation of virus detectability in patients according to the previous findings [12, 41–43]. One of our studies conducted during $\frac{2018}{2019}$ season demonstrated the emergence of PA/E23K and I38K/M/S/T variants in $13.5\%$ ($\frac{13}{96}$) of influenza A infected patients after baloxavir treatment, and the rebound of viral RNA was observed in $13.5\%$ ($\frac{2}{13}$) patients who shed the PA variants [14]. Thus, our results are compatible with the previous reports of delayed viral clearance when PA variants emerged after baloxavir treatment. In addition to PA variants, resistance variants of NAIs such as NA/H275Y should have a similar effect [10]. However, NA/H275Y variant was not detected in this study maybe because we used virus isolates to screen the NAI-resistant viruses. In some strains of influenza A/H1N1pdm09, the NA/H275Y substituted virus showed reduced viral fitness [44], in contrast to PA/I38T substitution that retained viral fitness relatively well, especially in the case of A/H3N2 [11, 45, 46]. This low viral fitness for NA/H275Y may be one of the reasons why we could not detect it in the second visit samples. Another reason can be the low viral RNA shedding in the second visit samples. As demonstrated by the ROC curve, the threshold of virus isolation was 2.628 log10 copies/µL for influenza A, but the average value for the viral RNA shedding at the second visit samples was much lower, 1.0 log10 copies/µL (Table 1). Thus, isolating influenza virus in the second visit samples became difficult, and resulted in no detection of NA/H275Y. On the contrary, we detected a total of 21 PA variants in the second visit samples not only due to relatively higher emergence of PA variant after baloxavir treatment, but this screening was directly done from the clinical samples using RT-PCR with a limit of detection of 0.301 log10 copies/µL for influenza A, more sensitive than the virus isolation [27]. Approximately 10–$30\%$ of children aged 6–18 years had potential infectivity of Additional file 1: Table S2). Additionally, laninamivir-treated patients may shed more infectious viruses than other treatment groups after home stay period in influenza A, although it was not statistically supported in influenza B due to the small number of patients. Our results suggested that the recommended home stay period designated by the School Health and Safety Act may not be sufficient to stop all viral transmission. The School Health and Safety Act in Japan states that children with influenza infection should stay home for at least six days after symptom onset [2, 19]. The purpose of this regulation is to stop transmitting influenza among children and to minimize the size of outbreaks at schools. This rule is applied to elementary schools, junior high schools, high schools, universities, and even workplaces for adults. A certain proportion of patients might remain infectious at the time of returning to school, but the majority of patients became non-infectious (70–$90\%$) (Additional file 1: Table S2), thus appropriate hygiene measurements at school such as wearing masks or frequent ventilation may help stop transmission from infectious patients. This study has certain limitations. Because there were only two clinical visits, it was impossible to determine the time when the viral RNA shedding was undetectable for the first time. Therefore, we assumed that the viral RNA shedding decreased unidirectionally between the first and second visits, which may cause the daily virus reduction to be slower than the actual situation. Second, the majority of patients had the second sample collection just one day before returning to school; therefore, the actual viral RNA shedding when patients presented to school may have been further reduced. Nevertheless, our study suggests that some patients shed the virus at a lower level at school. Finally, the small number of patients in several groups in the study (e.g., influenza B) compared to others may have affected the main results. Further studies with accumulated case numbers are critically needed to overcome these potential concerns. Measuring the viral RNA shedding has significant public health implications for controlling transmission via infections. This study verified the recommendations provided by the School Health and Safety Act in Japan and provided evidence for these regulations with regard to the return of children with influenza to school. *In* general, viral RNA shedding used to be not a major concern for clinicians, unless patients are in severe conditions or immunocompromised. However, after the emergence of coronavirus disease 2019 (COVID-19), it was revealed that the virus shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was longer than the symptomatic period [47, 48], and some patients even caused pre-symptomatic infections [49, 50]. This turned the clinicians to pay more attention to viral RNA shedding in respiratory infections to prevent spread to others. A previous study found that influenza viral RNA shedding is positively correlated with the presence of clinical symptoms [51]. 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--- title: The co-development of a linguistic and culturally tailored tele-retinopathy screening intervention for immigrants living with diabetes from China and African-Caribbean countries in Ottawa, Canada authors: - Valerie Umaefulam - Mackenzie Wilson - Marie Carole Boucher - Michael H. Brent - Maman Joyce Dogba - Olivia Drescher - Jeremy M. Grimshaw - Noah M. Ivers - John G. Lawrenson - Fabiana Lorencatto - David Maberley - Nicola McCleary - Sheena McHugh - Olivera Sutakovic - Kednapa Thavorn - Holly O. Witteman - Catherine Yu - Hao Cheng - Wei Han - Yu Hong - Balkissa Idrissa - Tina Leech - Joffré Malette - Isabelle Mongeon - Zawadi Mugisho - Marlyse Mbakop Nguebou - Sara Pabla - Siffan Rahman - Azaratou Samandoulougou - Hasina Visram - Richard You - Junqiang Zhao - Justin Presseau journal: BMC Health Services Research year: 2023 pmcid: PMC10054218 doi: 10.1186/s12913-023-09329-3 license: CC BY 4.0 --- # The co-development of a linguistic and culturally tailored tele-retinopathy screening intervention for immigrants living with diabetes from China and African-Caribbean countries in Ottawa, Canada ## Abstract ### Background Diabetic retinopathy is a sight-threatening ocular complication of diabetes. Screening is an effective way to reduce severe complications, but screening attendance rates are often low, particularly for newcomers and immigrants to Canada and people from cultural and linguistic minority groups. Building on previous work, in partnership with patient and health system stakeholders, we co-developed a linguistically and culturally tailored tele-retinopathy screening intervention for people living with diabetes who recently immigrated to Canada from either China or African-Caribbean countries. ### Methods Following an environmental scan of diabetes eye care pathways in Ottawa, we conducted co-development workshops using a nominal group technique to create and prioritize personas of individuals requiring screening and identify barriers to screening that each persona may face. Next, we used the Theoretical Domains Framework to categorize the barriers/enablers and then mapped these categories to potential evidence-informed behaviour change techniques. Finally with these techniques in mind, participants prioritized strategies and channels of delivery, developed intervention content, and clarified actions required by different actors to overcome anticipated intervention delivery barriers. ### Results We carried out iterative co-development workshops with Mandarin and French-speaking individuals living with diabetes (i.e., patients in the community) who immigrated to Canada from China and African-Caribbean countries ($$n = 13$$), patient partners ($$n = 7$$), and health system partners ($$n = 6$$) recruited from community health centres in Ottawa. Patients in the community co-development workshops were conducted in Mandarin or French. Together, we prioritized five barriers to attending diabetic retinopathy screening: language (TDF Domains: skills, social influences), retinopathy familiarity (knowledge, beliefs about consequences), physician barriers regarding communication for screening (social influences), lack of publicity about screening (knowledge, environmental context and resources), and fitting screening around other activities (environmental context and resources). The resulting intervention included the following behaviour change techniques to address prioritized local barriers: information about health consequence, providing instructions on how to attend screening, prompts/cues, adding objects to the environment, social support, and restructuring the social environment. Operationalized delivery channels incorporated language support, pre-booking screening and sending reminders, social support via social media and community champions, and providing using flyers and videos as delivery channels. ### Conclusion Working with intervention users and stakeholders, we co-developed a culturally and linguistically relevant tele-retinopathy intervention to address barriers to attending diabetic retinopathy screening and increase uptake among two under-served groups. ### Supplementary Information The online version contains supplementary material available at 10.1186/s12913-023-09329-3. ## Background Diabetic retinopathy is a leading cause of preventable blindness in working-aged Canadians [1] and worldwide [2, 3]. Retinopathy involves microvascular damage to the retina that leads to swelling of the central retina and abnormal blood vessel growth that can lead to vision loss if not detected early and treated [4]. Early diagnosis and treatment are effective in preventing vision loss associated with diabetes. Canadian clinical guidelines recommend yearly diabetic retinopathy screening (DRS) for people living with diabetes to reduce the risk and progression of vision loss [5]. Screening for diabetic retinopathy is one of the most effective and least costly ways to reduce severe complications associated with this condition [6]. However, diabetic retinopathy screening rates are low across Canada. For example, in a teleophthalmology project across 5 provinces in Canada, over $68\%$ of the study’s cohort of individuals living with diabetes had not attended screening in the last year, and almost a third never had [7]. Furthermore, diabetic retinopathy screening rates are often lower among cultural and linguistic minority groups [8], and among newcomers to Canada, including people arriving from China, Africa, and the Caribbean; groups at higher risk of developing diabetes complications [4]. The 2021 *Canadian census* showed that $21.9\%$ of the Canadian population were foreign-born, and recent newcomers to Canada represented $3.5\%$ of the total population [9]. In the capital city of Canada (Ottawa), a $25\%$ sample of census respondents showed that $17\%$ residents had immigrated from Africa and $48\%$ from Asia [10]. Those immigrating from Asia were predominantly from China, making up $17\%$ of the population [10]. Linguistically, approximately $65\%$ of the immigrant population’s mother tongue is Mandarin and $8\%$ speak French as their mother tongue in Ottawa [11]. Tele-retinopathy screening is a potentially useful way to deliver and improve access to diabetes eye care [12, 13]. Tele-retinopathy screening involves capturing, securely transmitting, and remotely grading retinal digital images, and referring individuals living with diabetes by eye specialists for further care [14]. There is limited work about tele-retinopathy screening conducted in Canada amongst key subgroups with ethnocultural and linguistic minority groups. The present study builds on our foundational research and studies investigating barriers and enablers of DRS attendance among newcomers and immigrants to Canada from China (Mandarin-speaking) and African and Caribbean (French-speaking) countries [15]. Also, the current evidence base is relatively silent on interventions targeting specific population groups [16]. Our work has demonstrated that immigrants face specific barriers and enablers that likely need to be addressed to create culturally sensitive and effective screening programs for these groups. In a study conducted with newcomers and immigrants to Canada from China and African-Caribbean countries living with diabetes, several barriers were identified and prioritized to help these individuals get their eyes screened [15]. Some of these barriers included: access to retinopathy screening itself, language barriers, lack of knowledge about diabetic retinopathy, fears about screening harming eyes, and other barriers, including remembering to get eyes screened, lack of transparency about costs, and family and healthcare provider influences [15]. Lack of access to DRS is a clear barrier, and tele-retinopathy screening is a promising and cost-effective solution [17]. However, improving access and providing tele-retinopathy screening alone will not ensure newcomers and immigrants attend. While tele-retinopathy screening addresses access-related barriers, additional behaviour change and implementation strategies are needed to address other barriers related to the uptake of services. These strategies need to be co-developed with communities and the health services surrounding them and informed by which strategies have already been shown to be effective [18]. Our overarching aim was to co-develop, with patient and health system stakeholders, a linguistically- and culturally relevant tele-retinopathy screening intervention for immigrants to Canada from China and African-Caribbean countries. Here, we aim to describe the systematic development of an intervention to improve DRS attendance informed by theory, evidence and patient and stakeholder involvement. ## Design Our overall approach is largely consistent with O’Cathain et al. ’s [19] broad taxonomy of approaches for developing interventions, which highlights eight categories of approaches to intervention development. Among the identified approaches, we partnered with those who will engage in the intervention; took a population centered approach of the views of those engaging in the intervention; used evidence and theory; prioritising real-world implementation; used a systematic development process; developed an approach tailored to the given intervention; and combined components into the intervention [19]. To operationalise these approaches, we combined a behaviour change theory-based approach to intervention development with a co-development process involving patients and healthcare system stakeholders. Our overarching theoretical approach was rooted in French et al. ’s [20] process model for developing theory-based behaviour change interventions, i.e., Who, needs to do what, differently; identify barriers and enablers to be addressed; identify potential behaviour change techniques to overcome the barriers and enhance the enablers; and determine how behaviour change be measured and understood. Our co-development process was rooted in the Framework of User-Centred Design [21], which emphasizes iterative development with those for whom an intervention is developed and underscores three concepts: understand users, develop and refine intervention prototypes, and observe users’ interactions with the prototype. User-centred (human-centered) design is an umbrella term of many design approaches [22]. We sought to co-develop the intervention, sharing power and decisional authority with patient partners and service users while being realistic about health systems constraints and drawing on evidence wherever available. We sought to use a theory-based approach to ensure that the intervention could best draw from what is already known in the extent literature about factors that impact on DRS attendance specifically and behaviour change generally. This was also done to ensure that future iterations and applications of this intervention could draw from the benefits of theory, including careful description of components using agreed terminology and drawing from evidence and theory supporting the links between specific barriers/enablers and fit for purpose solutions. We sought to use a co-development process to recognise the importance that any intervention developed has the best chance of being useful and effective if groups who would engage in the intervention have a hand in informing its content. The intervention was reported according to guidance from the TIDieR checklist (Additional file 1). ## Participants The research team consisted of the researchers, patients in the community, health system stakeholders, and patient partners. ## Patients in the community We aimed to recruit two groups of 8–10 patients living with diabetes in the city of Ottawa (Canada) from China whose mother tongue is Mandarin or from African or Caribbean countries whose mother tongue is French, over 18 years of age, who had immigrated to Canada within the past 20 years. Prospective participants were invited to take part in a series of intervention co-development workshops conducted in Mandarin or French (virtually due to COVID-19 restrictions). We excluded those who spoke Cantonese but not Mandarin or French Creole to ensure planned workshops would be conducted in one primary language. We leveraged our professional networks via community health centres in Ottawa to engage interested participants. To recruit patients in the community, we used direct emails, information sheets, social media posts to Twitter and Facebook, poster shared via our networks, and reached out to publicly identifiable patient groups catering to these communities. Recruitment materials were shared with community organizations and distributed to their membership on behalf of the study team to enable interested participants to self-refer to the study team. Our target sample size is consistent with Nominal Group Technique methods that informed our workshop process [23, 24] and consistent with recommendations that co-development groups include 6–12 participants to enable participants space to share their views while providing sufficient diversity [25]. ## Health system stakeholders We sought to include 6–12 individuals involved in delivering care for patients with diabetes in Ottawa, especially for newcomers and/or immigrants to Canada, to join a health system partner Local Advisory Group (LAG). We invited primary care physicians, nurse practitioners, primary care and community health centre administrators, diabetes educators, and other relevant health system stakeholders involved in providing diabetes care or familiar with the use of tele-retinopathy screening. We used posters, email invitations, and information sheets to allow interested participants to self-refer to the study team. ## Patient partners We sought to form two groups of 2–4 adults living with diabetes (or their family members) from China whose mother tongue is Mandarin or from African or Caribbean countries whose mother tongue is French who could bring their lived expertise and experience with diabetes to inform the development of the intervention. We sought individuals who had a connection with their local community in Ottawa and/or had key role within the community (such as community leaders or facilitators), and who were at least bilingual (English/French or English/Mandarin). We reached out to Diabetes Action Canada’s patient circles and our professional networks in Ottawa to identity potential patient partners. We used posters, information sheets, and emails encourage interested participants to self-refer to the study team. ## Intervention co-development workshops We held six co-development sessions with patients in the community (3 workshops per group), patient partners (1 workshop per group), and health system partners (2 workshops). We conducted co-development sessions with patients in the community and patient partners using the Nominal Group Technique (NGT) [23, 24] to develop the intervention and resources. Materials for workshops with patients in the community were translated into Mandarin and French. The NGT is commonly used for idea generating, problem-solving, and consensus-building, and provides an opportunity to include the “voice” of all participants and democratized ideas. We conducted all workshops online (i.e., Zoom), each lasting about two hours. Detailed steps of the NGT-informed patient co-development workshops are presented in Additional file 2. Workshops with health system partners utilized prompts informed by Action, Actor, Context, Target, Time – (AACTT) framework [26] to clarify changes in practice implied by intervention activities, and the Theoretical Domains Framework (TDF) [27–29] to anticipate barriers to intervention delivery from the perspective of each stakeholder’s role and responsibilities. The AACTT framework used for pinning down the range of the details of a specific behaviour, focusing on specifying who needs to do what differently, when and where. Specifying the relevant AACTTs provides a basis for more specific assessment of barriers and enablers to engaging in these AACTTs. The TDF is a framework often used to assess barriers and enablers to engaging in a given behaviour, and reflects a synthesis of constructs of 33 theories of behaviours into 14 overarching domains. ## Language of co-development workshops Patients in the community co-development workshops were conducted in Mandarin and French and facilitated by an individual fluent in Mandarin (JZ) or French (MMN). The patient partner co-development workshop was conducted in English and co-facilitated by an individual fluent in Mandarin or French. The health system partner co-development workshops were conducted in English. The Mandarin-speaking community patient group named themselves the “Chinese group”, while the French-speaking patients called themselves the “French group”. As such, these terms will be used to refer to the two groups in this paper. Table 1 describes activities that occurred within and between workshops. Details on how the data from each workshop informed subsequent workshops and intervention development is included in the ‘post-workshop activity’ column of Table 1.Table 1Workshop objectives, activities and post workshop activitiesWorkshop labelNumber of WorkshopsWorkshop ObjectivesWorkshop ActivitiesPost Workshop ActivitiesMonth 1:Patients in the community co-development workshop 12 (1in Mandarin, 1 in French)Project Step 2—Building of personas of individuals who require diabetic retinopathy screeningDeveloped 3–4 personas using Nominal Group Technique (NGT)Data Type: PersonasResearch team and patient partners prepared cards containing barriers/enablers to DRS based on personasMonth 2: Patients in the community co-development workshop 22 (1in Mandarin, 1 in French)Project Step 3 – Identifying and prioritizing barriers/enablers for attending tele-retinopathy screeningGenerated and prioritized barriers/enablers to attending screening based on personas using NGTData type: Ranking of barriers/enablersResearch team and patient partners mapped literature based BCTs to prioritized barriers/enablers using meta-analytic evidence from Cochrane reviewMonth 3: Patients in the community co-development workshop 32 (1in Mandarin, 1 in French)Project Step 4 – Prioritizing and operationalizing solutions to barriers/enablersUsing NGT, brainstormed, discussed, prioritized, and described how each persona could receive the strategiesData Type: Ranking of StrategiesResearch team developed a draft intervention to inform workshop discussions with health system partners and prototyping resourcesMonth 4: Health system partner co-development workshop 11Project Step 5 – Anticipate delivery barriers to inform further patient partner co-developmentUsing the Action, Actor, Context, Target, Time – (AACTT) framework, described who would need to do what differently to enact the interventionData Type: Workshop notesResearch team, patient, and health system partners, developed draft resources to operationalize the prioritized strategies, emphasizing content and clarityMonth 5–8: Patient partner co-development workshop4 (4 for each group)Project Step 6 – Optimize intervention contentUsing NGT, shared suggestions for optimizing the content of resources and the care pathway for the interventionData Type: Workshop NotesThe research team summarized the intervention process and optimized resourcesMonth 9: Health system partner co-development workshop 21Project Step 7 –Optimize deliveryUsing AACTT and TDF, clarified any remaining anticipated barriers and developed implementation solutions to address themData Type: Workshop NotesThe research team produced the working version of the tele-retinopathy screening intervention ## Iterative project steps Figure 1 summarizes the project steps and participants involved. Fig. 1Project steps and participants involved ## Step 1: Environmental Scan We conducted an environmental scan to generate a preliminary map of the available diabetes programs and the associated care pathways for eye screening available for individuals with diabetes in Ottawa. We used a structured online search followed by discussion with our health system partners to identify programs that were discoverable to people living with diabetes [30]. We assumed the Google Canada search engine is one of the main approaches prospective patients would use to identify and connect with diabetes eye care programs on their own. We conducted a search on June 12, 2021 and reviewed the top 10 Google search results (1st page of results) for each search that provided information about the programs available in Ottawa. We used a combination of search terms including “Diabetes, retinopathy screening, and Ottawa” (Additional file 3). We included search outputs that mentioned diabetes and eye screening programs offered in Ottawa. Discussion with our health system partners served to fill any gaps in programs identified online to help develop a more comprehensive description of diabetes eye care programs and pathways in the city. An understanding of the geographic landscape of diabetes eye care situated the project. It enabled the identification of possible sites for conducting a community-based tele-retinopathy screening intervention for immigrants from China and Africa and the Caribbean countries in Ottawa, Canada. ## Step 2: Patients in the community co-development workshop 1 In the first co-development workshop, we co-developed personas to understand barriers to screening better. We presented examples of personas to the patient groups to support their creation of additional personas. The sociodemographic factors included in the example personas were informed by previous DRS work with ethnocultural groups in Ottawa [15] and the sociodemographic factors associated with the risk of diabetic retinopathy detected by a tele-ophthalmology program in Toronto, Canada: language, ethnic background, citizenship status, education level, household income and housing situation [31]. At the end of the first workshop, three [3] personas were generated in each group to cover known barriers/enablers to attending screening in each group. ## Step 3: Patients in the community co-development workshop 2 At the second workshop, participants were provided with examples of barriers/enablers to DRS previously identified in the literature and from previous work with the same population [15, 32]. Participants brainstormed any additional barriers/enablers relevant to attending tele-retinopathy screening for each persona created in the first workshop and prioritized the barriers/enablers for attending screening. At the end of the second workshop, five [5] barriers relevant to all personas were prioritized in each group (Additional File 2). Participants did not prioritize the barriers indicated by the same population in our previous work [15]. Following the second co-development workshop, recognizing that barriers to screening may not limited to a top five identified in a workshop, the research team (researchers and patient partners) decided to draw on literature on barriers to screening attendance prioritized by the same population in a previous study [15] to complement the barriers of focus of the intervention. All prioritized solutions generated from the patients in the community workshops were incorporated and operationalized in the intervention. For example, the solution, “The doctor must encourage patients to be tested and then make reminders by email (doctor's assistant) or via telephone messaging” was included in the intervention by providing prompts/cues to patients to attend DRS. ## Step 4: Patients in the community co-development workshop 3 Before the third co-development workshop with patients in the community, the research team matched the barriers to attending DRS identified in patient co-development workshop 2 to domains from the TDF and potential effective Behaviour Change Techniques (BCT) most likely to target the barriers identified in a Cochrane review that identified effective BCTs associated with greater DRS attendance for patients and health care providers [16]. BCTs are strategies that help to change the health behaviours of individuals [20]. First, we summarized and combined similar barriers generated from the French and Chinese patients in the community workshop groups to focus on five distinct barriers that the intervention would address (there were no key barriers specific to only one group). Secondly, we identified a long list of BCTs that are evidenced to address specific barriers (TDF-domains) informed by the online Theory and Techniques Tool [33]. This tool clarifies which BCTs may be best suited to address which TDF-informed barriers and enablers (and which are not well suited or have inconclusive links), providing a basis for selecting BCTs fit-for-purpose to address prioritized barriers. We focused on BCTs with established links in this tool. Thirdly, from the long list, we selected BCTs reported in the Cochrane review [16] that were more likely to be effective in increasing diabetic retinopathy screening attendance to create a short list of BCTs. We then created a list of potential strategies and channels of delivery most likely to be effective for each population group (where delivered, who delivered, how delivered). This process yielded a set of potential behaviour change strategies for promoting diabetic retinopathy screening attendance in both patient groups. In the third co-development workshop, participants were presented with the personas, prioritized barriers, and proposed BCTs (simplified using plain language). This provided the foundation for discussions on how to operationalize the BCTs meaningfully. We provided examples of how BCTs, such as “information about health consequences”, could be delivered based on consultation with our patient partners. Patients in the community used these examples to brainstorm, generate, and prioritize channels of delivery i.e., who should provide the information and instruction, how, where, using what resources, and how often. At the end of this co-development workshop, we prioritized solutions to DRS barriers (Additional file 2) and produced a draft intervention to inform prototyping resources and health-system stakeholder discussions. The three “Patients in the community” workshops were conducted in French and Mandarin. ## Step 5: Health system partners co-development workshop 1 We conducted the first workshop with health system partners to identify any practice changes needed to deliver the intervention, who would be involved, and anticipate barriers to its implementation. We began by presenting DRS screening rate data, introducing tele-retinopathy screening (process, cost-effectiveness) and personas, barriers, and initial solutions from Step 2 & 3. We asked participants to describe (using the Action, Actor, Context, Target, Time – AACTT framework) [26] who would need to do what differently to deliver the intervention as described, and whether any alterations would enhance the feasibility of delivery. We focused on clarifying practical considerations such as, how to invite individuals living with diabetes to attend tele-retinopathy screening, feasible community delivery settings for screening, and exploring referral for screening options. At the end of this phase, we identified solutions that could be addressed within the health system and anticipated delivery barriers to inform further patient partner and health system co-development. ## Step 6: Patient partner co-development workshop Between phases, the research team (researchers, patient partners, and health system partners) developed draft resources to operationalize the prioritized strategies identified during the patient in the community workshops. The patient partner co-development workshops occurred over four meetings. The proposed intervention strategy was presented to the patient partners, and they identified gaps in the intervention and proposed solutions. They identified and developed the content to be included in resources, shared their suggestions for additional resources, and ensured clarity of the content. We conducted the meetings with the French and Chinese groups separately. We used NGT to ensure that all patient partners could provide their input and changes to the various aspects of the intervention. For instance, changes to the content in the resources were made during the meetings in real time. At each meeting with the patient partners, there was a formal consensus process on decisions made. By the end of this co-development phase, we reached agreement on the resources to develop, its content, format, prototypes of resources, and mode and settings for delivery. This was presented to the health system partners in a final workshop. ## Step 7: Health system partners co-development workshop 2 The research team presented the intervention and optimized resources based on suggestions from previous steps. Health system partners identified any remaining anticipated barriers and develop implementation solutions to address them. Patient partners were also invited and attended this workshop to ensure patient perspectives were included. At the end of this co-development workshop, we had a co-developed tele-retinopathy screening intervention optimized as best as could be anticipated for delivery. ## Data collection and analysis Data collection, analysis, and development of the tele-retinopathy screening intervention were iterative, i.e., data from each step informed the next step. For example, following each workshop, data were analyzed, interpreted, and findings informed both the content of subsequent workshops and intervention development. ## Environmental scan We grouped similar programs into service categories and locations, which included 1) Diabetes service delivery and 2) Diabetes eye care service delivery. We summarized discussions with the health system partners and combined information provided with data from the Google search. The environmental scan notes were shared with our health system partners for further feedback and input. We identified that in 2021, there was no specific program for diabetes eye-care operating at any Community Health Centres (CHC) in Ottawa. Central intake to diabetes education programs was offered at locations across Ottawa. The programs were often provided in various languages including French and Mandarin and were open to self-referral and physician referral [34, 35]. Individuals with diabetes could access retinopathy screening either via self-referral to an optometrist or referral from a primary care practitioner to an optometrist or ophthalmologist. From our scan, there was no pathway specifically available to persons immigrating to Canada from China and African-Caribbean countries for diabetic retinopathy screening in Ottawa. Health system partners indicated that health practitioners typically referred patients to optometrists that are conveniently located for patients. Additionally, they mentioned that some health practitioners chose to send patients to places that have both an optometrist and ophthalmologist but, patients generally made the final decision on whom to consult. ## Patients in the community co-development workshops Using the NGT, the co-development workshops yielded rapidly generated results. Data on the sum of scores for each idea generated and voting frequency informed the ranked priority based on each of these measurements for each group. Participants provided one or more solutions for each persona across the five barriers from the previous sessions. Responses to the solutions generated for the five barriers were collated and each participant assigned a score for the preferred solutions/channels of delivery. The total scores for each aspect were calculated, and the top-ranked were prioritized (Additional file 2). Following each session, a summary of the priority list was generated and presented to participants for feedback. Audio recordings of the group sessions provided insight into the intricacies, context, and rationale with which group consensus was achieved and was used to back-check the data utilized. ## Patient partners and health system partners co-development workshops The patient and health system partners co-development workshops were audio recorded. We summarized the workshop discussions and shared the abridged notes with patient and health system partners for feedback. In addition, we verified their input on the resources developed, roles and behaviours for the implementation of the proposed intervention, and decisions towards operationalization of the solutions and channels of delivery generated. ## Patients in the community co-development workshop Patients in the community contributed to three co-development workshops conducted from November 2021 to January 2022. Participants representing African-Caribbean ($$n = 6$$) and Chinese ($$n = 7$$) immigrants to Canada were involved in all three different co-development workshops. The Chinese group was more alike due to similarities in culture, whereas the French group was more heterogeneous and consisted of individuals from different African and Caribbean countries with varying cultures but sharing a common language. Participants demographic data are presented in Table 2.Table 2Patients in the community workshop participants demographic data ($$n = 13$$)CharacteristicsNLanguage Spoken French6 Mandarin7Gender Male8 Female5Age group (years) 18–493 50–693 70 + 7Years since diabetes diagnosis 1–4 years4 5–9 years2 10 + years7Years in Canada 0–4 years3 5–9 years7 10–19 years3 Outputs from each patient co-development workshop are presented in Tables 3. The tables summarize the personas and top five prioritized barriers and generated solutions selected by each group. Table 3Personas and top five barriers and generated solutions from the 1st, 2nd, and 3rd patients in the community co-development sessions developed with French-speaking and Mandarin-speaking individuals living with diabetes who have migrated from African-Caribbean countries and ChinaPatients in the Community GroupWorkshop 1: PersonasWorkshop 2: Barriers/EnablersWorkshop 3: Generated SolutionsFrench-speaking individuals living with diabetes who have migrated from African-Caribbean countries1. Abu is a 50-year-old male who lives in Ottawa, has no knowledge about diabetic retinopathy, he finds appointments with his eye specialist very long, he has difficulty getting eye care2. Clement is a 34-year-old male, he works at night and has diabetes. He has never heard of Diabetic Retinopathy; he is followed by a general practitioner and his doctor has never prescribed an appointment to see an eye specialist3. Sylvie is 43 years old woman and does not speak English. She has had two diabetes tests and is taking diabetes medication. She is on a diet. She has no information on diabetic RetinopathyLanguageProvide interpreter servicesNot knowing what retinopathy screening isOrganize radio broadcasts, invite during these programs the participants to share their testimony, invitation of medical specialistsDoctor haven’t told him/her about itThe community health team sends reminders (emails, SMS) about screeningDoctor doesn’t help to make AppointmentThe doctor must encourage patients to be tested and then make reminders by email (doctor's assistant) or via telephone messagingHard to fit eye screening around work and other activitiesThe doctor or his assistant can send the reminder and include the screening in the periodic examinationsMandarin-speaking individuals living with diabetes who have migrated from China1. Cuihua is a 60-year-old female with type 2 diabetes. She has suffered from severe diabetic retinopathy. Her family doctor suggested to have routinely eye checks every 1-to-2 years. She feels that three issues exist impeding her to do the eye check. First, the language problem. All the hospitals or eye check places use English or French. She cannot speak these two languages. It makes it very difficult for her to communicate with doctors. Her daughter is very busy with her work, and it is difficult for her to take a leave every time to accompany her to eye checks. So Cuihua often delays the eye check or even seldom does the check anymore. Especially during current COVID situation, she cannot go to see the doctor directly, but have to make an appointment. She is unable to make an appointment using English. Secondly, she cannot find the right place to go for eye check. Is it the clinic or eye specialty hospital? Third, before September 2021, it was free to do the eye check. But now it seems that the eye check is not free anymore. She does not have income and have multimorbidity. It seems very expensive to do the eye check2. Sun is a 67-year-old man who immigrated to Canada 15 years ago. He runs a pub and because of the nature of his work, he has irregular work hours. He smokes and drinks and has suffered from diabetes for 8 years. He does not control his blood sugar well and the main reason is he does not control what he eats. He would like to have an eye check. He does not know whether he suffers from diabetic retinopathy or not. He didn’t know that Ontarians could have free diabetic retinopathy check before this September. He never checked his eyes. His eyesight is ok, not very good. Since the elderly always have some eyesight problems, so he does not care about it a lot. He can speak the daily “pub” English, but medical *English is* a bit difficult for him. He thinks that it will be great if there are doctors that can speak Mandarin, but we all know there is very few3. John is 58 years old and have suffered from diabetics for 15 years. He would like to get early screening, early identification, and early treatment. He knows nothing about diabetic retinopathy, its screening, and its severity. He has never heard of eye screening from the family doctor. Each time when he went to the family doctors for medication, the family doctor paid high attention on the diabetic foot and would knock his feet for checkup. But the family doctor never mentioned about the eye check or did any eye check to him. So, he does not have any information sources about diabetic retinopathy. He does not know how much the screening cost and how often he should go for the eye check. If it cost too much, then he has to consider whether it is worth it for him to spend so much money for eye check. He is concerned that he has to adjust his work schedule for the eye check and also concerned with the language for communicationLanguageSupport from interpretersLack of knowledgeDiabetes patient WeChat groupLack of communication with the family doctor about screeningBrochures with audio recordings about diabetic eye screening (via a QR Code)Insufficient publicity about the screeningA patient guideline on diabetic eye screening, which encompasses different aspects of the screening, ranging from making appointment to screening and treatmentLack of specialized diabetic retinopathy screening facilitiesAdvocate for more specialized diabetes hospitals/facilities with the screening ability ## Health system partners and patient partner co-development workshops Health system partners consisted of 6 health practitioners, i.e., a Nursing Practitioner, diabetes educator, social support worker, endocrinologist, clinical manager, and diabetes program director. All provide services in different capacities at a CHC designated as a potential site for the diabetic retinopathy screening intervention. Patient partners consisted of French-speaking ($$n = 3$$) and Mandarin-speaking ($$n = 4$$) individuals living with diabetes [3] or family members/carers of a person with diabetes [4]. Health system and patient partners highlighted and generated possible operationalized strategies/solutions and channels of delivery perceived to be feasible, practical, safe, affordable, and equitable to address [36] (identify those targeting patients and health care providers separately). We identified the modes and settings of delivering behaviour change interventions [37, 38], agreed on materials to create, prototypes, and how to integrate other barriers and effective strategies not identified in the co-development workshops. Workshop participants decided the intervention should target individuals with diabetes and healthcare providers. The summary of the operationalized solutions for the prioritized barriers and outputs from the health system and patient partner co-development workshops are presented in Table 4.Table 4Mapped barriers to TDF domains, intervention strategies and channels of deliveryBarriersTDF domainsBCTs (Online tool)*Effective BCTs in Cochrane Review (Patients)Effective BCTs in Cochrane Review (HCP**)BCTs + Effective strategies (Cochrane)BCTs to be OperationalizedTarget: Patient vs HCP**Operationalized Solutions (Components of the intervention)Mode and Settings of Delivery1,2Language BarrierSkills + Social Influences4.1., 3.2., 7.1.,7.5., 8.1., 8.7., 12.1., 12.2., 12.3., 12.5., 1.2., 6.1., 8.1., 8.7., 15.1., 15.3., 15.44.1., 3.2., 7.1., 12.24.1., 3.2., 7.1., 12.2., 12.54.1., 1.23.2. Social support (practical)4.1. Instructions on how to perform behaviourPatient1. Language support services: Leveraging Language support services to deliver the intervention via phone, virtual (zoom), and physical interpretation as needed2. Flyers with translated terms:Provide flyers with translated key medical terms1. Human interactionalmode of delivery2. Printed publication mode of deliveryNot knowing what retinopathy screening is/ Lack of knowledgeKnowledge2.6., 4.1., 4.2., 5.1., 5.34.1., 5.14.14.1., 5.14.1 Instruction on how to perform the behavior5.1. Information about health consequencesPatient1. Group workshops: *Programming is* provided at the Community Health Centre (CHC) in Mandarin and French focused on diabetes and its complications. Provide information about the intervention, diabetic retinopathy, consequences, screening, and how to attend screening (i.e., 1–2 presentation slides) at the programs2. Posters: create a “poster” with short and simple messaging on diabetic retinopathy, consequences, and screening that can be displayed at doctors’ offices, pharmacies, other CHCs, Diabetes Education Programs, walk-in clinics, and clinics accepting newcomers3. Flyers, information sheets, and videos:- Communicate information about how to book screening, the screening process, the difference between screening and routine check, and risks1. Group-based mode of delivery at CommunityHealthcare facility2. Public notice mode of delivery at healthcare facilities3. Printed publication mode of delivery, Visual informationalmode of delivery, and Website mode of delivery at Community and retail, facilities, and social settingsLack of communication with the family doctor about screening + Doctor hasn’t told him/her about it + Doctor doesn’t help to make appointment​Social Influences3.1., 3.2., 6.2., 6.3., 10.43.1., 3.23.23.1., 3.23.1. Social support (unspecified)3.2. Social support (practical)HCP1. Send Reminders:- Appointment reminders are generated and sent to patients 24 h before scheduled visits- Pre-book yearly visits, i.e., book appointments one-year in advance via the Electronic Medical Record (EMR) and reminders will be sent one week before the appointment2. Social Support: Arranging for support from friends/family/ community. i.e., provide support via Community Champions and create a diabetes patient WeChat group3. Disseminate resources at various locations:- Information about diabetic retinopathy screening and the intervention sent to HCPs1. Messaging mode of delivery, or Email mode of delivery2. Human interactionalmode of delivery and electronic mode of delivery (Diabetes support WeChat group)Insufficient publicity about the screeningKnowledge + Environmental Context and Resources2.6., 4.1., 4.2., 5.1., 5.3., 3.2., 7.1., 7.5., 12.1., 12.2., 12.3., 12.54.1., 5.1., 7.14.1., 7.1., 12.54.1., 5.1., 7.1., 12.54.1 Instruction on how to perform the behavior5.1. Information about health consequences7.1. Prompts/cues12.5. Adding objects to the environmentPatient and HCP1. WeChat for communicating about the intervention: Patient partners communicate via their networks and groups on WeChat about the intervention using the developed resources2. Host videos and other resources on CHC Website:-Video resources for the intervention hosted on the CHC website3. Disseminate resources at various locations:- Information about the intervention posted via the CHC’s communication channels, sent to health practitioners at other CHCs, and community organizations4. Using TV Screens for promotion:- Where CHCs have a TV screen in client waiting areas, leverage this to display a poster with intervention information1. Electronic mode of delivery (WeChat)2. Visual informationalmode of delivery, and Website mode of delivery3. Printed publication mode of delivery at health, religious, retail facilities, and social settings4. Electronic billboard modeof delivery at Communityhealthcare facilityHard to fit eye screening around work and other activitiesEnvironmental Context and Resources3.2., 7.1., 7.5., 12.1., 12.2., 12.3., 12.53.2., 7.1., 12.23.2., 7.1., 12.2., 12.53.2., 7.1., 12.2., 12.53.2. Social support (practical)7.1. Prompts/cues12.2. Restructuring the social environmentHCP1. Send Reminders to patients2. Conduct screening with other diabetes care:- Coordinate eye screening with diabetes education visits and diabetes care activities such as foot care- Retinopathy screening integrated with the ongoing diabetes workshops such as the Chinese group workshops, where clients can connect with peers to have support whilst getting their eyes screened1. Messaging mode of delivery, or Email mode of delivery, or Letter mode of delivery2. Communityhealthcare facilityBCTs (Online tool)*: Human Behaviour-Change Project. The Theory and Techniques Tool. Available from: https://theoryandtechniquetool.humanbehaviourchange.org/tool; HCP**: Health care provider; 1,2 Marques et al. 2021 and Norris et al. 2020 (mapped by the research team during intervention development) ## Intervention development and components Informed by the co-development workshops and the literature on effective strategies for increasing DRS, we designed the final diabetes tele-retinopathy screening intervention to be piloted. Our intervention is tailored to the linguistic and cultural preferences of Mandarin-speaking and French-speaking individuals from China and African-Caribbean countries living with diabetes. After discussions with patient and health system partners, the intervention was named “Diabetes Eye Screening Ottawa (DESO)”. The logic model of the intervention development is outlined in Figs. 2 and the targeted TDF Domain, BCT and Mode of Delivery by Action, Actor, Context, Target and Time in implementation of the intervention is summarized in Additional file 4.Fig. 2Diabetes Eye Screening Ottawa logic model The intervention was designed to be free to patients at the point of care and primarily based on co-developed solutions and channels of delivery to barriers to attending DRS prioritized by Mandarin-speaking and French-speaking individuals from China and African-Caribbean countries living with diabetes. The barriers to screening and solutions identified in the literature but not prioritized during the patient workshops were nevertheless integrated in the intervention either in the tele-retinopathy screening care pathway or in the resources developed following discussions with the patient and health system partners. For example, views about harms caused by screening, forgetting, lack of transparency on screening costs, wait times, and making/getting to appointments were not specifically in the top five prioritised barriers in the co-development workshops but were key barriers identified in previous research [15], and were thus were also addressed in the flyers and information sheets developed. In addition, strategies such as monitoring and providing feedback on outcomes of screening and problem solving to address barriers to screening [16] were not prioritized in the patient workshops but nonetheless, they were integrated into the intervention’s care pathway given the evidence supporting their utility in addressing barriers in the extant literature. Our intervention will include operationalizing BCTs that focus on patient behaviour (via social support) using social media such as WeChat and Community Champions that include our patient partners who will act as liaison with the population groups and the health providers delivering the intervention. Other BCTs targeting patient behaviours include screening attendance reminder messages, and patient-facing resources such as posters, flyers, and videos). Our intervention will also focus on healthcare provider behaviour (via providing language support, pre-booking screening, prompts, and health practitioner faced resources). The healthcare provider-facing intervention is comprised of BCTs, including Instruction on how to perform behaviour, Information about health consequence, Prompts/cues, Adding objects to the environment, Social support, and Restructuring the social environment. Resources developed included flyers, information sheets, videos, posters, presentation slides, and a TV screen poster. The content of the developed resources was informed by information from the National Eye Health [39] and Diabetes Canada [40]. The content was tailored based on cultural and linguistic feedback from the patient partners and health system partners. Patient partners were involved in developing the intervention materials and the resources went through multiple levels of iterative modifications. The first prototype was presented in English and reviewed by both patient partner groups and health system partners. They recommended reducing the text included, changing the images to more culturally representative ones, using more neutral colors, and changing the format of the resources. A second modified prototype in English, French and Chinese was presented to the partners for feedback. Some advised changes were regarding the accuracy and simplification of the translations. The final prototype incorporated suggestions from the consultations. Since the barriers identified in both groups were similar, the research team decided that tailoring decisions of the resources could draw from suggestions from one group to the other. For instance, the Chinese patient partner group requested an explanation of key diabetic retinopathy screening terms in the flyer in Mandarin. This was similarly tailored in the French flyer. Nonetheless, there are some nuances where aspects of the intervention distinctly reflect cultural contexts. Culturally-tailored aspects of the intervention included specific channels and settings of delivery of the intervention resources aimed at encouraging reach. For example, the use of WeChat was included as a delivery channel for the Chinese individuals since this platform is commonly used for communication and enabling activities of daily living. In addition, representative photos embedded in the resources that resonated more with individual groups were unique and culturally-tailored. Resources were designed using a colour theme consistent with the community health centre that would house the tele-retinopathy screening intervention. ## Patients in the community perceptions of the co-development process At the end of the “Patients in the community” co-development workshop 3, participants were invited to complete an online questionnaire (Additional file 5) informed by a similar diabetes NGT co-development workshop in Ireland [41]. Patients were asked to provide feedback on how interesting, useful, and agreeable/enjoyable they found the workshops and to provide suggestions about how the workshop could have been improved. Seven participants completed the post-workshop feedback questionnaire. On a scale from 1 to 5 (where higher scores indicate higher levels), the mean scores for how interesting, useful, and enjoyable participants found the workshops were 4.9, 4.9, and 5.0 respectively. Common suggestions for improvement were to include other participants in the workshops, such as ophthalmologists and family doctors, and using online and in-person format for the workshops. ## Discussion Herein, we report the iterative co-development of intervention to encourage greater attendance to DRS amongst under-screened and under-served linguistic and cultural minority groups in the capital city of Canada. Our intervention draws on previously identified barriers and enablers to attendance and behaviour change techniques shown to be effective in supporting attendance. We specifically prioritized and sought to develop an intervention to address patient, provider, and institutional barriers to DRS, such as language barriers, cultural competency, lack of understanding of diabetic retinopathy, patient-physician interaction on DRS, conflicting priorities, and problems scheduling appointments [8, 15, 42]. The result is a combination of potentially effective BCTs including providing instructions on how to perform behaviour, information about health consequences, prompts/cues, adding objects to the environment, social support, and restructuring the social environment [16, 43], and channels of delivery to improve diabetic retinopathy screening attendance among French-speaking and Mandarin-speaking individuals living with diabetes from African-Caribbean and China. Our study serves to demonstrate how we worked and engaged with diverse stakeholders and patient and health system partners in a consensus process to co-develop a culturally and linguistically tailored intervention. We ensured that patients in the community, patient partners, and health system partners were involved at different steps throughout the co-development process [18] and possessed decisional authority over the development of the intervention [22]. For example, patients in the community and patient partners had decisional influence on the settings and channels of delivery. The health system partners possessed decisional weight on the logistics around the operationalization of the intervention. The ownership, relevance, and responsibility established from the co-development process with health partners and service users is likely to support the successful implementation of the intervention. Given the differential uptake of diabetic retinopathy screening amongst immigrants to Canada relative to the wider population of eligible people with diabetes, interventions tailored to support particular communities may better serve the overall goal of increasing DRS attendance [43]. Our theory-informed intervention will focus on both healthcare provider and patient behaviour operationalizing BCTs, and resulting channels of delivery such as providing information and instruction via videos, flyers, and information sheets. Our hope is that the methods described herein serve as an exemplar to inform the design of health services/interventions for linguistic and cultural minority groups. The co-development processes with patients and health system partners to identify barriers/enablers and generate and operationalize solutions can be adapted to other contexts in Canada. Now developed, this intervention will be piloted from December 2022 to June 2023 for feasibility and acceptability. We will use a multimethod approach to assess the feasibility, fidelity, and acceptability of the intervention with the healthcare providers delivering the intervention and individuals with diabetes who attend the intervention (Umaefulam V, Wilson M, Boucher MC, Brent MH, Dogba MJ, Drescher O, et al.: Assessing the feasibility, acceptability, and fidelity of a teleretinopathy-based intervention to encourage greater attendance to diabetic retinopathy screening in immigrants living with diabetes from China and African-Caribbean countries in Ottawa, Canada, submitted). ## Strengths and limitations Intervention co-development was strengthened by having multidisciplinary research team consisting of patients and caregivers with lived experience of diabetes, as well as health system partners, clinicians (eye specialists), implementation scientists, health services researchers, and behavioural scientists. This diverse expertise enabled the co-development of an intervention feasible for implementation in practice and reflective of the newcomers’ and immigrant community needs. The intervention considers the population groups’ heterogeneity of the population groups to increase its cultural and linguistic appropriateness. Patient partners ensured cultural appropriateness and adequate representation in intervention resources (such as in photos) and relevant settings and channels of delivery for the population groups. For example, we included WeChat as a channel of delivery and included religious, retail and/or community settings specific to the two groups. Likewise, we provided different versions of the intervention resources (English, French, and Chinese). There is the potential that we missed or overlooked existing diabetes eye care programs using Google alone for executing the search strategy for the environmental scan. Nonetheless, our data extraction relied on both source materials taken directly from online websites and information obtained from health care practitioners providing diabetes eye care and involved at different levels of diabetes programming in Ottawa’s primary, secondary, and tertiary care. As such, we captured the scope of programs not exclusively listed on the websites accessed. The environmental scan highlighted some gaps (and opportunities for improvement) in the existing diabetic retinopathy screening programs available in Ottawa. Additionally, we identified possible CHCs suitable for conducting a community-based tele-retinopathy screening for French-speaking African Caribbean and Mandarin-speaking Chinese individuals living with diabetes. Patients in the community and patient partners self-declared their diabetes status and immigration status. As such, we could have included individuals not representing the desired group in the study. However, patient participants were identified by community networks that cater to individuals living with diabetes. Our ability to observe user interactions [22] with the prototypes of the resources developed was limited, given the virtual nature of the design process. Also, the patients in the community groups were not able to review the intervention after the health system and patient partners’ input. However, the patient partners had various opportunities to alter the resources during their development. Some barriers and strategies were additionally incorporated without involving patients in the community. We took an approach that supplements what our patients in the community helped us to co-develop with strategies that are known in the trial literature to be effective at addressing barriers that are common in the literature, to round out the range of approaches included in the intervention. We worked with our patient partners in bringing in this additional content, and thus we did not remove the content co-developed with patients in the community, but rather we supplemented it. We identified several contextual factors and challenges during the co-development process, which have broader methodological relevance for implementation science. *Personas* generated at the workshops were closely connected to the participants themselves and their lived experiences, more subjective, and may not reflect the broader experiences of the population groups in Ottawa. Thus, to provide a holistic representation of the factors to address, we integrated the barriers to attending tele-retinopathy screening identified by patients in the community workshops with the input of patient and health system partners and our previous research with similar populations in Ottawa and Montreal [32]. Also, the dynamics of the patients in the community and patient partner groups were different influencing the approach needed to facilitate the workshops. Case in point, the Chinese patients in the community and partners regularly interacted via a WeChat group created for project participants, as such a working relationship existed throughout the co-development phases. French participants did not have a common forum or platform of which they were part, and relationships were not developed prior to the co-development sessions. By conducting the co-development activities virtually, we experienced some challenges in facilitating the workshops, such as limited internet access for some participants during the workshops. The facilitator used various formats for communication, such as typing thoughts in the zoom chat, sending text messages, or speaking out during the workshop sessions to encourage participation and enhance interaction. Utilizing the NGT in the workshops ensured that each participant had the opportunity to contribute. Although our health system partners possessed different professional backgrounds, most of them had working relationships with each other, which assisted with the dynamics of the workshops and advanced the collaborative work in designing the intervention. The health system partners provided insight into current pathways of care and programs available for individuals with diabetes to get their eyes screened in Ottawa. As a result of the ongoing working relationship among the health system partners, there was ready consensus on the changing roles, processes, and tools required to operationalize the tele-retinopathy screening intervention. As such, recruiting health system partners who work in some capacity within similar environments, may enhance the co-development process. ## Conclusion We highlight the co-development of a linguistically and culturally tailored tele-retinopathy intervention with patient and health system partners to improve the attendance of DRS for immigrants to Canada from China and African-Caribbean countries. By integrating behaviour change theory with user involvement and various levels of engagement, our intervention is well placed to be acceptable, relevant, and able to equitably deliver and facilitate the uptake of the tele-retinopathy screening intervention. Our intervention will fit within community health care practice workflow and leverage existing networks and processes to advance its implementation. 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--- title: mTORC1 Deficiency Prevents the Development of MC903-Induced Atopic Dermatitis through the Downregulation of Type 2 Inflammation authors: - Anupriya Gupta - Keunwook Lee - Kwonik Oh journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054228 doi: 10.3390/ijms24065968 license: CC BY 4.0 --- # mTORC1 Deficiency Prevents the Development of MC903-Induced Atopic Dermatitis through the Downregulation of Type 2 Inflammation ## Abstract Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by eczema and itching. Recently, mTORC, a central regulator of cellular metabolism, has been reported to play a critical role in immune responses, and manipulation of mTORC pathways has emerged as an effective immunomodulatory drug. In this study, we assessed whether mTORC signaling could contribute to the development of AD in mice. AD-like skin inflammation was induced by a 7-day treatment of MC903 (calcipotriol), and ribosomal protein S6 was highly phosphorylated in inflamed tissues. MC903-induced skin inflammation was ameliorated significantly in Raptor-deficient mice and exacerbated in Pten-deficient mice. Eosinophil recruitment and IL-4 production were also decreased in Raptor deficient mice. In contrast to the pro-inflammatory roles of mTORC1 in immune cells, we observed an anti-inflammatory effect on keratinocytes. TSLP was upregulated in Raptor deficient mice or by rapamycin treatment, which was mediated by hypoxia-inducible factor (HIF) signaling. Taken together, these results from our study indicate the dual roles of mTORC1 in the development of AD, and further studies on the role of HIF in AD are warranted. ## 1. Introduction Atopic dermatitis (AD) is one of the chronic inflammatory skin diseases characterized by recurrent eczematous lesions and intense itching [1,2,3]. The pathophysiology is complicated and includes exaggerated type 2 inflammation driven by type 2 T helper (TH2) and innate lymphoid cells (ILC2s), and impaired barrier functions include a loss-of-function mutation in the gene encoding filaggrin [4]. These drivers can also promote and interact with each other. For example, skin barrier impairment caused by filaggrin deficiency promotes T-cell infiltration and bacterial infection in the skin. Local type 2 inflammation further diminishes barrier function, causing itching and inducing tissue damage. Some individuals with AD suffer from a series of other allergic diseases, such as allergic rhinitis, food allergies, and asthma, which is the so-called ‘atopic march’ [5]. AD steadily increases in incidence and has been a burden for healthcare resources. However, the development of new therapeutics remains an unmet need. MC903 (calcipotriol) is an active vitamin D analog without affecting calcium metabolism [6] and has been used for psoriasis patients [7]. In some psoriasis patients, MC903 induces irritant skin inflammation as a side effect. However, in mouse keratinocytes, it upregulates TSLP, which induces AD-like type 2 skin inflammation [8,9]. Since TSLP receptors are expressed in various immune cells, including ILC2s, the TSLP-TSLP receptor interaction activates ILC2s to produce type 2 cytokines, such as IL-4, IL-5, and IL-13 [10] and stimulates eosinophils [11], basophils [12,13], and dendritic cells [14], which eventually causes AD-like skin inflammation. Collectively, the MC903-induced skin inflammation model allows us to analyze the roles of various immune cells during the development of AD. The mechanistic target of rapamycin (mTOR) is a crucial regulator of cellular metabolism and is implicated in cancers and diabetes. mTOR is a serine/threonine kinase, and its signaling proceeds via two complexes: mTOR Complex 1 (mTORC1) and mTORC2 [15,16]. mTORC1 contains Rheb (a small GTPase), the regulatory-associated protein of mTOR (Raptor), G protein β-subunit-like protein (GβL), and the proline-rich Protein Kinase B (PKB)/Akt substrate 40 kDa (PRAS40), and it is rapamycin-sensitive. mTORC1 activation leads to the phosphorylation and activation of the ribosomal S6 kinase and is thought to be associated with ribosome biogenesis, autophagy, and protein translation. mTORC2 contains, in addition to mTOR and GβL, the rapamycin-insensitive companion of mTOR (Rictor) and mammalian stress-activated protein kinase interacting protein-1 (mSin1). The phosphorylation of *Akt is* one of the downstream targets of mTORC2 [17,18]. Both mTORC1 and mTORC2 are also closely involved in immune responses as well as metabolism. mTORC1 also promotes a shift in glucose metabolism from oxidative phosphorylation to glycolysis by increasing the translation of transcription factor hypoxia-inducible factor (HIF), which drives the expression of several glycolytic enzymes [15]. HIF is independently regulated by both mTORC1 and hypoxia. In the presence of sufficient oxygen, HIF is hydroxylated by iron-dependent prolyl hydroxylases (PHDs) and then degraded. Under hypoxia, the activity of PHDs is inhibited, and then HIF is stabilized, allowing translocation to the nucleus and activation of a group of genes that minimize oxygen consumption and restore oxygen delivery [19]. In this study, we found that ribosomal protein S6 was phosphorylated in keratinocytes and inflammatory cells after MC903 treatment, which led us to investigate the roles of mTORC in the MC903-induced AD model. MC903-induced skin inflammation was significantly reduced in the Raptor deficient or rapamycin-treated mice, accompanied by downregulation of IL-4 and reduced numbers of eosinophils, suggesting that mTORC1 is essential for the type 2 skin inflammation induced by MC903. In contrast, TSLP was upregulated in the Raptor deficient or rapamycin-treated mice and downregulated by DMOG (dimethyloxalylglycine). Considering that DMOG inhibits PHD and stabilizes HIF, these findings demonstrate both pro- and anti-inflammatory roles of mTORC1 in the development of AD. ## 2.1. Ribosomal Protein S6 Is Phosphorylated in MC903-Induced Skin Inflammation MC903 has been known to induce type 2 skin inflammation and develop human AD-like symptoms in mice [8,9]. First, we tested the effect of MC903 on the development of AD-like skin inflammation in our mouse facility. 2 nmol of MC903 was applied to the ears every day, and the extent of inflammation was monitored by ear thickness. The ears swelled gradually and became more than twice as thick after 7 days of treatment with MC903 compared with those treated with the vehicle (EtOH) (Figure 1A). The inflamed ears also displayed reddening, swelling, and scaling, and the epidermis began to peel when the treatment period was extended to 14 days (Figure 1B). Histological analysis revealed epidermal hyperplasia and inflammatory cell infiltrates (Figure 1C). We also tested the phosphorylation of ribosomal protein S6 (pS6) using immunohistochemistry to check the activity of mTORC1 and found that both keratinocytes and dermal inflammatory cells were pS6 positive (Figure 1C), suggesting that mTORC1 was activated in both immune cells and keratinocytes. A similar finding was observed in the immunoblotting assay as well (Figure 2B). The serine residue of Akt was also phosphorylated modestly in the skin tissues treated with MC903 (Figure 2B). ## 2.2. mTORC1 Is Essential for MC903-Induced Skin Inflammation Since the roles of mTORC1 and mTORC2 in type 2 inflammation and AD were controversial [20,21,22,23,24,25], we investigated this issue in the MC903 skin inflammation model using Raptor and Rictor deficient mice. To exclude the potential effects of mTORC1 on the development, we inactivated Raptor in adult mice using the tamoxifen-inducible Ert2Cre transgene. We applied tamoxifen into the ears of Ert2Cre-Raptorfl/fl (referred to as Raptor cKO) daily for 5 days and checked the expression of Raptor in the ear tissues using RT-qPCR. After tamoxifen treatment, the floxed Raptor alleles were deleted, and the expressions of the Raptor transcripts (Figure 2A) and the S6 phosphorylation (Figure 2B) were reduced significantly (without tamoxifen, the level of pS6 was comparable between WT and Ert2Cre-Raptorfl/fl mice (Figure 2B)). Next, 2 nmol of MC903 was applied to the WT and Raptor cKO mice for 7 days, and the extent of ear swelling was monitored. Although the ears of both WT and Raptor cKO mice swelled after MC903 treatment, the ears of WT mice were much thicker than those of Raptor cKO (Figure 2C). Consistent with the ear thickness results, the signs of inflammation, such as reddening, scaling (Figure 2D), epidermal hyperplasia, and inflammatory cell infiltration were much less severe in the Raptor cKO mice (Figure 2E). We next investigated the immunologic changes in the ears using flow cytometry. In control WT mice (treated with EtOH), the frequencies of lymphoid (CD90+) and myeloid (CD11b+) cell populations were similar, or there were more lymphoid cells. In contrast, the frequency of myeloid cells, including neutrophils (CD11b + Ly6G+) and eosinophils (CD11b + Siglec-F+), increased dramatically in the MC903-treated WT ears (Figure 3A, left). In lymphoid cell populations, MC903 treatment upregulated TH2 markers, including GATA3 and ST2 in CD4+ T cells (Figure 3A, right) and TH2 cytokines, such as IL-4 (Figure 3C). We also calculated the absolute numbers of each cell population and found that there were more hematopoietic cells (CD45+), myeloid cells (CD11b+), and TCRβ+ T cells in the MC903-treated WT ears (Figure 3B). However, the expression levels of GATA3 and ST2 in CD4+ T cells (Figure 3A) and the numbers of all subsets of inflammatory cells (Figure 3B) were reduced in Raptor cKO mice, supporting that mTORC1 was essential for the activation of immune cells in skin inflammation induced by MC903. Since the ribosomal protein S6 was phosphorylated in not only immune cells but also keratinocytes (Figure 1C), we checked the expressions of epidermal cell-derived cytokines such as TSLP, IL-33, and IL-25 [21,22]. The expressions of IL-33 and IL-25 were not changed significantly in WT and Raptor cKO. By contrast, TSLP was upregulated by MC903 treatment in WT and even more in Raptor cKO (Figure 3C). To confirm the above results, we repeated the MC903 experiments again using different mouse models. ## 2.3. Rapamycin Prevents Type 2 Inflammation It was reported that mTORC2 and its downstream molecules, such as Akt and cathepsin H were essential for the barrier function of the skin, and the disruption of this axis was associated with AD [26], which led us to investigate the role of mTORC2 in the MC903-induced skin inflammation. In order to delete the Rictor alleles, the Ert2Cre-Rictorfl/fl (referred to as Rictor cKO) mice were treated with tamoxifen (Figure 4A). Then, 2 nmol of MC903 was applied to WT and Rictor cKO mice. In contrast to Raptor cKO mice, Rictor cKO mice were susceptible to MC903 treatment, and the skin inflammation developed comparably in both WT and cKO mice (Figure 4B). The shape of the ears and the expression levels of cytokines, such as IL-4 and TSLP (Figure 4C), were also indistinguishable between WT and cKO mice, implying that acute ablation of Rictor did not impair the functions of skin barrier and immune cells. To make sure the roles of Raptor in MC903 skin inflammation, we deployed two different mouse models: Ert2Cre-Ptenfl/fl (referred to as Pten cKO) and rapamycin. Consistent with the results of the Raptor cKO study, the ear inflammation induced by MC903 was enhanced in the Pten cKO mice (Figure 4D,E) and diminished after rapamycin treatment (Figure 4F,G). Then, we analyzed the cytokine expression in mice treated with rapamycin and found that IL-4 was downregulated, but TSLP was upregulated by rapamycin, as it was in Raptor cKO mice (Figure 4H), which led us to hypothesize that rapamycin could work differently in immune cells and keratinocytes and search for the downstream target in the regulation of TSLP expression. ## 2.4. Rapamycin Upregulates TSLP in Keratinocytes through a HIF Pathway To determine the downstream target of mTORC1 in the expression of TSLP, we treated HaCaT cells with TNF-α plus various inhibitors and performed the RT-qPCR analysis to quantify the amount of TSLP transcripts. Since the long form of TSLP mRNA contributes to the release of TSLP protein [27,28], we measured the long form of TSLP transcripts. Consistent with the previous reports [29] and in vivo data (Figure 4H), TSLP was upregulated by TNF-α, and the expression level of TSLP was higher in the presence of TNF-α and rapamycin. The expression of TSLP was decreased by the inhibitors of NF-κB (TAK), JNK, and PHD (DMOG) (Figure 5A). DMOG is a well-known inhibitor of PHD and helps to maintain HIF. Since HIF is a downstream target of mTORC1 as well as PHD, we hypothesized that the expression of TSLP was regulated by the mTORC1-HIF axis. To determine the relationship between mTORC1 and HIF, we examined the expression of HIF in WT and Raptor KO mice treated with MC903 and found that both HIF isoforms (HIF-1α and HIF-2α) were downregulated in Raptor KO skin (Figure 5B). Next, we applied DMOG on the ear together with MC903 and investigated whether DMOG reduced the expression of TSLP and MC903-induced skin inflammation in vivo. Not only the expression of TSLP (Figure 5C) but also the skin inflammation (Figure 5D) was reduced significantly by DMOG treatment. Papain is a protease known to cause occupational asthma [30] that also induces asthma-like inflammation in mice via TSLP [31], IL-33 [32], and ILC2 [33]. Since the mechanism of action of papain in lung inflammation seems to be like that of MC903 in the skin, we decided to check the effect of DMOG on the TSLP expression using BEAS-2B bronchial epithelial cell lines. Like the results in HaCaT cells, DMOG downregulated TSLP in BEAS-2B cells treated with papain (Figure 5E), supporting the idea that TSLP production under inflammatory conditions could be prevented by mTORC1-HIF signaling. ## 3. Discussion In this study, we investigated the roles of mTORC1 and mTORC2 in an MC903-induced AD model and found that mTORC1 is essential for type 2 inflammation. Raptor (mTORC1) deficiency or rapamycin treatment dramatically reduced the expression of IL-4, inflammatory cell recruitment, and the extent of ear swelling. All of the results demonstrated the pro-inflammatory effect of mTORC1 on the development of AD. However, we also found an anti-inflammatory function of the mTORC1 signaling: TSLP was upregulated by Raptor deficiency or rapamycin treatment. Given that TSLP acts early in allergic inflammation, such as conditioning basophils [34] or dendritic cells [35], we speculated that the anti-inflammatory effect of rapamycin or Raptor deficiency gradually became predominant at the late stage of MC903-induced inflammation (via downregulation of IL-4) [36]. It has been reported that mTORC1 controls HIF signaling through various mechanisms at both transcription [37,38] and translation [39] levels. We also found that both HIF-1 and HIF-2 were downregulated in Raptor KO (Figure 5B), supporting the idea that mTORC1 regulates TSLP expression via HIF. HIF and glycolysis have been reported to promote type 1 [40] and type 3 [41] inflammation. However, the role of HIF in type 2 inflammation remains unclear. Here, we found that DMOG inhibited the expression of TSLP (Figure 5B) and type 2 skin inflammation (Figure 5C), suggesting that HIF might reduce type 2 inflammation in the skin. Therefore, it would be intriguing to investigate whether HIF or DMOG inhibits type 2 inflammation without affecting type 1 or 3 inflammation. Lastly, we would like to mention the limitations of this study. In contrast to reactions in mice, MC903 did not upregulate TSLP in human keratinocytes [42], nor did it induce AD-like dermatitis in human skin. Instead, it inhibited human keratinocyte proliferation [43]. Therefore, extrapolation of our findings to human AD pathogenesis should be applied with great caution. ## 4.1. Mice Wild-type (WT) C57BL/6 (B6) mice were purchased from Koatech. Raptorfl/fl, Rictorfl/fl, and Ptenfl/fl mice [44,45] were crossed with the tamoxifen-inducible Cre (Ert2Cre) transgenic mice (B6.129-Gt(ROSA)26Sortm1(cre/ERT2)Tyj/J, The Jackson Laboratory). To delete floxed genes, tamoxifen (0.1 mg/ear, Sigma-Aldrich, St. Louis, MO, USA) was applied to the ear skin daily for 5 days. Genotyping was performed by using PCR or immunoblotting. All animal experimentations were conducted in accordance with guidelines and approval of the International Animal Care and Use Committees of Hallym University (Hallym 2020-28, Hallym 2021-59). ## 4.2. MC903 Induced Murine AD Model MC903 (calcipotriol, Sigma-Aldrich) was dissolved in EtOH and topically applied to mouse ears. Mice were sensitized with 2 nmol of MC903 for 7 days unless specified otherwise. As vehicle control, the same volume of EtOH was applied to mouse ears. During MC903 treatment, ear thickness was measured and recorded using a micrometer (Mitutoyo, Kawasaki City, Tokyo). ## 4.3. Tissue Preparation and Flow Cytometry The ears were minced and digested in 2 mL HBSS containing 0.1 mg/mL DNase I and 0.1 mg/mL Liberase TL (Sigma-Aldrich) for 1 h at 37 °C. The suspension was then passed through a 70 μm cell strainer (SPL). For surface staining, the cells were stained with antibodies for 30 min at 4 °C in the dark. For intracellular staining, the cells were stained using Foxp3 Staining Buffer set (eBioscience, San Diego, CA, USA). The antibodies included anti-mouse CD11b BV510 (M$\frac{1}{70}$), CD11c BV421 (N418), CD3 FITC (145-2C11), CD4 PE/Cy7 (RM4-5), CD45 PE/Cy7 or BV510 (30-F11), CD8 APC (53-6.7), CD90.2 APC/Cy7 (30-H12), Ly-6G PerCP/Cy5.5 (1A8), Siglec-F A647 (E50-2440), TCRβ APC/Cy-7 (H57-597), TCRγ/δ PerCP/Cy5.5 (GL3), Gata-3 eFluor660 (TWAJ), and T1/ST2 biotinylated (DJ8) antibodies (all from Biolegend (San Diego, CA, USA), BD Biosciences (San Jose, CA, USA), eBioscience, and mdbioproducts (Oakdale, MN, USA)). Data were acquired through FACS Canto-II (BD Biosciences) and were analyzed with FlowJo software (version 10, BD Biosciences). ## 4.4. Cell Culture The human keratinocyte HaCaT cells (ATCC) and human bronchial epithelial cell BEAS-2B (kindly provided by Professor Young-Hee Kang (Department of Food and Nutrition, Hallym University)) were used in this study. Both were cultured at 37 °C under a humidified atmosphere of $5\%$ CO2 in $10\%$ FBS/DMEM or $10\%$ FBS-BEGM (Bronchial Epithelial Cell Growth Medium BulletKit™, Lonza, Basel, Switzerland), respectively. For all cell stimulation experiments, 2 × 105 cells were seeded in each well of a 24-well plate. When cells were grown to $80\%$ confluence, cells were stimulated with TNF-α and various inhibitors for 2 h and then harvested in Trizol (Invitrogen, Waltham, MA, USA) for RNA extraction. The inhibitors (all from Sigma-Aldrich, except ACSS2 and ACLY inhibitors) are as follows: TAK inhibitor, (5Z)-7-Oxozeaenol; JNK inhibitor, JNK Inhibitor II; p38 inhibitor, SB203580; CAMKK inhibitor, STO-609; Caspase inhibitor, Z-VAD-FMK; JAK inhibitor, Pyridone 6; ACSS2 inhibitor N-(2,3-di-2-thienyl-6-quinoxalinyl)-N′-(2-methoxyethyl) urea (Hit2Lead); ACLY inhibitor, and SB 204990 (Tocris, Bristol, UK). ## 4.5. Immunohistochemistry Ear tissues were fixed in a $10\%$ neutral-buffered formalin, dehydrated, and embedded in paraffin. Paraffin sections (5 μm thick) were blocked ($10\%$ normal goat serum in PBS) and incubated with anti-pS6 antibodies (Cell Signaling, Danvers, MA, USA) overnight at 4 °C. Bound primary antibodies were detected with HRP-Conjugate secondary antibodies and a DAB IHC detection kit (Abcam, Cambridge, UK). ## 4.6. Quantitative PCR (qPCR) RNA was extracted using Trizol (Thermo Fisher Scientific, Waltham, MA, USA) and reverse-transcribed into cDNA using QuantiTect Reverse Transcription kit (Qiagen, Hilden, Germany). All data were normalized to actin. Non-specific amplification was checked by using melting curves and agarose gel electrophoresis. The sequences of primers are as follows. Mouse Il4 Forward: 5′-ACAGGAGAAGGGACGCCA-3′ Mouse Il4 Reverse: 5′-GAAGCCCTACAGACGAGCTCA-3′ Mouse Tslp Forward: 5′-AGGCTACCCTGAAACTGAG-3′ Mouse Tslp Reverse: 5′-GGAGATTGCATGAAGGAATACC-3′ Mouse Il33 Forward: 5′-GGTGTGGATGGGAAGAAGCTG-3′ Mouse Il33 Reverse: 5′-GAGGACTTTTTGTGAAGGACG-3′ Mouse Il25 Forward: 5′-CAGCAAAGAGCAAGAACC-3′ Mouse Il25 Reverse: 5′-CCTGTCCAACTCATAGC-3’ Mouse Actin Forward: 5′-CATCCGTAAAGACCTCTATGCCAAC-3′ Mouse Actin Reverse: 5′-ATGGAGCCACCGATCCACA-3′ ## 4.7. Immunoblotting The pieces of ear skin were lysed with cold radioimmunoprecipitation (RIPA) buffer containing a protease inhibitor cocktail (Roche, Basel, Switzerland). Subsequently, the collected protein was subjected to sodium dodecylsulfate (SDS)–polyacrylamide gel electrophoresis (PAGE) and blotted using nitrocellulose paper (Amershan). 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--- title: Wavelength-Dependent Effects of Photobiomodulation for Wound Care in Diabetic Wounds authors: - Peter Dungel - Sanja Sutalo - Cyrill Slezak - Claudia Keibl - Barbara Schädl - Harald Schnidar - Magdalena Metzger - Barbara Meixner - Jaana Hartmann - Johannes Oesterreicher - Heinz Redl - Paul Slezak journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054229 doi: 10.3390/ijms24065895 license: CC BY 4.0 --- # Wavelength-Dependent Effects of Photobiomodulation for Wound Care in Diabetic Wounds ## Abstract Photobiomodulation, showing positive effects on wound healing processes, has been performed mainly with lasers in the red/infrared spectrum. Light of shorter wavelengths can significantly influence biological systems. This study aimed to evaluate and compare the therapeutic effects of pulsed LED light of different wavelengths on wound healing in a diabetic (db/db) mouse excision wound model. LED therapy by Repuls was applied at either 470 nm (blue), 540 nm (green) or 635 nm (red), at 40 mW/cm2 each. Wound size and wound perfusion were assessed and correlated to wound temperature and light absorption in the tissue. Red and trend-wise green light positively stimulated wound healing, while blue light was ineffective. Light absorption was wavelength-dependent and was associated with significantly increased wound perfusion as measured by laser Doppler imaging. Shorter wavelengths ranging from green to blue significantly increased wound surface temperature, while red light, which penetrates deeper into tissue, led to a significant increase in core body temperature. In summary, wound treatment with pulsed red or green light resulted in improved wound healing in diabetic mice. Since impeded wound healing in diabetic patients poses an ever-increasing socio-economic problem, LED therapy may be an effective, easily applied and cost-efficient supportive treatment for diabetic wound therapy. ## 1. Introduction Incidence of diabetes has risen to an alarming rate. In Europe, about 60 million people are affected from diabetes and each year about 3.4 million people die from the consequences of elevated blood sugar levels [1,2]. Due to the chronic state of hyperglycemia in diabetic patients, an unbalanced level of matrix metalloproteases (MMP) establishes, which leads to excessive degradation of the extracellular matrix, ultimately leading to reduced tensile strength of the skin [3]. Along with other factors, including limited functionality of leukocytes and endothelial cells, as well as decreased collagen deposition by fibroblasts, this results in defective wound healing [4]. Patients diagnosed with diabetes exhibit a $25\%$ lifetime prevalence of developing diabetic foot ulcer (DFU) [5,6]. The chronic impairment of wound healing predisposes affected patients to severe infections, leading to the fact that one out of six DFU patients will require limb amputation, with a following 5-year mortality rate of up to $77\%$ [7]. Those numbers emphasize the huge burden of impaired diabetic wound healing. However, to date, no adequate therapeutic approaches exist. In recent decades, different therapeutic approaches based on biophysical effects to treat diabetes-related impaired wound healing have been investigated. These therapeutic options include extracorporeal shock wave treatment, ultrasound, negative and positive pressure, and photobiomodulation or photobiomodulation by laser or light emitting diode (LED) irradiation, and have been demonstrated to have clinical benefits for patients [8,9,10]. Although the therapeutic benefit of these therapies could be shown, for most approaches, the involved molecular mechanisms have not yet been satisfyingly unraveled. Photobiomodulation through LED irradiation is remarkably interesting and stands out from other biophysical methods as it is cost-effective, easy to apply and safe to use. A recent study reviewed four randomized control trials involving 131 participants, with the main aim to confirm the beneficial effects of PBM for the treatment of DFU. All studies demonstrated positive healing outcomes by PBM compared to placebo or control groups, and no adverse events associated with PBM treatment were reported [11,12]. Most of the studies on PBM in wound healing to date have been performed on red to near infrared (red-NIR) light sources, ranging from 600–1400 nm. However, shorter wavelengths could support wound healing probably via alternative modes of action. Light can significantly influence biological systems such as nitric oxide (NO) metabolism. We showed previously that photolysis of bioactive NO from nitrosyl-hemoglobin or mitochondrial protein complexes is wavelength-dependent and significantly more efficient with light in the green and blue range [13,14]. Nitric oxide has been shown to be highly involved throughout all phases of wound healing where it is associated with the regulation of inflammatory response, collagen deposition and angiogenesis [15]. In the present study, the effects of low level light therapy of three different wavelengths (red, 629 nm; green, 540 nm; blue, 470 nm) on wound healing in a diabetic (db/db) mouse excision wound model was investigated. ## 2. Results All used animals in the impaired wound healing group showed blood glucose levels ≥300 mg/dL. Figure 1 shows representative figures of wounds and wound progression over time. Wound geometry is an important factor of the healing process and has to be considered explicitly, especially when considering challenges associated with circular excisions [16]. Especially in earlier wound stages, maintaining a circular shape is crucial as to not introduce other driving mechanisms in addition to phototherapy into the system. Figure 2 shows that, for the study group, we maintain a high level of circularity until wounds have almost closed up. We have measured eccentricity as the ratio of the circular estimates for the radii based on the circumference and area. A perfect circle would yield a value of 1 and a linear cut would correspond to a 0. Here, highly non-circular wounds starting in early stages would tend to smaller wound sizes at increasingly elongated wound shapes. This is evident when fitting the data using a least squares exponential plateau regression fit. Within our study group we see a certain geometric homogeneity as evident by the narrow mean prediction bands at the $95\%$ confidence interval. Furthermore, there is no observed difference in the wound shapes for each of the experimental therapy groups as measured by the distribution of eccentricities (F[21, 222] = 0.4744, $$p \leq 0.9768$$) as they develop very similar shapes as they approach final healing (eccentricity = 0.735 ± 0.176). This allows a subsequent analysis of wound healing of circular excision wounds as promoted by each respective therapy, as emerging differences would likely not be a result of wound geometry. Basic wound healing progression was analyzed by comparison of the area of non-enclosed wound surface (Figure 3, left). The average wound area increased during the first 4-day interval in all groups and started to decrease thereafter. At day 8, a trend of a reduction in wound size compared to the control was observable in the red and green light groups, but not in the blue light group. The difference in average relative wound area compared to the control was significant (F[3194] = 4.37, $$p \leq 0.0253$$) on day 12 in the red light-treated group (48.6 ± $16.5\%$) compared to the control group (73.1 ± $33.4\%$). A visible, yet not significant trend was observed in the green light group (59.6 ± $16.2\%$). In contrast, there was only a marginal, non-significant reduction compared to the control in the blue light group (69.2 ± $13.7\%$) compared to the control. These trends of beneficial red and green light were maintained during the rest of the observation period through day 28, but were not significantly different from the control as wounds gradually closed in all groups. The dynamic wound size was further analyzed utilizing a least squares exponential plateau regression fit to the individual wound size measurements (Figure 3, right). The fitting form for the time-dependent relative wound size reduction from the initial W0 is taken to be %W(t)=(W0−Wp)∗exp(−k∗t)+Wp with plateau Wp and rate constant k. The red light treated group achieves a %50 wound size reduction after 12.2 days, while the control group does not reach this milestone until day 16.7. This delay in healing further increases until it reaches a maximum of 5.1 days at $30.7\%$ of the initial wound size at day 17.3. Green and blue light therapies show similar trends, but at shorter delays. These results coincided with the assessment of wound healing rate, which was analyzed for all interior time points averaged over a center-weighted 4-day window (±2 days in each direction), shown in Figure 4. Due to the increase in wound size, measured on day 4, the mean wound healing rate shows a negative value at this time point. At day 8, the initial wound size was reached again, followed by an early onset of increased wound healing rate at day 12 with red light therapy, with 0.092 ± 0.087 mm/day, and green light therapy, with 0.063 ± 0.155 mm/day. At day 16, similar healing rates were observed in all groups. To analyze the superficial blood flow in the wound area, an LDI (laser Doppler imaging) was performed on day 0 and on day 28 immediately after the illumination. The effect on tissue perfusion showed a wavelength dependency. A significant (F[3,28] = 3.746, $$p \leq 0.0174$$) increase in blood flow (Figure 5) after treatment with red (544.1 ± 142.5 AU), and a trend wise increase after treatment with green (495.1 ± 88.5 AU) and blue light (419.6 ± 66.5 AU), was observed on day 0. On day 28, no significant differences in blood flow from red (502.4 ± 105.6 AU), green (459.6 ± 112.7 AU) and blue light (412.7 ± 138.2 AU) were observed, although a similar trend wise increase as on day 0 was persistent in all groups. In order to analyze blood vessel formation, immunohistochemical staining of vonWillebrand factor (vWF) was carried out on day 28 after euthanasia of the animals. The blood vessels were counted in a 2 × 2 mm area of interest (ROI) in the center of the wound. The number of blood vessels (Figure 6 and Figure 7) was significantly increased (F[3,22] = 3.931, 0.0218) in the wounds treated with red (115 ± 36, $$p \leq 0.0182$$) and green light (109 ± 52, $$p \leq 0.0338$$). Wounds treated with blue light showed a positive but not significant increase in blood vessel formation (73 ± 27). Throughout the treatment, both wound size and wavelength affected the amount of light being absorbed and scattered by the surrounding tissue. In this experiment, the radiative power for each wavelength was nominalized but the absorbed and transmitted energies of the therapy are beyond an experimental evaluation. In lieu, Figure 8 (left) shows the remaining fractional reflection of light intensity of early wounds as an estimate of the power not penetrating the wound or deeper tissue. As expected, red light was mostly reflected, as evident by the surface color, commensally indicating the least energy penetrating the animal. Since the therapy was set calibrated for a constant illumination power, this demonstrates, in turn, that the most energy is being deposited at the wound site for blue light therapy. The volume, which, together with the energy, is deposited, also varies dependent on the wavelength. Figure 8 (right) shows the significant increase in wound temperature at the end of the treatment. Shorter wavelengths result in larger surface heating, while penetrating longer wavelengths result in a core temperature rise. To obtain better insight into the governing thermal mechanism, further analysis of the wound surface temperature dynamics during therapy was performed. Figure 9 shows the continually increasing mean wound surface temperature when exposed to the light therapy. Noticeably, there is no change in wound surface temperature in the control group for the first 140 s of the sham treatment. Only thereafter has enough time passed for the internally built up thermal energy due to kinetic activity and induced stressors to be transported to the surface. In order to correct for the light deposition of thermal energy, we need to correct for the inherent internal heating of the control group by treating it as the zero-external heating value. The dashed lines in Figure 8 show that the corresponding control group corrected least squares exponential plateau regression fits to the individual temperature readings. The fitting form ∆T(t)=Ts∗[1−exp(−k∗t)], where *Ts is* the long-term thermal steady state equilibrium with rate constant k. For each color therapy at steady state, once net energy transfers have equilibrated, the wound surface heating due to irradiation alone is in the range of 1.575 to 1.877 °C for blue, 1.436 to 1.638 °C for green, and 0.7220 to 0.8869 °C for red, given a $95\%$ confidence interval. Figure 10 shows groupwise comparisons of the mean standardized erythema value (SEV *) pre/post comparison, which was obtained by the Scarletred®Vision system. The image analysis data shows an increase for all colors over the duration of the therapy session. The wavelength dependent variations in observed superficial skin erythema can be seen as the result of dilatation of the blood capillaries. Wilcoxon matched pairs signed rank tests show the statistically significant largest increases commensurate with higher internal body temperatures for red ($$p \leq 0.0156$$) and green ($$p \leq 0.0078$$), and only a slight change for the control group ($$p \leq 0.0156$$). Only the blue group shows no change ($$p \leq 0.0781$$) in the SEV *, where large wound surface temperature increases are observed but comparatively little changes in body temperature. ## 3. Discussion Promising effects of photobiomodulation (PBM) have already been reported in numerous studies. In the present study we show that positive effects of PBM by pulsed LED light on wound healing and vascularization in a wavelength-depended manner. The irradiance at the target was 50 mW/cm2, which gives a radiant exposure of 14.4 J/cm2 for 6 min therapy in all treatment groups. As expected from previous studies, red light showed significant effects compared to untreated controls, while green light was also effective. The limited effects of blue light might be associated with light-dependent generation of reactive oxygen species (ROS) [17], which were reported to be predominantly produced at energy densities above 7 J/cm2, with blue light inducing the production of damaging concentrations of ROS of mitochondrial origin [18]. Studies using red laser light, such as Kaviani et al., reported that light of 685 nm significantly decreased the size of DFUs in patients compared to a placebo control group [19]. Significantly increased wound contraction was observed by Kajagar et al. in a clinical study investigating the effects of light with 660 nm combined with 850 nm wavelength [20]. Feitosa et al. used a laser with 632.8 nm to decrease the wound size of DFUs in patients and reported significant successes [19]. Additionally, the meta-analysis of randomized controlled trials [21], including the studies of Kaviani et al. and Kajagar et al., showed a significantly enhanced healing rate, diminished ulcer area, as well as a reduced recovery time of DFU patients in comparison to the control groups after low-level laser therapy (LLLT) treatment (wavelength range: 400–904 nm). Publication bias risk analysis demonstrated a low risk with a sensitivity, indicating that the results have strong reliability [21]. Most of the reported studies in the past were performed with laser light. Due to its advantages, including easier handling and lower costs, non-coherent LED light represents an alternative technology. Therefore, recently, more and more treatment options are being performed based on LED light, which was also the case in the present study. Comparative studies by Nishioka et al. and Agnol et al. demonstrated that therapies with laser and LED have similar effects on tissue regeneration and angiogenesis in vivo [22,23]. The previously mentioned studies, as well as most of the studies found in the literature investigating the effects on wound healing in diabetic foot ulcers used light within the red and infrared light spectrum, which currently holds the status of the gold standard in PBM [12]. Delayed wound healing affects wound sizes and its closure. Therefore, the main parameter investigated in this study was wound surface, wound healing rate, vascularization, as well as the overall wound geometry. As seen in Figure 2, the wounds gape initially, a typical behavior of wounds prior to the healing process [24]. After day 4, wound areas in all groups start to decrease consistently, with red and green light treated wounds showing a distinct trend of accelerated closure compared to the control group. This positive trend by red and green light was observable throughout the healing process and reached significance at day 12 in the red light treated group. Comparable stimulating effects of red (700 nm) and green (530 nm) LED light were also observed by de Sousa et al. in an in vitro proliferation assay of rat fibroblasts [25]. Positive effects of green light were also reported by Fushimi et al. using green LED light with 518 nm in both a wound healing model in mice and an in vitro model investigating mRNA and protein levels of cytokines secreted by human fibroblasts during wound healing [26]. In the present study, blue light with the same radiant exposure of 14.4 J/cm2 was ineffective, which stands in contrast to the study of Adamskaya et al., where the examined blue light in an excision wound model in rats resulted in significantly decreased wound size [27]. The accelerated wound healing of red and green light treated wounds in our study is also reflected by the wound healing rate (Figure 3), which was significantly increased at day 12 in the red and green light groups. Significantly increased wound healing rates were also observed in studies investigating red and infrared laser light in in vivo studies in rats and clinical studies [28,29,30]. Functionally, vascularization and the enabled reperfusion is a pivotal factor in wound healing and essential to ensure proper blood circulation and tissue integrity [31]. To include these aspects of wound healing, vascularization status was determined by assessing blood vessel presence in the regenerated wounded area. All tested wavelengths increased blood vessel formation, with the strongest effect found for red and green light. Similar angiogenic effects were previously reported by Cury et al. in a skin flap rat model using 660 nm and 780 nm lasers [32]. Zaidi et al. described increased blood vessel formation after red light treatment in an ischemic hindlimb mouse model [33]. We have shown before that angiogenesis and tissue perfusion in a rodent flap model can be significantly enhanced by red light, confirming our observations in the present study [34]. In the cited paper, blue light also showed a beneficial effect, which was not detected in the present study. This could be due to the fact that in the previously performed study ischemia-disturbed wounds were investigated, which added another possible layer of interaction of underlaying mechanisms. Under these conditions, nitrite is activated as an internal pool for nitric oxide (NO), high levels of NO are induced, and this molecule can be best targeted with blue light [14]. In accordance with our data, the stimulating effects of not only red but also green LED light were also confirmed in different in vitro studies using endothelial cells [35], as well as cells of the stromal vascular fraction [36]. We also demonstrated in this study that photobiomodulation led to increased blood perfusion, which was clearly shown by laser doppler imaging (LDI). Significant differences were detected at day 0 in the red and green light group, but not in the blue light group. On day 28, this pattern could also be detected; however, the trends did not reach statistical difference and were not associated with the significantly increased blood vessel counts in the red and green light group. This discrepancy might be explained by the fact that the performed LDI analyses were too insensitive and were only able to detect larger differences in perfusion. The significant increases at day 0 can obviously not be connected to angiogenesis, but rather to temperature increases caused by light, despite the fact that photobiomodulation is also termed cold light, which was also used in the present study to prevent temperature effects. To analyze the physical effects, reflection data in the wounds, as proxy data for tissue absorption, as well as both surface wound temperature and core body temperature of the treated mice, were recorded. Once again, a shift in these parameters was observed in a wavelength-dependent manner. The longer the wavelength was, the more light was reflected at the wound surface with significant differences of green and blue light compared to red light. Inversely, this shows the higher total deposition of energies at the shorter wavelengths. As far as the location of deposition is concerned, the higher absorbance of light of shorter wavelengths led to a significant increase in wound surface temperature after green and blue light treatment. Here, however, we observe a compounded, wavelength-dependent effect of reflection and absorption. Only a comparable small fraction of the higher red wavelength’s energy is being absorbed, as most of it is reflected and the absorption is spread out over a larger volume due to the long wavelength’s increased penetration depth. In contrast, the deposited energy increases for the shorter wavelengths and, in addition, primarily accumulates at the wound site due to decreasing transmissivity. For this type of small-rodent model, the deposited light energy per animal mass is not insignificant. For one, we observe an internal temperature increase in the control group during sham treatment. This can likely be ascribed to an increased stress level and the confined space allocated during treatment, which better retains body heat. Wound surface temperature readings indicate the same change. For two, irradiative energy deposition with the animal contributes to additional warming. Penetrating longer wavelengths results in a larger increase in core temperature due to the increased deposition depth beyond the wound, even though the animal received a smaller amount of energy. Convective heat transfers are effectively mediated by the animal’s vascularly system, resulting in a homogeneous temperature increase in the body. In contrast, the shorter, more energetic wavelengths lead to higher localized surface wound heating, while only resulting in moderate core temperature rises. Here, cooling occurs due to less effective radiative cooling at the surface, while convective processes are diminished due to low local perfusion volumes. This effect is quite evident and should be considered as an important parameter in controlled small animal studies. As an increased wound temperature can correlate with decreased wound healing and wound bed score [37], the choice of the wavelength used has to be carefully considered. In conclusion, we demonstrated that PBM by both pulsed red and green LED light has the potential to accelerate wound closure and increase angiogenesis of excision wounds in diabetic (db/db) mice. It remains to be elucidated whether or not the combination of two or more effective wavelengths leads to synergistical effects. PBM provides an effective, non-invasive and comfortable treatment for chronic wounds, such as diabetic foot ulcers. In order to offer the most effective treatment to patients, energy densities, duration and periods of PBM and potential combinations of red and blue or green light have to be compared in the future. ## 4.1. Animal Model C57BL/KsJm/Leptdb (db/db) mice were obtained from Charles River and Janvier Labs, housed three per cage in a 12-h light/dark cycle, and provided standard laboratory food and water ad libitum. After an acclimatization period of 14 days, the below-mentioned surgical procedure (dorsal excision) was performed. The observation period after surgery was 28 days. Thirteen-week-old genetically diabetic db/db mice were used for the experiment. The animals were weighed, anaesthetized with $3\%$ isoflurane (Abbott GmbH., Vienna, Austria) and had their blood glucose levels checked via an Akku-Chek Go glucose meter (Roche Diagnostics, Mannheim, Germany). All animals exhibited severely increased blood glucose levels above ≥300 mg/dL. Eight mice were used in each group. The animals’ dorsal hair was shaved and completely removed by using a depilatory cream. The skin was cleaned with alcohol and a ø 1.4 cm full-thickness skin wound was excised under aseptic conditions on the mid-dorsum. Subsequently, 200 μL of transparent hydrogel matrix (NU-GEL, KCI Medizinprodukte GmbH, Vienna, Austria) was topically administered. Then, the wound was covered with transparent Suprasorb F (Lohmann & Rauscher, Schoenau, Austria) to provide a standardized moist wound environment. The animals received an adequate pain management of 0.05 mg/kg Buprenorphine s.c. ( Buprenorphin, Richter Pharma, Wels, Austria) 2× daily at intervals of 6–12 h post-surgery for up to 2 days after intervention, as well as 0.15 mg/kg Meloxicam (Meloxicam, Boehringer, Vienna, Austria) daily for the first four days. Post-operative treatment comprised of warming the animals until end of anesthesia and a subcutaneous Ringer lactate infusion depot. Treatments and analyses were performed as stated below. On day 28, the animals were sacrificed in deep isoflurane anesthesia by intracardiac injection, whereupon the wound area was harvested for histologic analysis. ## 4.2. Photobiomodulation Therapy The first therapeutic application (day 0), according to group allocation, was performed. Application of light therapy was repeated every second day without anesthesia in a custom made container. Dressing changes were performed every four days, during which fresh hydrogel was applied. PBM was performed with red (629 nm), green (540 nm) and blue (470 nm) light. Irradiation time was 6 min (through the transparent wound cover membrane), and all therapy LEDs used a pulse frequency of 2.5 Hz, a duty cycle of $50\%$, and were normalized to 40 mW/cm2. These parameters were chosen based on the positive results of previous in vitro and in vivo studies [34,35,36]. The mouse was placed in a transparent, cylindrical enclosure of a diameter commensurate with the size of light source with surrounding ventilation slots for cooling, to ensure the animal remains within consistent light exposure throughout the therapy while maintaining some mobility (Figure 11). The vertical source distance to the mouse’s dorsum was kept at 10 cm. The overall dose of each treatment was 14.4 J/cm2. ## 4.3. Wound Assessment Wound size was assessed every fourth day from day 0 through to day 28 during wound dressing changes, using a stereoscopic lens (LifeViz micro, Quantificare, Biot, France) and a Canon Rebel XSi camera (Canon, Ota City, Tokyo, Japan) for 3D wound measurement (circumference, surface, average depth). Stereoscopic wound analysis parameters were evaluated using DermaPix Pro 2.28.5. Skin erythema was captured by using a smartphone (iPhone 6 Plus, Apple Inc., Cupertino, CA, USA) with installed CE medical device software Scarletred® *Vision plus* a Scarletred® Skin patch, which resulted in auto white balanced and color corrected skin images over treatment time. The images were consecutively uploaded and analyzed within the Scarletred® web platform (SCARLETRED Holding GmbH, Vienna, Austria) by using the standard erythema value (SEV *) algorithm [38,39,40]. Additionally, the animals were scanned via laser Doppler imaging (Moor, UK) under isoflurane inhalation anesthesia on the day of surgery (day 0) and on day 28 to assess superficial tissue perfusion. Results for the post-operative and post treatment scans were calculated in percentage of arbitrary units (AU) from baseline, pre-operative scans. The wound healing rate for every 8th day was calculated using the data from the wound surface (A) and perimeter (P) evaluated at time points T1 and T2. [ 1]healing rate in mm/day = A1−A2P1+P2∗0.5T2−T1 ## 4.4. Histology and Immunohistochemistry For histological evaluation, haematoxylin, eosin and immunohistochemical vWF stainings were performed according to standard protocol. Briefly, formalin-fixed paraffin-embedded tissue specimens were cut in 5 μm thick sections and de-paraffinized. Immunohistochemical stainings were performed in a Lab Vision Autostainer 360 (Thermo Scientific, Waltham, MA, USA). Anti-vWF (1:100, M-20, sc-1506-G, Santa Cruz Biotechnology, Santa Cruz, CA, USA) was used as the primary antibody. ## 4.5. Quantification of Stainings The vWF-stained whole sections were scanned with an Olympus BX61VS scanning microscope (Olympus Austria GmbH, Vienna, Austria) at ×20 magnification. The region of interest was defined to be 2 × 2 mm in the center of the regenerated wound tissue. ## 4.6. Temperature and Reflection Measurements At given timepoints, the effects of light treatment on both wound surface temperature and body core temperature were recorded. Wound surface temperature readings were obtained both at the start and immediately after the conclusion of individual therapy sessions via a contactless infrared thermometer PhotoTemp MX (Raytek, Bremgarten, Switzerland). Body temperature readings were concurrently obtained via a rectal probe using a Fluke 52 Series II thermometer (Fluke Austria GmbH, Brunn, Austria). Stereoscopic wound images were taken flanked by a grey/white reference card of $18\%$ and $90\%$ calibrated reflectance, respectively (Kodak, Rochester, New York, NY, USA), under monochromatic therapy illumination only. The sRGB color space recorded images were converted to a purely gamma-based color space Adobe RGB 1998 (ICC profile by Adobe Systems Incorporated, San Jose, CA, USA) and subsequently linearized. Average wound reflection brightness was obtained by the stereoscopic average of their intensities as a fraction of the reference card measurement. 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--- title: Mangiferin-Enriched Mn–Hydroxyapatite Coupled with β-TCP Scaffolds Simultaneously Exhibit Osteogenicity and Anti-Bacterial Efficacy authors: - Subhasmita Swain - Janardhan Reddy Koduru - Tapash Ranjan Rautray journal: Materials year: 2023 pmcid: PMC10054241 doi: 10.3390/ma16062206 license: CC BY 4.0 --- # Mangiferin-Enriched Mn–Hydroxyapatite Coupled with β-TCP Scaffolds Simultaneously Exhibit Osteogenicity and Anti-Bacterial Efficacy ## Abstract Biphasic calcium phosphate (BCP) containing β-tricalcium phosphate and manganese (Mn)-substituted hydroxyapatite (HAP) was synthesized. Biomedical scaffolds were prepared using this synthesized powder on a sacrificial polyurethane sponge template after the incorporation of mangiferin (MAN). Mn was substituted at a concentration of $5\%$ and $10\%$ in HAP to examine the efficacy of Mn at various concentrations. The phase analysis of the as-formed BCP scaffold was carried out by X-ray diffraction analysis, while the qualitative observation of morphology and the osteoblast cell differentiation were carried out by scanning electron microscopy and confocal laser scanning microscopy techniques. Gene expressions of osteocalcin, collagen 1, and RUNX2 were carried out using qRT-PCR analyses. Significantly higher ($p \leq 0.05$) levels of ALP activity were observed with extended osteoblast induction on the mangiferin-incorporated BCP scaffolds. After characterization of the specimens, it was found that the scaffolds with $10\%$ Mn-incorporated BCP with mangiferin showed better osteogenicity and simultaneously the same scaffolds exhibited higher anti-bacterial properties as observed from the bacterial viability test. This study was carried out to evaluate the efficacy of Mn and MAN in BCP for osteogenicity and antibacterial action. ## 1. Introduction Bone makes up the majority of the connective tissue mass in the body. Bone matrix is physiologically mineralized, unlike most other connective tissue matrices, and it is constantly rebuilt throughout the life of a human being because of the formation of new bones. Bone is a heterogeneous composite material consisting of a mineralized phase called hydroxyapatite (HAP; Ca10(PO4)6(OH)2), an organic phase ($90\%$ type I collagen), $5\%$ non-collagenous proteins (NCPs), and $2\%$ lipids together with water. Fracture healing is a physiological process that leads to bone union. However, large bone defects, despite surgical stability, does not heal spontaneously and entails additional intervention such as natural bone grafting (with an autograft, allograft, or xenograft) [1,2,3]. However, natural bone grafting has several disadvantages. Hence, synthetic calcium phosphate (CaP) bone grafts have been used in many cases. Its exceptional biocompatibility with bone tissues arises due to its chemical composition, similar to the bone mineral phase. Furthermore, CaP ceramic has nontoxic properties and can be attached to bone directly [4,5]. Tissue engineering (TE) is a broad and transdisciplinary field that has shown considerable promise in developing living substitutes for harvested tissues and organs for transplant and reconstructive surgery. TE relies heavily on materials and fabrication technologies to create temporary, synthetic extracellular matrices that supports formation of 3D tissues. Growing cells in 3D scaffolds have become increasingly popular for engineering tissues of realistic size scale and specified forms. They aid in creating functional tissues and organs by guiding cell growth and synthesizing extracellular matrix and other biological substances [6,7]. There are some primary conditions for building polymer scaffolds that are commonly accepted. The first condition is that it must have sufficient porosity and pore size. Secondly, a large amount of surface area is required. Biodegradability is a primary property of the scaffolds with a breakdown rate corresponding to the pace of new tissue creation. For retaining the tissue structure, the scaffold must possess corresponding mechanical strength to that of natural bones. The scaffold should not exhibit any toxicity to the cells. Finally, there should be a positive interaction between scaffold and tissues, resulting in improved cell adhesion, differentiation, migration, and growth [8]. Bioactive ceramics are recognized as the most promising biomaterials for bone tissue engineering. Because of its potential for direct bone-to-implant interaction, ceramics like hydroxyapatite, bioactive glass, β-tri-calcium phosphate (β-TCP), and calcium silicate have been extensively studied for biomaterial applications [9]. For over three decades, biphasic calcium phosphate (BCP) ceramics, which is a blend of HAP and β-TCP, have been broadly utilized as substitute biomaterials for synthetic bone grafting for which it has gained a lot of interest. BCP is appropriate for artificial bone applications and is considered superior to individual phase HAP or β-TCP components due to its exceptional controlled dissolving properties, which enhance new bone development at the implantation site. The degradation rate of β-TCP is 20 times higher than that of HAP [10]. Due to its high brittleness and low fracture toughness, HAP can only be used in non-load bearing areas in clinical orthopaedic and dental applications. β-TCP has less mechanical strength than HAP [11]. As a result, a mixture of HAP and β-TCP would balance out each other’s shortcomings. Thorough characterization of BCP is very important because it offers a combination of improved mechanical stability and bioactivity, which is challenging to accomplish in single-phase materials [12]. Adding trace metal elements (Ag+, K+, Na+, Sr2+, Zn2+, Cu2+, Mn2+, Mg2+, Al3+, Fe3+, Th4+) significantly improves the physical and chemical properties of bioceramics. The HAP phase contains a large number of trace metal elements [13]. Manganese (Mn) may be added to BCP as a sintering additive to enhance the mechanical characteristics of the material. In the presence of Mn, ligand affinity rises, resulting in increased cell adhesion. Mn in the bones has been observed to reduce bone resorption, according to one study [14]. Mn was also found to act as a calcination and sintering additive in BCP powders without causing establishment of any other subordinate phases such as α-TCP and CaO. Manganese doping in BCP is expected to increase the physicochemical characteristics of the material, resulting in better biological function in antimicrobial efficacy [15]. Moreover, Mn also has a role in the production of mucopolysaccharides, which are necessary for cartilage development [16]. Apart from osteogenicity, Mn2+ macrocyclic complexes have many biological properties. Various bacterial strains were utilized in the antibacterial test on Mn. It was observed that Mn-BCP showed outstanding antibacterial action against all of the bacteria examined. Gram-positive and Gram-negative pathogens were both strongly suppressed by MnBCP [17]. Mangiferin (MAN; 2-D-glucopyranosyl-1,3,6,7-tetrahydroxy-9H-xanthan-9-one), a naturally occurring polyphenol found in mango and papaya, is a natural immunomodulator. MAN is antiallergic, antidiabetic, antibacterial, antioxidant, immunomodulatory, and hypocholesterolemic and has some other health-promoting characteristics [18]. MAN also boosts the monocyte–macrophage system capacity and possesses an antibacterial effect against both Gram-positive and Gram-negative pathogens. MAN may be a viable alternative therapy for treating osteolytic bone disorders due to its anti-NF-κβ characteristics. MAN has also been shown to suppress bone apoptosis and the production of osteoclasts. MAN boosted the growth of human bone formation cells considerably, and there was no evidence of cytotoxicity. Moreover, MAN could stimulate the production of alkaline phosphate (ALP) inside human osteoblast cells [19,20]. The synthesis of $5\%$ and $10\%$ Mn-doped BCP-MAN scaffolds has been carried out in this investigation and the efficacy of mangiferin and manganese in terms of enhanced bone regeneration and antibacterial action has been described. ## 2. Materials and Methods Polyvinyl alcohol (PVA) was obtained from Labo Chemie Pvt. Ltd., Mumbai, India (degree of polymerization ~1700–1800 and hydrolysis ~98–$99\%$). Diammonium hydrogen phosphate ((NH4)2HPO4), calcium nitrate tetrahydrate (Ca(NO3)2.4H2O), manganese(II) chloride tetrahydrate (MnCl2.4H2O), and mangiferin (C19H18O11) were obtained from Merck Specialities Pvt. Ltd. (Mumbai, India), Sisco research laboratories Pvt. Ltd. (Mumbai, India), India and Himedia laboratories Pvt. Ltd. (Thane, India), respectively. Ammonia was obtained from the Sisco research laboratories Pvt. Ltd., India. All chemicals utilized in this study were of analytical grade. ## 2.1. Fabrication of Mn-BCP Porous Scaffolds The aqueous precipitation technique was adopted to fabricate $5\%$ and $10\%$ Mn-doped BCP scaffolds. Measured quantities of Ca(NO3)24H2O and MnCl2.4H2O were added dropwise to a (NH4)2HPO4 solution at room temperature maintaining a pH of 11. This white coloured product was thoroughly washed with deionized water and aged for 24 h and the solution was then filtered [21]. The resultant product was thermally processed for two hours at 1000 °C to yield Mn-BCP containing Mn-HAP and β-TCP. Next, the as-formed Mn-BCP powder was ground using a mortar and pestle and thereafter sieved to produce particles with a size less than 75 μm. For preparation of the scaffolds, fully reticulated polyurethane (PU) sponge was employed as a sacrificial template. Surface treatment of the sponge was carried out using a NaOH solution for about half an hour to increase its hydrophilicity, and templates of the PU sponges were carved into proper dimensions. PVA was mixed with water at a concentration of 0.1 mol/L to make a slurry. The $5\%$ and $10\%$ Mn-doped BCP powders were further mixed with the slurry in a 30:70 ratio by weight. PU sponges were cleaned and dried before being soaked into the Mn-doped BCP slurry and after uniform soaking, the PU sponges were lightly squeezed to remove excess slurry, and the leftover slurry was then blown with compressed air to achieve a uniform dispersion throughout the sponge. Before getting fired in an electric furnace (at 1200 °C for two hours), the MnBCP-coated sponges were dried at 37 °C for 48 h and then cooled at a rate of 5 °C/min until the temperature reached 25 °C [22,23]. The $5\%$ and $10\%$ Mn-doped BCP scaffolds were soaked in 1 μg/mL mangiferin mixed with dimethylsulfoxide (DMSO) and kept at 37 °C until completely dried. ## 2.2.1. X-ray Diffraction To carry out the phase characterization of the synthesized $5\%$ and $10\%$ Mn-doped BCP scaffolds, an X-ray diffractometer using Cu Kα radiation (λ = 0.154 nm) operated at 40 kV and 20 mA was employed for qualitative analysis. A scan speed of 2° per minute in the range of 10° ≤ 2θ ≤ 80° was used to record the XRD patterns. ## 2.2.2. Contact Angle Measurement The wettability of scaffolds was determined using Dulbecco’s modified Eagle’s medium (DMEM) cell culture media and simulated body fluid (SBF). Static contact angles of the immobilized liquid drops were assessed utilizing contact angle equipment at pH 7.2. ## 2.2.3. Water Uptake Capability The water absorption capability of the prepared scaffolds was tested by immersing a measured amount of the scaffold in distilled water for 2 h. Thereafter, the scaffolds were removed from the water, the excess water was removed, and their wet weight was calculated [24]. The following formula was used to determine the extent of water absorption: Water uptake capability (%) = Wet weight − dry weight /dry weight × 100 ## 2.2.4. Mechanical Property Measurement The mechanical properties of the scaffolds were measured at 3, 5, 7, 9, and 11 weeks after degradation and week 0 was used as the base of comparison. The degradation media was replaced every week throughout the degradation period. With the help of an electromechanical universal testing machine (SANSCMT4503, SANS, Shenzhen, China), the compressive strength was evaluated by crushing a 10 × 10 × 10 mm3 scaffold amid two flat platens possessing a ramp rate of 0.5 mm min−1. The compressive strength and modulus of scaffold yield were noted for comparison [25]. ## 2.2.5. Biodegradation in SBF By soaking the scaffolds in SBF at 37 °C, the biodegradability of the scaffolds was examined in vitro. At a solid/liquid ratio of 50 mg/mL, cylinder-shaped scaffolds were soaked in SBF for 1, 5, 10, 15, 20, and 25 days at 37 °C. All the samples were kept in a sealed plastic flask to prevent pH changes and microbial contamination. Throughout the experiment, the SBF solution was not refreshed. The immersed samples were then filtered, rinsed with deionized water, and dried at 40 °C for about four days before being weighed. The percentage of original weight was utilized to compute the weight loss. The weight loss and difference in pH were measured from five scaffolds, and the findings were reported as mean ± SD [22]. ## 2.2.6. Release of Mangiferin during In Vitro Degradation In the process of degradation, the scaffolds were taken for characterization at 0, 1, 2, 4, 6, 8, 10, 12, and 14 weeks, and the quantification of MAN release from the scaffolds was performed in vitro. After adding equal volumes of DMSO, MAN was extracted from the scaffold and subsequently centrifuged. High-performance liquid chromatography (Beckman, Brea, CA, USA) was employed for detection of MAN concentration [4]. ## 2.2.7. Ion Release To determine the ion release characteristics of $5\%$ and $10\%$ Mn-BCP-MAN scaffolds, 500 mg of the sample was immersed in 50 mL SBF. Particle-induced X-ray Emission (PIXE) was utilized to identify the increase of Ca2+ as well as Mn2+ in the body fluid over time [26]. ## 2.2.8. In Vitro Toxicity Testing Using MTT Assay In this investigation, the human osteoblast MG63 cell line (obtained from NCCS, PUNE) was used. These cells were incubated at 37 °C in a dehumidified environment containing $5\%$ CO2. DMEM (Invitrogen, Paisley, UK) was used to culture the cells, which was supplemented with $10\%$ foetal bovine serum (FBS, Invitrogen, Paisley, UK), 100 mg/mL streptomycin, and 100 U/mL penicillin. Every other day, the cultured media was changed. The MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) assay was used to quantify cell proliferation by detecting mitochondrial succinate dehydrogenase function and was utilized to investigate the cytotoxicity of the synthesized scaffolds. The obtained scaffolds were then fixed in the bottoms of 96-well cell culture plates and sterilized for 24 h at room temperature with ethylene oxide (ETO) steam; then, 1 mL of cell suspension was seeded uniformly on each sample. Every two days, the cultured medium was replaced with new medium. Following seeding for 1, 7, and 14 days, 100 mL of MTT (5 mg/mL) solution was added to each well and the detailed procedure was performed as per our previous work [27]. Measurements of four test runs were initiated to evaluate the mean value. The data were evaluated statistically to determine the mean and standard deviation (SD). ## 2.2.9. Microscopic Observation and Immunostaining The microscopic view of the scaffolds was performed using scanning electron microscopy (SEM) for qualitative analysis of the osteoblast cells along with determination of the pore dimensions of the scaffolds. For assessments using CLSM, colonized cells present on the scaffolds were fixed using $3.7\%$ paraformaldehyde for 20 min. Cell cytoskeletal filamentous actin (F-actin) was visualized by Alexa Fluor 488 Phalloidin (1:25 dilution in PBS, 1.5 h) treatment of cells and counter-staining with propidium iodide (1 μg mL−1, 20 min) for labelling of cell nuclei. The cultures were then placed in Vectashield and assessed using a Leica SP2 AOBS (Leica Microsystems, Wetzlar, Germany) microscope [28]. ## 2.2.10. Osteogenic Gene Expression To measure mRNA gene expression, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was utilised to analyse the osteogenic differentiation of MG63 cells on scaffold surfaces. Runt-related transcription factor X2 (RUNX2), osteocalcin (OCN), and type-1 collagen were computed using Bio-rad MyiQ2. Cells were cultured at a density of 4 × 104 per well for 1, 7, and 14 days before being lysed with TRIZOI (Invitrogen, Waltham, MA, USA) to obtain RNA. To acquire enough RNA, cells from all scaffolds in each group were used. A total of 1 mg of RNA was reverse transcribed to complementary DNA (cDNA) using the superscript II first-strand cDNA synthesis kit [29]. ## 2.2.11. Alkaline Phosphatase (ALP) Assay Osteoblast cell differentiation was estimated by ALP activity. Osteoblast cells were lysed in a buffer solution containing $0.05\%$ Triton X-100, $1.0\%$ Tris, and $6.0\%$ NaCl (w/v in deionized water, pH 10.0. All the chemicals were procured from Sigma Aldrich (St. Louis, MI, USA). A volume of 60 µL of scaffold specimen solution was added to 50 µL of $0.07\%$ p-nitrophenylphosphate (w/v, Thermo Fisher, Waltham, MA, USA) in amino methyl propanol (AMP, Acros Organics, Pittsburgh, PA, USA) buffer and then the resulting solution was placed in an incubator for 2 h at 37 °C. The absorbance was recorded at 400 nm. ALP activities were normalized to the ALP activity/µg of the entire DNA content [27]. ## 2.2.12. Bacterial Viability Test The antibacterial study of the $5\%$ and $10\%$ Mn-doped BCP-MAN scaffolds was carried out using *Staphylococcus aureus* (S. aureus). Mueller–Hinton Broth (MHB) medium was used to culture the bacteria. The MTT assay was utilized to assess bacterial viability in vitro. The detailed procedures were followed as per our previous work [30]. ## 2.3. Statistical Analysis The SPSS (V 22) statistical analysis software was used to perform statistical analyses on the collected data. The mean ± standard deviation was used to express all of the experimental outcomes except XRD, SEM, and CLSM. One-way analysis of variance (ANOVA) was used to compare the changes in the data. A p value < 0.05 was considered statistically significant in all the studies. ## 3.1. X-ray Diffraction The XRD pattern of $5\%$ Mn-BCP and $10\%$ Mn-BCP are shown in Figure 1. In the synthesized Mn-BCP scaffolds, Mn-HA and β-TCP peaks were present and are quite similar to the stoichiometric HA diffraction peaks (JCPDS no. 9-0432) and (JCPDS no. 9-0169), respectively. The doped Mn-BCP nanoparticles did not show any additional impurities, according to the XRD pattern. ## 3.2. Contact Angle Measurement In both media, the $10\%$ Mn-BCP-MAN scaffold had lower contact angles than the $5\%$ Mn-BCP-MAN scaffold (Figure 2). Further investigation revealed that DMEM contact angles of the $5\%$ Mn-BCP-MAN scaffolds were as low as 42° ± 2.04, whereas SBF contact angles were 48° ± 2.44. Meanwhile, DMEM and SBF had contact angles of 35° ± 1.81 and 41° ± 2.06 for $10\%$ Mn-BCP-MAN, respectively. ## 3.3. Swelling Ratio The water uptake capability of the soaked scaffolds after different soaking periods of 0, 1, 4, and 7 days is depicted in Figure 3. A significant change in swelling ratios of the scaffolds was observed. The swelling was higher in $5\%$ Mn-BCP-MAN scaffolds (287 ± 14), but it decreased to 253 ± $13\%$ for $10\%$ Mn-BCP-MAN scaffolds. ## 3.4. Mechanical Property of the Scaffold Compressive strength (Figure 4) and modulus (Figure 5) of the scaffolds were estimated from week 0–11 after degradation. The in vitro compressive strength and modulus at yield considerably decreased in the BCP scaffolds with time. However, BCP-MAN scaffolds with different Mn concentrations did not exhibit any change in the above tests. ## 3.5. Degradation It can be seen that the rate of degradation of both the scaffolds increased as the soaking period increased (Figure 6). The $10\%$ Mn-BCP-MAN scaffold show a lower deterioration rate in comparison to $5\%$ Mn-BCP-MAN scaffolds. Within the time period of one week, $10\%$ Mn-doped BCP scaffolds lose less weight than $5\%$ Mn-doped BCP scaffolds. The biodegradation ratio reduced as the concentration of Mn increased from $5\%$ to $10\%$. ## 3.6. In Vitro Release of Mangiferin from Scaffolds The release of MAN was closely linked with the concentration of Mn present in $5\%$ and $10\%$ Mn-BCP-MAN scaffolds. The total release of MAN was estimated to be about $90\%$ for each sample (Figure 7). MAN exhibited a fast release from Mn-BCP-MAN ($5\%$ and $10\%$) scaffolds in the 1st week and steadied within 2 weeks of release. There seemed to be little difference between $5\%$ Mn-BCP-MAN and $10\%$ Mn-BCP-MAN scaffolds as far as MAN was concerned. The amount of MAN released from $5\%$ Mn-BCP-MAN (MAN: 96 µg/10 mg) and $10\%$ Mn-BCP-MAN (MAN: 93 µg/10 mg) scaffold in the degradation media were similar at the end of two weeks of degradation. In vitro release of MAN was detected after the 14th week of degradation. ## 3.7. Ion Release The antibacterial property of the scaffold surface can be revitalized over time by the bioactive Mn ions released by the scaffolds. The ion release behaviour of the $5\%$ and $10\%$ Mn-BCP-MAN scaffolds were studied by immersing the scaffolds in SBF at 37 °C, and ion release was measured using PIXE at various time points. Mn ions were liberated from the scaffolds after 12 h at a concentration of 64 ppm and 79 ppm from $5\%$ Mn-BCP-MAN and $10\%$ Mn-BCP-MAN scaffolds, respectively. The liberated Mn ions play an important role in enhancing the antibacterial properties of Mn-doped BCP-MAN scaffolds. ## 3.8. MTT Assay The MTT assay was used to examine MG63 cell viability on $5\%$ and $10\%$ Mn-BCP-MAN scaffolds. The cell density of both the scaffolds was evaluated after culturing for 1, 7, and 14 days, as shown in Figure 8. Pure BCP was used as the control specimen. On day 1, cell viability of the $10\%$ Mn-BCP-MAN scaffold was modest, but on days 7 and 14, the cell proliferation rate was higher than the $5\%$ Mn-BCP-MAN scaffold. For all cultured days, the statistical analysis resulted in a significant difference ($p \leq 0.05$) in cell density between the $5\%$ and $10\%$ Mn-doped BCP-MAN scaffolds. ## 3.9. SEM and CLSM Observation Assessment of the $10\%$ Mn-BCP-MAN scaffold by SEM (Figure 9a) and CLSM (Figure 9b) on the 14th day of culture exhibited elongated cells spread throughout the scaffold surface by establishing cell-to-cell contacts on $10\%$ Mn-BCP-MAN. Adherent cells seemed to be well spread with elevated cytoplasmic volume and higher amounts of fibrillar projections. Moreover, the cells showed a well-aligned F-actin cytoskeleton having intense staining at the boundaries of cells with the appearance of prominent nuclei and cell division [31]. ## 3.10. Osteogenic Gene Expression *Osteogenic* gene expression was used to assess the differentiation of MG63 cells on both $5\%$ and $10\%$ Mn-BCP-MAN scaffolds. Pure BCP was used as the control specimen. The expression level of osteogenic genes of COL1A1 (Figure 10), RUNX2 (Figure 11), and OCN (Figure 12) increased from day 1 to day 14 for MG63 cells on both $5\%$ and $10\%$ Mn-BCP-MAN scaffolds. In comparison to the $5\%$ Mn-BCP-MAN scaffold, the $10\%$ Mn-BCP-MAN scaffold demonstrated greater gene expression levels ($p \leq 0.05$). Table 1 shows the forward and reverse primers for quantification of expression of the relevant genes. ## 3.11. ALP Activity Measurement of ALP activity was carried out to assess the capability of the scaffolds to accelerate osteoblast cell differentiation (Figure 13). Pure BCP was used as the control specimen. After 7 days of culture, osteoblast cells in contact with the $5\%$ Mn-BCP-MAN scaffold surface exhibited insignificant ALP activity compared to those on the $10\%$ Mn-BCP-MAN scaffolds ($p \leq 0.05$). However, after 14 days of culture, there seemed to be significantly higher ALP activity on $10\%$ Mn-BCP-MAN scaffolds than the $5\%$ Mn-BCP-MAN scaffolds. ## 3.12. Bacterial Viability At 490 nm, optical density measurements were used to examine the activity of S. aureus. The data were compiled in 10 h intervals until 30 h. Bacteria growth was monitored on pure BCP control scaffold, $5\%$ Mn-BCP-MAN scaffold, and $10\%$ Mn-BCP-MAN scaffold. During the initial 10 h, there was an insignificant decrease in bacterial cells, but bacterial count exponentially decreased as the time period increased from 20 h to 30 h. In the $10\%$ Mn-BCP-MAN scaffold, there was a significant decrease in bacteria cell count, as illustrated in Figure 14. ## 4. Discussion Mn-BCP-MAN comprises balanced combinations of a non-resorbable phase (Mn-HAP) and resorbable phase (β-TCP) that frequently demonstrate increased bioactivity, and satisfactory antibacterial properties together with good mechanical strength, which cannot be achieved by a single-phase biomaterial. The diverse action of naturally occurring MAN at the cellular as well as molecular level offers vital knowledge for its usage as a potential osteoporotic agent. It has been established that MAN suppresses the formation of bone resorption cells by inhibiting RANKL-induced activation of NF-kβ and ERK I ligand. Moreover, it enhances the development of bone formation cells by raising OCN, COL1A1, and RUNX2 expression levels [31]. The effectiveness of a sustained-release MAN scaffold in the treatment of diabetic alveolar bone defects was analysed in an earlier study. The resulting scaffolds exhibited porous architectures, possessing pores 111.35 to 169.45 μm in size. Average pore size decreased with increasing PLGA content. Increased drug content was produced by either a decrease in PLGA concentration or an increase in MAN concentration [32]. In in vitro models, the MAN-loaded scaffolds prevented the decline in cell viability due to diabetes. Additionally, healing of delayed alveolar bone defects was improved with enhanced bone regeneration in diabetic mice. Another study was carried out to find out whether treatment of MC3T3-E1 cells with MAN could protect the cells against dexamethasone-induced toxicity. The outcomes showed that incorporation of MAN greatly reduced the effects of dexamethasone on cell viability of MC3T3-E1 cells and levels of ALP activity. Increased OCN is a characteristic of osteogenic differentiation, and ALP activity is regarded as an early marker of this differentiation [33]. In summary, it can be concluded that MAN could be used to treat significant bone disorders. Figure 1 depicts the XRD pattern from which it was evident that Mn-doped BCP did not show any impurities because of the absence of additional diffraction peaks. The $10\%$ Mn-BCP scaffold showed higher crystallinity as compared to its $5\%$ Mn-BCP counterpart. Although $5\%$ Mn-BCP showed a further increase in the intensity of the β-TCP peak while decreasing the intensity of the HAP peak, the highest amount of β-TCP was detected in this specimen as compared to its $10\%$ Mn-BCP counterpart. These phenomena could be explained by the Mn solubility limit in HAP. The $5\%$ Mn-BCP likely resulted in the production of β-TCP in terms of the second phase; however, a concentration of Mn > 5 mol%, stabilizes the HAP phase, thereby preventing the formation of the subordinate phase. Furthermore, the decrease in the β-TCP peak leads to an enhancement of the HAP peak as the concentration of manganese increases in BCP [34]. The enhancement in the β-TCP peak intensity of Mn concentration to 5 mol% can be attributed to the incorporation of Mn2+ ions at the Ca2+ ion site in the β-TCP phase. Calcination of Mn-doped BCP at 1000 ℃ stabilizes its phase structure, and this phenomenon explains the decomposition of the structural phase [16]. The intensity of the β-TCP peak marginally deviated to a higher angle of 2θ with an increase in the concentration of Mn, but no change was observed in the HAP peaks. This finding demonstrated that doping of Mn favours the TCP phase over the HAP phase [35]. On the other hand, $5\%$ Mn-doped BCP-MAN exhibited a large contact angle due to its lower hydrophilicity when compared with $10\%$ Mn-BCP-MAN scaffolds. The wettability of the specimens influences cell proliferation, differentiation as well as cell adhesion on the biomaterial surface. Furthermore, an increase in Mn concentration in the scaffold results in decreased contact angles [36]. The swelling ratio of the scaffold is used to estimate impact on cell activities like cell proliferation, growth, and adhesion [37]. The swelling ratio was found to be >$100\%$ for all the synthesized samples, thereby stimulating cell development on the scaffold. However, micro, as well as macro pores were present in the synthesized scaffolds for both the $5\%$ and $10\%$ Mn-BCP-MAN scaffolds. The number of macropores was abundant, showing that water absorption increases with an increase in pore size [38]. The newly generated bone is envisaged to substitute the $5\%$ and $10\%$ Mn-BCP-MAN scaffolds and show better mechanical strength because of the presence of higher amount of Mn in it. An ideal scaffold should have a controlled biodegradation rate, which is related to the bone remodelling speed. Enhanced osseointegration should supply ample mechanical strength for the regeneration. During the resorption process, the mechanical strength of the scaffolds must be retained until the implantation area is totally replaced by the host tissues so that it can resume its structural role [39]. According to the literature [11], the dissolution rate of β-TCP is higher inside the body environment in comparison to HAP. The degradation rate of all our synthesized scaffolds was slow and both the specimens demonstrated a consistent degradation rate, which differs from the literature. Ca and P, as the major mineral components of HAP, exhibit critical functions in accelerating and retarding osteoblast and osteoclast activities. Both 2–4 mmol (low) and 6–8 mmol (medium) content of Ca2+ ions are favourable for osteoblast proliferation, differentiation, and extracellular matrix remineralization. On the other hand, P seems to perform as a subordinate in osteoblast proliferation as well as differentiation [12]. The Mn-BCP-MAN scaffold was soaked in SBF at 37 °C, and ion content was measured using the PIXE technique for different time periods to explore its ion release properties. The release of Mn2+ ions aids in the stimulation of osteoinductivity along with the antibacterial activities of Mn-BCP-MAN scaffolds [40]. Furthermore, the amounts of β-TCP and Mn-doped HAP in the scaffolds regulate cell viability as well as functionality. In the initial phases of the experiment, according to the MTT assay, the survival rate of MG63 cells suggested its cytotoxic nature. On the 14th day, however, the survival rate of MG63 cells on the $10\%$ Mn-BCP-MAN scaffold was comparatively higher than those on the $5\%$ Mn-BCP-MAN scaffold. Thus, the presence of MAN affects the cell proliferation rate. CLSM observation exhibited organized cellular activities. This behaviour is appropriate as far as biological activities on the scaffolds is concerned, i.e., since the F actin cytoskeleton, that is highly concentrated below the plasma membrane, gives structural strength and elasticity to the cell that undergoes adaptation to the scaffold structure. Moreover, the F-actin cytoskeleton is a primary candidate in the mechano-transduction mechanism of cells that modulates complex signalling pathways that are mandatory to the next stages of osteoblast proliferation and differentiation [41] The qRT-PCR technique was carried out in order to investigate the osteogenic gene expression of MG63 cells for COL1A1, RUNX2, and OCN. Throughout proliferation as well as matrix maturation stages of osteoblastic cell development, COL1A1 is considered an early-stage marker. On the 7th and 14th day, the osteogenic gene expression for COL1A1 of osteoblast cells on the $10\%$ Mn-BCP-MAN scaffold was higher than the $5\%$ Mn-BCP-MAN scaffold, indicating that the presence of MAN results in increased proliferation as well as differentiation rate. OCN is regulated via RUNX2 and is a RUNX2 target gene [42]. OCN is termed a late-stage gene marker. The presence of MAN significantly boosts RUNX2 transcriptional activity, as discussed by Peng et al. [ 43]. However, the results revealed that, in the presence of antimicrobial Mn2+ ions, the level of gene expression decreased. Because of the higher antibacterial efficacy of Mn, less bacterial cells were viable in the $10\%$ Mn-BCP-MAN scaffold compared to those in the $5\%$ Mn-BCP-MAN scaffold [44]. Relating to the osteo-inductive property of the scaffolds, the ALP activity of osteoblast cells on both the scaffolds on day 7 showed the least variation. 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--- title: 'Barbed Dental Ti6Al4V Alloy Screw: Design and Bench Testing' authors: - Keila Lovera-Prado - Vicente Vanaclocha - Carlos M. Atienza - Amparo Vanaclocha - Pablo Jordá-Gómez - Nieves Saiz-Sapena - Leyre Vanaclocha journal: Materials year: 2023 pmcid: PMC10054258 doi: 10.3390/ma16062228 license: CC BY 4.0 --- # Barbed Dental Ti6Al4V Alloy Screw: Design and Bench Testing ## Abstract Background context. Dental implants are designed to replace a missing tooth. Implant stability is vital to achieving osseointegration and successful implantation. Although there are many implants available on the market, there is room for improvement. Purpose. We describe a new dental implant with improved primary stability features. Study design. Lab bench test studies. Methods. We evaluated the new implant using static and flexion–compression fatigue tests with compression loads, 35 Ncm tightening torque, displacement control, 0.01 mm/s actuator movement speed, and 9–10 Hz load application frequency, obtaining a cyclic load diagram. We applied variable cyclic loadings of predetermined amplitude and recorded the number of cycles until failure. The test ended with implant failure (breakage or permanent deformation) or reaching five million cycles for each load. Results. Mean stiffness was 1151.13 ± 133.62 SD N/mm, mean elastic limit force 463.94 ± 75.03 SD N, and displacement 0.52 ± 0.04 SD mm, at failure force 663.21 ± 54.23 SD N and displacement 1.56 ± 0.18 SD mm, fatigue load limit 132.6 ± 10.4 N, and maximum bending moment 729.3 ± 69.43 mm/N. Conclusions. The implant fatigue limit is satisfactory for incisor and canine teeth and between the values for premolars and molars for healthy patients. The system exceeds five million cycles when subjected to a 132.60 N load, ensuring long-lasting life against loads below the fatigue limit. ## 1. Introduction Tooth loss, and bone degradation associated with traumas and age-related degeneration, are important public health problems [1]. Bone density decreases after age 30, resulting in a reduction of up to $40\%$ in mechanical resistance [2]. Moreover, osteoporosis is common in older adults [3] and likely contributes to tooth loss. Dental implants are designed to replace the root of a missing tooth [4] and serve to hold the new artificial tooth in its correct position [5]. These implants are a safe and durable solution for the loss of one or more teeth. Researchers have developed countless dental implants and insertion techniques to meet a wide variety of patients’ medical conditions [6,7,8]. Unfortunately, the presence of osteoporotic bone reduces success with dental implants due to loosening [9]. Odontologists have developed implants based on titanium [10], tantalum [7], and zirconia [11], among others. These bioinert materials show contact osteogenesis, so the implant’s union with the bone is mainly mechanical, producing so-called “biological fixation” [12]. As a result, the bone grows orderly in direct contact with the implant but does not fix to it [13]. Titanium-based implants are advantageous because of osseointegration, namely a structural and function connection between implant and bone. Titanium’s other advantages include relatively easy manufacturing and high mechanical resistance. Not surprisingly, most dental implants are made from titanium [8,14]. Other important properties are its biocompatibility and high corrosion resistance [15]. Implant surface roughness and porosity foster osseointegration, particularly needed in the case of osteoporotic edentulous patients [16]. Surface porosity allows bone tissue growth within the implant, integrating it with the bone, which makes it possible to ensure secondary stability [10,17]. Porous structures are also highly osteoconductive, with fast vascularized fibrous tissue invasion and substantial accelerated (by three to five times) incorporation into surrounding bone compared to other rough surfaces [18]. The pores act in two ways [19]: mechanical coupling with nearby bone and, on the other hand, directly and indirectly influencing the cells’ metabolism [17]. Pre-osteoblasts show a kind of “poro-philia”, i.e., increased gene expression, differentiation, and mineralization related to signals received from the implant’s surface [20]. Implants with complex porous structures are most easily manufactured using 3D-printing technology. Primary stability is a third crucial dental implant feature, which is essential for optimal long-term osseointegration [6]. Once said stability takes place, its quality is important, as well as how fast and biomechanically strong it can be, depending in most cases on the presence of suitable anchoring systems [21,22]. The implant itself must be strong to avoid breakage. Considering the above discussion, we developed a new dental implant whose primary anchoring system is based on clockwise threading. Two outgoing legs deployed by a screw provide secondary stability. Additionally, this dental implant has a porous structure to enhance osseointegration. The mechanical goals of the implant are [1] to provide an immediate anchor to the cortical bone once inserted and [2] a porous surface that allows bone on-growth and in-growth. This design should enable good primary stability in older patients with osteoporosis and type IV bone [23] as well as adequate long-term osseointegration. Once we designed the dental implant and decided on its material, titanium, manufacturing it was the next challenge. Additive 3D printing from a 3D CAD file is a good alternative when manufacturing an object with complex geometry and a relatively small size, such as our dental implant [24,25]. To evaluate the mechanical characteristics of our dental implant, we performed static and flexion–compression fatigue tests. ## 2. Material and Methods The device was manufactured out of a grade five titanium alloy (Ti6Al4V, elasticity module 1100 MPa) and has three components: the dental implant body, the barrette, and the deployment screw. The dental implant body consists of [1] an implant–abutment connection thread in the implant’s head, [2] two anchoring system exit holes, [3] a double thread with a 1 mm pitch to facilitate implant insertion, [4] a self-drilling tip thread, [5] a porous zone to improve osseointegration, [6] a 16° angle hexagonal implant–abutment connection with Morse taper fixation to guarantee optimal connection sealing, and [7] an internal thread for anchor insertion and attachment connection (Figure 1). The two implant body exit holes are opposite each other, corresponding to the arrangement of the deployable wings of the anchorage. The implant body has a porous, trabecular-shaped structure in the middle area of the external thread. The external threaded area is a double 1 mm thread to reduce bone removal during implant insertion, reduce heat generation, and improve torque insertion in low-density bone. The implant body self-drilling tip allows changing the implant’s orientation during insertion, thus enabling correct parallelism between implants, and optimizing their placement. The implant–abutment connection area has an angle of 16° to reduce the friction between the walls. The implant–abutment connection uses a Morse taper fixation to reduce the micro gap between the implant and the abutment connection, minimizing bacterial microleakage, decreasing bone tissue reabsorption, and stabilizing soft tissues with a better long-term aesthetic result. In addition, this connection type absorbs the vibration and pressure exerted on the abutment, minimizing the potential for prosthetic screw loosening. The upper hole connects the anchor itself and the insertion screw. The deployment screw has a hexagonal head connection, a shank, and a thread. The thread allows the screw to move in and out inside the implant (Figure 1, number 7), pushing the barrette externally. The shank connects the screw with the barrette, and the hexagonal connection facilitates screw manipulation, dental implant insertion, and removal using the corresponding instruments (Figure 2). The barrette is inserted into the implant body. When the deployment screw is threaded in, the barrette’s legs bend outwards and protrude through the implant’s holes mentioned above (Figure 3). These two legs support against the mandible or maxilla cortical walls, and a clip at its center connects it with the screw. With the assembly in position, as shown in Figure 4D, the deployment screw is threaded into the implant body’s internal channel. Then, the barrette’s legs bend and expand outside the implant, holding against the lateral and medial mandibular and maxilla cortical bone (Figure 4E). The barrette’s legs inside the dental implant body can be recovered by inverting the process and unscrewing the deployment screw. The barrette’s legs are 1.5 mm in diameter, have a blunt tip on both sides, and extend 4 mm from the implant once deployed (Figure 5). We can insert the abutment or cover screw once the deployment screw is fully inserted and secured, and the barrette’s legs are deployed. This cover screw holds the artificial tooth in place. The implant is patented in Spain, the USA (Patent number $\frac{16}{956594}$), and Brazil. The implant barrette and the dental implant body were additively manufactured to achieve the middle zone porosity of the latter (Figure 6). Next, we machined the implant body’s internal thread as well as the deploying screw and gave it an Allen hexagonal head. Figure 7 shows the set implanted to replace an incisor tooth in a human jaw reconstructed using a 3D simulation program. ## Implant Testing We evaluated our implant through static and flexion–compression fatigue tests, following the UNE-ENISO 14801:2017 standard “Dentistry. Implants. Dynamic fatigue test for endosseous dental implants” [26]. All testing was performed using an INSTRON $\frac{8874}{135}$ universal testing machine (Norwood, MA, USA) at 22 °C and $58\%$ humidity. For the test, we used three components: the dental implant, a universal conical base connection RP 3 mm REF 38217 (Nobel Biocare, Zürich, Switzerland), and a securing screw (Figure 8A–C, respectively). We inserted the dental implant into a polymethyl methacrylate resin with bone-like rigidity. We placed this construct inside the stainless-steel machine clamp between the testing machine actuators, applying compression loads as shown in Figure 9. The tightening torque applied to the implant connection screw was 35 Ncm. We performed the test by displacement control, 0.01 mm/s actuator movement speed, and the test end condition was implant failure. We defined the bending moment as M = sin30 × 11 × F, M = bending moment and F = force. We applied cyclical loads through a haversine (rectified sine) with the amplitude, preload, and maximum load values indicated in Table 1. The load application frequency was 9–10 Hz. First, we constructed a cyclic load diagram (S-N Wohler curves) [27] to evaluate the assembly’s flexion–compression fatigue resistance. Then, we tested the implants at variable cyclic loading of predetermined amplitude and recorded the number of loading cycles until failure. The test was performed by flexion–compression force control, applying cyclical loads using a haversine (rectified sine) with amplitude, preload, and maximum load. The end of the test was either the implants’ components’ failures (breakage or permanent deformation) or reaching 5 million cycles for each load value. We tested thirty-five dental implants. ## 3. Statistical Analysis We used R software ((R Development Core Team 2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, URL https://www.R-project.org, accessed on 1 January 2022) in combination with the Deducer user interface library (I. Fellows, “Deducer: A Data Analysis GUI for R”, Journal of Statistical Software, 2012; 49[8]: 1–15, doi:10.18637/jss.v049.i08) [28]. We calculated the mean and standard deviation. We considered them statistically significant values if $p \leq 0.005.$ ## 4. Results In the geometric arrangement indicated in the ISO 14801:2017 standard, mean (SD) values for stiffness were 1151.13 ± 133.62 N/mm, at an elastic limit force of 463.94 ± 75.03 N and displacement of 0.52 ± 0.04 mm. The mean failure force was 663.21 ± 54.23 N, and dental implant displacement failure occurred at a mean of 1.56 ± 0.18 SD mm. Implant failures were either permanent connection system deformations or dental implant ruptures (Figure 10). We show below the charge cycle diagram. Our dental implants (screw plus barrette deployed) had an elastic force limit of 463.94 ± 75.03 SD N and a failure force of 663.21 ± 54.23 N. Figure 11 shows the S-N Wholer curve results. The fatigue limit (maximum loads at which failure does not occur for infinite loading cycles of trial limit) was 132.6 ± 10.4 N. In the geometric arrangement indicated in the ISO 14801:2017 standard, the maximum bending moment was 729.3 ± 69.43 mm/N. Table 2 shows the number of cycles the dental implant supported for each load. All failures during cyclic loading occurred at the actuator–implant interface, not the implant itself. ## 5. Discussion We designed a dental implant prototype optimized for use in patients with grade IV osteoporotic bone, which is prevalent in the elderly population [29]. The discussion below highlights key design features that may be advantageous. We are unaware of any other dental implant that rests in the mandible or maxilla lateral cortical bone [14], improving the primary fixation capacities. Titanium, the material selected for our implant, is used in $91\%$ of dental implants [14,15]. While zirconia might have better osseointegration [8,11] it is less resistant to permanent failures (cracking) [30]. Similarly, while porous tantalum has greater biocompatibility, lower corrosion, and greater porosity than titanium [7], resulting in a greater osseointegration capacity [7,31], manufacturing dental implants with tantalum is technically cumbersome [32]. Only one tantalum implant is available in the EU market, and this implant is a combination of tantalum and titanium [7]. In addition, we have found no data on the mechanical resistance of other porous dental implants to compare with ours. Dental implant design dramatically impacts primary stability and long-term osseointegration [6,33], therefore reinforcing fixation elements is advisable in osteoporotic bone [16]. Expandable [21] or barbed [34] designs are important improvements compared to simpler implants, and our implant follows this path. In addition, the double-external thread and the two-barrette leg improve our implant’s primary stability. Like the implant used by Bencharit et al. [ 7], our implant’s middle implant body porosity is designed to improve osseointegration. The primary advantage of titanium is reduced manufacturing costs [35]. Our dental implant’s double 1 mm thread external threaded area increases the space between the thread pitches, removes less bone during implant insertion, reduces the heat generated during insertion, and improves the insertion torque in low-density osteoporotic bone. These features are advantageous [36,37]. Our dental implant–abutment connection area has an angle of 16° because when two conical metal parts fit together with an angle of 8° or less, a wedge effect is produced due to the friction between the two walls [38]. The implant–abutment Morse taper fixation connection area, which we used in our dental implant, reduces the micro gap between the implant and abutment connection since it increases the contact surface between them. This feature minimizes bacterial microleakage [39], decreases bone tissue reabsorption [40], and stabilizes soft tissues [41] with a better long-term aesthetic result [42]. In addition, the Morse cone connection absorbs the vibration and pressure exerted on the abutment, avoiding loosening the prosthetic screw [43]. The major issue faced by any dental implant is resistance to daily chewing forces. The first issue is the force any dental implant must stand daily. Scientific reviews have analyzed the maximum chewing forces and compared these with the static tests, reporting a vast variation depending on the age, sex, measurement system, and measurement method used [44,45,46]. In addition, as people age, osteoporosis is commonplace, markedly influencing primary and secondary implant stability with a concomitant loss of resistance to chewing force [47,48]. The mean reported values for the maximum occlusal force in the intercuspal position are 511.7 N for men and 442.4 N for women [49]. With aging, these forces decrease somewhat (391 N and 203 N, respectively) [50]. The maximum bite force in the molars of female patients with osteoporosis was 117 N and 230 N for those without this medical condition [47]. In male patients, these values are near twice that of their female counterparts (≈240 N). This maximum force value of 240 N for patients with osteoporosis is much lower than the elastic limit and failure force obtained in the static test of our dental implant (663.21 ± 54.23 N). Thus, our implant has sufficient properties compared to these forces. The reported chewing forces found peak values between 5 and 54 N for incisor and canine [51,52,53,54,55] and 50 and 284 N for premolars and molars [53,54,56]. Our dental implant fatigue limit is 132.60 ± 10.4 N, higher than the occlusal force reported for incisor and canine teeth, but between occlusal force values for premolars and molars for healthy patients. *The* general estimation is that one million cycles are equivalent to a year of everyday chewing (365 days, three meals a day, chewing 15 min per meal at 1 Hz, and 60 chews per minute), so the testing performed covers an implant life of at least five years [57]. In addition, the standard itself (ISO 148201:2017) determines the maximum load at which failure does not occur with an infinite (in practice, very large) number of cycles. Therefore, the standard assumes everlasting life, provided the load does not exceed the limit. This phenomenon corresponds to other authors’ infinite fatigue life criterion [58]. This study has allowed us to verify that our dental implant manufacture and functionality are possible, meeting the resistance, stability, and elasticity standards expected for any dental implant. However, we need live animal tests and human clinical studies to confirm these data. ## 6. Strengths and Limitations Our study was performed following international standards and with certified, calibrated equipment. However, our study has some limitations, First, the number of tested dental implants (thirty-five) was limited. Second, testing did not address bruxism, i.e., sideways mandible movements. We attempted to simulate this condition by applying loads at a 16° angle, but this might not entirely reproduce the clinical scenario. ## 7. Conclusions A new dental implant designed for placement in osteoporotic bone showed adequate results when tested against ISO 14801. Specifically, the elastic assembly limit resulting from the static test was 463.94 Nm, and the mean maximum failure force value is 663.21 N. The implant, abutment, and screw set fatigue limit was 132.60 N. These results are satisfactory for incisor and canine teeth but between the values for premolars and molars for healthy patients. The system subjected to the 132.60 N load level exceeded the five million cycles stipulated by the standard. 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--- title: HIV Tat Expression and Cocaine Exposure Lead to Sex- and Age-Specific Changes of the Microbiota Composition in the Gut authors: - Lu Li - Xiaojie Zhao - Johnny J. He journal: Microorganisms year: 2023 pmcid: PMC10054272 doi: 10.3390/microorganisms11030799 license: CC BY 4.0 --- # HIV Tat Expression and Cocaine Exposure Lead to Sex- and Age-Specific Changes of the Microbiota Composition in the Gut ## Abstract The balance of microbial communities in the gut is extremely important for normal physiological function. Disruption of the balance is often associated with various disorders and diseases. Both HIV infection and cocaine use are known to change the gut microbiota and the epithelial barrier integrity, which contribute to inflammation and immune activation. Our recent study shows that Tat expression and cocaine exposure result in changes of genome-wide DNA methylation and gene expression and lead to worsen the learning and memory impairments. In the current study, we extended the study to determine effects of Tat and cocaine on the gut microbiota composition. We found that both Tat expression and cocaine exposure increased Alteromonadaceae in 6-month-old female/male mice. In addition, we found that Tat, cocaine, or both increased Alteromonadaceae, Bacteroidaceae, Cyanobiaceae, Erysipelotrichaceae, and Muribaculaceae but decreased Clostridiales_vadinBB60_group, Desulfovibrionaceae, Helicobacteraceae, Lachnospiraceae, and Ruminococcaceae in 12-month-old female mice. Lastly, we analyzed changes of metabolic pathways and found that Tat decreased energy metabolism and nucleotide metabolism, and increased lipid metabolism and metabolism of other amino acids while cocaine increased lipid metabolism in 12-month-old female mice. These results demonstrated that Tat expression and cocaine exposure resulted in significant changes of the gut microbiota in an age- and sex-dependent manner and provide additional evidence to support the bidirectional gut–brain axis hypothesis. ## 1. Introduction Up to 100 trillion [1014] microbes colonize in human gut and are collectively called gut microbiota [1,2]. There are about 2200 species and 12 phyla, which mostly fall into four phyla: Protebacteria, Firmicutes, Actinobacteria, and Bacteroidetes [3,4]. They are believed to originate at birth and evolve over the course of biological ageing [5,6,7,8,9]. *Host* genetics, environment, and lifestyle contribute to the changes of their composition [4,10,11]. The dynamic crosstalk between these microbes and the host also affects the host’s health [1,10]. The balance of various microbial communities in the gut plays a fundamental role in normal physiological functions such as breakdown of food for absorption, protection against pathogens, elicitation of immunity, and maintenance of the barrier integrity of the gut and intestines [12,13,14]. Thus, disruption of the balance, also known as dysbiosis, is often associated with various disorders and diseases such as cancer, viral infection, and abnormal behaviors [2,15,16,17,18,19]. Microbes, their metabolites such as short-chain fatty acids, their structural components lipopolysaccharides (LPS), and hormones released by gut epithelial enteroendocrine cells can all function to mediate the interactions between the microbiota and the host [2,20]. Early HIV infection and replication in gut-associated lymphoid tissues result in massive CD4 T cell depletion and compromised epithelial barrier and gut immunity and as a result, direct translocation of gut microbes and their products such as LPS into the circulatory system and subsequent systemic inflammation and immune activation [21,22,23,24,25]. HIV infection is also associated with decreased abundance, composition, and diversity of gut microbiota. These changes in turn contribute to persistent inflammation and microbial translocation, dysfunctional metabolism of the host, and HIV disease progression and reservoir size [26,27,28,29,30]. Importantly, antiretroviral therapy does not fully restore the integrity of the gut epithelial barrier and the disrupted gut microbiota that result from HIV infection despite its potent suppressive effects on HIV replication [27,31]. HIV infection, antiretroviral therapy, and changes in gut microbiota have all been linked to HIV comorbidities including metabolic, cardiovascular, and neurocognitive disorders [32,33,34,35,36,37]. In the era of antiretroviral therapy, mild cognitive and motor disorder has become the most common clinical manifestation of HIV-associated neurocognitive disorders (HAND), characterized by persistent neuroinflammation [38,39,40]. HIV viral protein *Tat is* a major pathogenic factor for HAND and neuroHIV, as its expression in the brain of doxycycline (Dox)-inducible astrocyte-specific HIV Tat transgenic mice (iTat) in the absence of HIV infection leads to locomotor, learning and memory deficits [41,42,43,44,45,46,47,48,49,50,51,52], and astrocyte/microglia activation, chronic neuroinflammation and loss of neuronal integrity [43,48,50,51,53], the consistent neurological and neuropathological hallmarks of HAND and neuroHIV in the era of antiretroviral therapy. Tat is present in the brain of HIV-infected people who are under active antiretroviral therapy [54,55,56]. Several studies suggest gut microbiota as a potential source of the persistent neuroinflammation. Specific gut microbiota signatures, elevated LPS, and systemic immune activation are associated with the severity of HAND [36,57,58], while supplementation of gut microbiota with probiotics decreases neuroinflammation and improves neurocognitive function in the context of HIV infection [59,60]. Use/abuse of substances such as cocaine, methamphetamine, and opioids constitute a major risk factor for HAND [61,62,63], while it alters the gut microbiota and permeability and increase inflammation [64,65,66,67]. In this study, we took advantage of iTat mice, exposed them to cocaine, and determined the changes of the gut microbiota in response to Tat expression and chronic cocaine exposure. Specifically, we harvested large intestines of the mice, extracted the DNA from the tissues, constructed 16S rRNA gene libraries, performed the metagenomic sequencing, and determined the abundance, composition, and diversity of the gut microbiota. Mice of two different ages, 6- and 12 months old, were included in the study. All the data were stratified by genotypes (WT/iTat), treatment (saline/cocaine, SA/CA), ages ($\frac{6}{12}$ months), and sexes (male/female). ## 2. Materials and Methods Experimental design and animals. Wild-type C57BL/6 mice (Jackson Laboratory, Bar Harbor, ME, USA) and Dox-inducible astrocyte-specific HIV-1 Tat transgenic mice (iTat) were derived from our previous study [43,63]. Animals were fed with Dox-containing diet (0.625 g Dox/kg, Envigo, Indianapolis, IN, USA) for 5 or 11 months from day 21 when they were weaned and continued on the same diet throughout the remaining studies. These animals were given cocaine (CA, i.p. 30 mg/kg/day) or the solvent phosphate-buffered saline (SA) for 14 days, kept drug-free for 10 days, assessed for various behaviors for 20 days, and euthanized to harvest large intestinal tissues. There were a total of 16 experimental groups: 2 mouse strains (WT/iTat) × 2 mouse ages ($\frac{6}{12}$ months) × 2 sexes (M/F) × 2 treatments (CA/SA) and a total of 192 mice (16 groups × 12 mice/group). All the animal procedures were approved by the Institutional Animal Care and Use Committee. DNA extraction. Large intestine tissues (near anus) were harvested and used to extract DNA using a DNeasy Blood & Tissue Kit (Qiagen, Germantown, MD, USA) according to the manufacturer’s instructions. Briefly, large intestine tissues (about 15 mg) were cut into small pieces, placed into a 1.5 mL microcentrifuge tube containing 180 µL ATL buffer, and treated with 600 mAU/mL proteinase K at 56 °C for 2 hr. When the tissues were completely lysed, DNA was precipitated with 200 µL buffer AL and 200 µL $100\%$ ethanol, washed twice (buffer AW1 and AW2, once each), eluted from the mini-spin column with 200 µL buffer AE, diluted to 10 ng/µL, and stored at −20 °C for subsequent PCR amplification. All DNA preps had the A260/A280 ratio of higher than 1.80. 16S rRNA gene metagenomic library construction, sequencing, and initial sequence analysis. The purified DNA was used to construct 16S rRNA gene libraries as previously described [68]. Briefly, the DNA was amplified for the V4 variable region of the bacterial 16S rRNA gene using fusion primers with partial Illumina adaptors. The universal bacterial primers used were 515F: 5′-GTG CCA GCM GCC GCG GTA A-3′ and 806R: 5′-GGA CTA CHV GGG TWT CTA AT-3′. The PCR reaction (25 µL) consisted of 10 ng the purified DNA, 1X AccuStart II PCR Supermix containing Taq DNA polymerase (Quantabio, Beverly, MA), 10 µg BSA, and 500 nM each primer, with a program of 1 cycle of 94 °C for 3 min, 30 cycles of 94 °C for 30 s, 50 °C for 30 s, and 72 °C for 1 min, and a final cycle of 72 °C for 10 min. Amplicon DNA were cleaned, indexed, normalized, and pooled using a MiSeq Reagent kit (Illumina, San Diego, CA, USA) and sequenced on the Illumina MiSeq platform (Illumina, San Diego, CA). The raw reads were processed and paired-end reads (forward and reverse reads) were merged and denoised using the DADA2 algorithm (ver. 1.3.3) [69]. The processed reads datasets from 123 samples (6–11 samples/group) were clustered to operational taxonomic units (OTU) using a similarity threshold of $97\%$ or higher (2,974,646 matched reads) and the taxonomy was assigned using the SILVA reference database (ver. 1.3.2) [70]. The sequencing and the initial sequence analysis were performed by the Center of Bioinformatics and Functional Genomics of Miami University, Oxford, OH. Subsequent sequence and statistical analysis. All OTU data were analyzed by an online analysis tool MicrobiomeAnalyst (ver. 1.0) [71]. The relative abundance (%) was calculated at the family level. The Shannon index was calculated to determine the α diversity and was compared using the Kruskal–Wallis test. The PCoA-Bray–Curtis index was calculated to determine the β diversity and was compared using permutational multivariate analysis of variance (PERMANOVA). The univariate analysis was performed using the Kruskal–Wallis test to compare the specific families among four experimental groups (WT/iTat × SA/CA). The software STAMP (ver. 2.1.3) was used to perform post hoc Games–Howell’s test to compare among multiple groups [72]. “*”, “#”, “&”, “ +” and “@” denote $p \leq 0.05.$ The Tax4Fun was used to estimate microbial metabolic functions based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database [71,73], and the functional metabolic pathways were compared using the Kruskal–Wallis test with a post hoc Games–Howell’s test. ## 3. Results We analyzed all the sequence reads and identified the 22 most reliable families of gut microbiota as the core microbiota to determine the abundance, and α diversity using the Shannon index which is a quantitative indicator of the number of different families, and β diversity using the PCoA-Bray–Curtis index which quantifies the variability in community composition among samples in mice of different ages and sexes in response to Tat expression and cocaine exposure. Then, we further compared 12 families which were found to be affected in either group for their abundance in mice of different ages and sexes in response to Tat expression and cocaine exposure. We first determined the effects of Tat and cocaine on the gut microbiota of 6-month-old female mice. The most abundant 22 families identified in the gut microbiota of 6-month-old female mice from the most abundance to the least abundance were Muribaculaceae, Lachnospiraceae, Bacteroidaceae, Ruminococcaceae, Desulfovibrionaceae, Erysipelotrochaceae, Helicobacteraceae, Tannerellaceae, Eggerthellaceae, Rickenellaceae, Prevotellaceae, Family_XIII, Peptococcaceae, Clostridiales_vadinBB60_group, Lactobacillaceae, Cyannobiaceae, Akkermansiacceae, Alteromonadaceae, Deferribacteraceae, Lachnospiraceae_Ambiguous_taxa, uncultured_bacterium, and Staphylococcaceae (Figure 1A). Both α diversity (Figure 1B, $$p \leq 0.515$$) and β diversity (Figure 1C, $$p \leq 0.112$$) did not show any significant changes. Kruskal–Wallis test only showed significant changes on Alteromonadaceae, but not on any other families. Post hoc Games–Howell’s test further showed that Alteromonadaceae was more abundant in iTat-SA mice than WT-SA mice and iTat-CA mice (Figure 2). These results showed that in 6-month-old female mice Tat expression was associated with more Alteromonadaceae in gut, which was reversed by cocaine exposure. Then, we determined the effects of Tat and cocaine on the gut microbiota of 6-month-old male mice. The most abundant 22 families identified in the gut microbiota of 6-month-old male mice were the same as these in 6-month-old female mice, but in a different order from the most abundance to the least abundance: Muribaculaceae, Lachnospiraceae, Ruminococcaceae, Bacteroidaceae, Erysipelotrochaceae, Desulfovibrionaceae, Rickenellaceae, Helicobacteraceae, Eggerthellaceae, Prevotellaceae, Peptococcaceae, Tannerellaceae, Family_XIII, Lactobacillaceae, Clostridiales_vadinBB60_group, Akkermansiacceae, Deferribacteraceae, Lachnospiraceae_Ambiguous_taxa, uncultured_bacterium, Cyannobiaceae, Alteromonadaceae, and Staphylococcaceae (Figure 3A). α diversity had no significant differences (Figure 3B, $$p \leq 0.276$$), while β diversity showed significant differences (Figure 3C, $$p \leq 0.032$$). Kruskal–Wallis test showed significant changes on Alteromonadaceae, Helicobacteraceae and Tannerellaceae. Post hoc Games–Howell’s test showed that Alteromonadaceae was more abundant in iTat-CA mice than iTat-SA, WT-CA, and WT-SA mice although Helicobacteraceae was less abundant in iTat-CA and iTat-SA mice than WT-SA mice (Figure 4). In addition, Post hoc Games–Howell’s test also showed that Tannerellaceae was more abundant in iTat-CA, iTat-SA, and WT-CA mice than WT-SA mice. These results showed that in 6-month male mice Tat expression alone, or cocaine exposure alone did not alter the abundance of Alteromonadaceae, but simultaneous Tat expression and cocaine exposure led to significant increases of the abundance of Alteromonadaceae. These results also showed that Tat expression alone significantly decreased abundance of Helicobacteraceae, and that Tat expression alone or cocaine alone had more abundant Tannerellaceae but simultaneous Tat expression and cocaine exposure significantly increased abundance of Tannerellaceae. We next determined the effects of Tat and cocaine on the gut microbiota of 12-month-old female mice. The most abundant 22 families identified in the gut microbiota of 12-month-old female mice remained the same, but in a different order from the most abundance to the least abundance: Muribaculaceae, Lachnospiraceae, Bacteroidaceae, Ruminococcaceae, Helicobacteraceae, Rickenellaceae, Prevotellaceae, Erysipelotrichaceae, Desulfovibrionaceae, Tannerellaceae, Peptococcaceae, Eggerthellaceae, Family_XIII, Clostridiales_vadinBB60_group, Akkermansiacceae, Staphylococcaceae, Lachnospiraceae_Ambiguous_taxa, Cyanobiaceae, Lactobacillaceae, Alteromonadaceae, uncultured_bacterium, and Deferribacteraceae (Figure 5A). Both α diversity (Figure 5B, $$p \leq 0.032$$) and β diversity (Figure 5C, $$p \leq 0.001$$) showed significant changes. Kruskal–Wallis test showed significant changes on Alteromonadaceae, Bacteroidaceae, Clostridiales_vadinBB60_group, Cyanobiaceae, Desulfovibrionaceae, Erysipelotrichaceae, Helicobacteraceae, Lachnospiraceae, Muribaculaceae, Ruminococcaceae, and Staphylococcaceae. Post hoc Games–Howell’s test showed that Alteromonadaceae was more abundant in iTat-CA and iTat-SA mice than WT-SA mice, that Bacteroidaceae was more abundant in iTat-CA, iTat-SA, and WT-CA mice than WT-SA mice, that Clostridiales_vadinBB60_group was less abundant in iTat-CA and WT-CA than WT-SA mice, that Cyanobiaceae was more abundant in iTat-CA and iTat-SA mice than WT-SA mice, that Desulfovibrionaceae was less abundant in iTat-CA, iTat-SA, and WT-CA mice than WT-SA mice, that Erysipelotrichaceae was more abundant in iTat-CA and iTat-SA mice than WT-SA mice, that Helicobacteraceae was less abundant in iTat-CA and iTat-SA mice than WT-SA mice, that Lachnospiraceae was less abundant in iTat-CA and iTat-SA mice than WT-SA mice, that Muribaculaceae was more abundant in iTat-CA, iTat-SA, and WT-CA mice than WT-SA mice, that Ruminococcaceae was less abundant in iTat-CA, iTat-SA, and WT-CA mice than WT-SA mice, and that Staphylococcaceae was less abundant in iTat-CA mice than WT-CA mice (Figure 6). These results showed that in 12-month-old female mice Tat expression increased the abundance of Alteromonadaceae, Bacteroidaceae, Cyanobiaceae, Erysipelotrichaceae, and Muribaculaceae and decreased the abundance of Desulfovibrionaceae, Helicobacteraceae, Lachnospiraceae, and Ruminococcaceae. These results showed that cocaine exposure alone increased the abundance of both Bacteroidaceae and Muribaculaceae and decreased the abundance of Clostridiales_vadinBB60_group, Desulfovibrionaceae’s and Ruminococcaceae. We next determined the effects of Tat and cocaine on the gut microbiota of 12-month-old male mice. The most abundant 22 families identified in the gut microbiota of 12-month-old male mice remained the same, but in a different order from the most abundance to the least abundance: Muribaculaceae, Lachnospiraceae, Ruminococcaceae, Bacteroidaceae, Erysipelotrochaceae, Desulfovibrionaceae, Helicobacteraceae, Rickenellaceae, Tannerellaceae, Prevotellaceae, Eggerthellaceae, Peptococcaceae, Family_XIII, Clostridiales_vadinBB60_group, Akkermansiacceae, Lactobacillaceae, Staphylococcaceae, Cyannobiaceae, Lachnospiraceae_Ambiguous_taxa, Alteromonadaceae, Deferribacteraceae, and uncultured_bacterium (Figure 7A). Both α diversity (Figure 7B, $$p \leq 0.379$$) and β diversity (Figure 7C, $$p \leq 0.231$$) showed no significant changes. Kruskal–Wallis test showed no significant differences in all 12 abundant families (Figure 8). These results showed that Tat expression alone, cocaine exposure alone, or simultaneous Tat expression and cocaine exposure led to no significant changes of the gut microbiota in 12-month-old male mice. Lastly, we analyzed all the sequence reads using the Tax4Fun to estimate the changes of microbial metabolic functions in gut for all the 16 experimental groups. In 12-month-old female mice, there was lower energy metabolism in iTat-SA mice than WT-SA mice, higher lipid metabolism in iTat-CA, iTat-SA, and WT-CA mice than WT-SA mice, higher metabolism of other amino acids in iTat-CA and iTat-SA mice than WT-SA mice, and higher nucleotide metabolism in WT-SA mice than iTat-CA and iTat-SA mice (Figure 9). The results showed that Tat expression alone decreased the energy metabolism and nucleotide metabolism, and increased the lipid metabolism and metabolism of other amino acids. In addition, cocaine exposure also increased the lipid metabolism. ## 4. Discussion Our recent study shows that HIV Tat and cocaine interactively alter genome-wide DNA methylation and gene expression and cause neuropathological and neurocognitive impairments [63]. As an extension, we continued to characterize effects of Tat expression and cocaine exposure on the abundance, composition, and diversity of the gut microbiota from these same groups of animals in the current study. To ensure the comparability, WT mice were fed with the same Dox-containing diet as iTat mice throughout the studies. Cocaine exposure alone decreased Clostridiales_vadinBB60_group, Desulfovibrionaceae and Ruminococcaceae in the gut of 12-month-old female mice. However, Tat expression alone increased Alteromonadaceae in 6-month-old female mice and Alteromonadaceae, Bacteroidaceae, Cyanobiaceae, Erysipelotrichaceae, and Muribaculaceae in 12-month-old female mice, but decreased Desulfovibrionaceae, Helicobacteraceae, Lachnospiraceae, and Ruminococcaceae in 12-month-old female mice. These results indicate that Tat expression causes more severe dysbiosis than cocaine exposure. In contrast, cocaine exposure is associated with more diverse bacterial communities at different taxonomy levels [74,75,76]. This apparent discrepancy may be due to several factors including different sources of samples, sequencing reads processing, and use of Dox to induce Tat expression in our study. Our further analysis showed that simultaneous Tat expression and cocaine exposure increased Alteromonadaceae and Tannerellaceae in 6-month-old male mice and Bacteroidaceae in 12-month-old female mice, while Tat expression alone or cocaine exposure alone only had slight increases these families. These results suggest that Tat expression and cocaine exposure have synergistic effects in increasing this family, which is consistent with their synergistic effects on neurobehaviors and neuropathologies [63]. Interestingly, cocaine exposure appeared to attenuate Alteromonadaceae increased by Tat expression in 6-month-old female mice. Furthermore, only Tat expression but not cocaine exposure changed Alteromonadaceae, Cyanobiaceae, Erysipelotrichaceae, Helicobacteraceae, and Lachnospiraceae in 12-month female mice. Taken together, these results indicate that Tat expression and cocaine exposure exhibit different effects on different families of gut microbiota. Aging is known to be associated with changes of the gut microbiota [77,78]. Thus, we determined the changes of bacterial communities in both 6-month-old and 12-month-old mice. Our results showed that only 1~3 families were affected by Tat expression or cocaine exposure in 6-month-old mice while 11 families were changed in 12-month-old female mice, supporting the notion that aging plays an important role in gut microbiota symbiosis. Lifestyle-induced changes of hormone or immune function may also contribute to alterations in gut microbiota, the underlying mechanism of microbiota alterations with aging is not completely clear. Our results, together with other studies, suggest that the changes of hormone or immune function induced by aging itself may play more important role in these changes [77]. At the same time, we also determined the effects of sex on gut microbiota. In 6-month-old mice, only Alteromonadaceae was affected in both female and male mice, and Helicobacteraceae and Tannerellaceae were also changed in male mice. Interestingly, completely different from 6-month-old mice, six families were altered in 12-month-old female mice, but no changes were found in 12-month-old male animals. These results indicate that sex plays an important role in gut microbiota dysbiosis. Consistent with our findings is another study in which gut microbiota shows significant differences between female and male [79]. Although male hormone can also change gut microbiota composition, most of studies focus on female hormone and the estrogen–gut microbiome axis; the concept was proposed that crosstalk exists between gut microbiota and estrogen and, in other words, gut microbiota also influence estrogen level [80]. Female is found to be more sensitive to addictive substance, including cocaine, and alterations of host microbiota affect cocaine-induced behavioral activities [81]. Therefore, the changes in gut microbiota between female and male may eventually contribute to the differences of behavioral activities between female and male through the gut–brain axis. Taken together, both age and sex are important factors in determining the gut microbiota composition. The normal gut microbiota primarily consists of four phyla Bacillota (also known as Firmicutes), Bacteroidota, Actinomycetota, and Verrucomicrobiota and mainly functions to provide nutrients, protection against pathogens, and immune response [82,83,84]. The families that were altered by Tat expression, cocaine exposure, or simultaneous Tat expression and cocaine exposure from the current study were Alteromonadaceae in 6-month-old female/male mice and Bacteroidaceae, Desulfovibrionaceae, Erysipelotrichaceae, Lachnospiraceae, Muribaculaceae, and Ruminococcaceae in 12-month-old female mice. These families belong to the phyla Bacillota (Ruminococcaceae, Lachnospiraceae, and Erysipelotrichaceae), Bacteroidota (Muribaculaceae and Bacteroidaceae), and Thermodesulfobacteriota (Desulfovibrionaceae), and Pseudomonadota (Alteromonadaceae). Lack of the phyla Actinomycetota, and Verrucomicrobiota in the gut microbiota from this study is likely due to use of doxycycline in all the mice [82]. In this study, we also found Tat expression or cocaine exposure resulted in metabolic abnormalities which are common in HIV-infected patients. Consistent with our findings, Tat expression results in a decrease in cellular energy metabolism by deregulating intracellular calcium homeostasis and disrupting mitochondrial function [85], and cocaine exposure increases lipid metabolism [86]. However, the relationship between changes of these families and changes of metabolic pathways in the gut of 12-month-old female mice remains to be determined. An increasing number of recent studies support the bidirectional gut–brain axis hypothesis that the brain can alter microbial composition in gut by autonomic nervous system, and that gut microbiota, in turn, can regulate the brain function by endocrine and neurocrine pathways [87]. In this study, we chose iTat mice as a surrogate HAND model to explore possible bidirectional interactions between HAND and gut microbiota. Tat protein is expressed in astrocytes, secreted from these cells, and taken up by other cells such as neurons [88,89,90,91,92,93]. Tat may be transported from the brain to the peripheral tissues/organs such as gut and lead to change of the gut microbiota, which in turn contributes to HAND. There is another possibility that *Tat is* induced in the glial fibrillary acid protein-positive glial cells, which directly regulate proinflammatory response, microbiota composition, and epithelial barrier integrity in gut and then contribute to neuroinflammation and changes of neurobehaviors [94,95]. On the other hand, cocaine was given to mice through the i.p. route in this study. Thus, cocaine’s effects on the gut microbiota could be direct or indirect. Nevertheless, further studies are needed to understand the underlying mechanisms of how Tat and cocaine affect the gut microbiota and whether these mechanisms can be explored for development of HAND therapeutics. 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--- title: Lacticaseibacillus rhamnosus ATCC 53103 and Limosilactobacillus reuteri ATCC 53608 Synergistically Boost Butyrate Levels upon Tributyrin Administration Ex Vivo authors: - Pieter Van den Abbeele - Mallory Goggans - Stef Deyaert - Aurélien Baudot - Michiel Van de Vliet - Marta Calatayud Arroyo - Michael Lelah journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054277 doi: 10.3390/ijms24065859 license: CC BY 4.0 --- # Lacticaseibacillus rhamnosus ATCC 53103 and Limosilactobacillus reuteri ATCC 53608 Synergistically Boost Butyrate Levels upon Tributyrin Administration Ex Vivo ## Abstract Modulation of the gut microbiota is a trending strategy to improve health. While butyrate has been identified as a key health-related microbial metabolite, managing its supply to the host remains challenging. Therefore, this study investigated the potential to manage butyrate supply via tributyrin oil supplementation (TB; glycerol with three butyrate molecules) using the ex vivo SIFR® (Systemic Intestinal Fermentation Research) technology, a highly reproducible, in vivo predictive gut model that accurately preserves in vivo-derived microbiota and enables addressing interpersonal differences. Dosing 1 g TB/L significantly increased butyrate with 4.1 (±0.3) mM, corresponding with 83 ± $6\%$ of the theoretical butyrate content of TB. Interestingly, co-administration of Limosilactobacillus reuteri ATCC 53608 (REU) and *Lacticaseibacillus rhamnosus* ATCC 53103 (LGG) markedly enhanced butyrate to levels that exceeded the theoretical butyrate content of TB (138 ± $11\%$ for REU; 126 ± $8\%$ for LGG). Both TB + REU and TB + LGG stimulated Coprococcus catus, a lactate-utilizing, butyrate-producing species. The stimulation of C. catus with TB + REU was remarkably consistent across the six human adults tested. It is hypothesized that LGG and REU ferment the glycerol backbone of TB to produce lactate, a precursor of butyrate. TB + REU also significantly stimulated the butyrate-producing Eubacterium rectale and *Gemmiger formicilis* and promoted microbial diversity. The more potent effects of REU could be due to its ability to convert glycerol to reuterin, an antimicrobial compound. Overall, both the direct butyrate release from TB and the additional butyrate production via REU/LGG-mediated cross-feeding were highly consistent. This contrasts with the large interpersonal differences in butyrate production that are often observed upon prebiotic treatment. Combining TB with LGG and especially REU is thus a promising strategy to consistently supply butyrate to the host, potentially resulting in more predictable health benefits. ## 1. Introduction The human colon is colonized by trillions of microorganisms that strongly influence health. Alterations of the gut microbiota have been associated with disease conditions such as metabolic and immune disorders, liver dysfunctions, inflammatory bowel disease, colorectal cancer, cardiovascular conditions, and central nervous system disorders [1,2,3,4,5,6]. A key role of the gut microbiota is to ferment indigestible glycans, which results in the production of short-chain fatty acids (SCFA), among other metabolites. SCFAs have cornerstone functions in maintaining gut homeostasis but also affect extra-intestinal systems [7,8,9,10]. Butyrate is of special relevance to health as it exerts multiple functions such as acting as a histone deacetylase (HDAC) inhibitor or signaling through G protein-coupled receptors (GPCRs) [11]. Butyrate signaling involves the control over central pathways regulating gut homeostasis, including the inhibition of NF-κB activation or IFN-γ signaling, the upregulation of PPARγ, and control over cell proliferation, differentiation, and apoptosis [12]. Butyrate is also the main energy source for colonocytes and promotes barrier integrity by modulating tight junctions and mucus production [11,13,14,15,16,17]. In addition, butyrate metabolism by the epithelium consumes local oxygen and stabilizes the hypoxia-inducible factor (HIF), a transcription factor influencing barrier protection and immune response [18]. Increasing butyrate levels is thus a promising strategy to maintain metabolic homeostasis, intestinal barrier integrity, and balanced immune responses. A first strategy to increase butyrate supply to the host could consider the administration of butyrate-producing bacteria. Key butyrate-producing species of the human gut belong to the Lachnospiraceae and Ruminococcaceae families and produce butyrate via butyrate kinase (e.g., *Coprococcus eutactus* and Subdoligranulum variabile) or butyryl CoA:acetate CoA transferase (e.g., Eubacterium rectale, Anaerobutyricum hallii, Coprococcus catus, and Faecalibacterium prausnitzii) [19], with specific species being able to convert acetate and lactate to butyrate in a process called cross-feeding [20]. The species capable of producing butyrate are thus very different from the traditional probiotics that are often lactic acid bacteria belonging to the Lactobacillaceae and Bifidobacteriaceae families. Some butyrate-producing species have been described to comply with probiotic criteria [21,22], but the commercialization of novel strict anaerobic microorganisms is a complex and expensive task, due to both regulatory and practical constraints (e.g., production, storage, and in vivo delivery of viable amounts). A second strategy to increase butyrate supply therefore considers increasing fiber intake. Fibers can increase butyrate production by stimulating specific butyrate producers in situ. However, a substantial interindividual variability in butyrate production upon fiber intake has been observed [23], resulting in unpredictable outcomes of interventions. Finally, while oral butyrate supplementation has been shown to improve clinical symptoms of inflammatory bowel disease, insulin sensitivity, diabetic inflammation, and an intestinal barrier, administering butyrate can be challenging for several reasons, including short metabolic half-life, toxicity, and patient intolerance [24]. Overall, while the health benefits of butyrate are generally acknowledged, its supply to the host remains difficult to manage in vivo. Preclinical studies have the potential to complement clinical studies as they allow for reducing the impact of confounding factors affecting the gut microbiota, including diet, environment, or host genetics. Further, they allow insights to be obtained on the production of metabolites such as SCFA that are rapidly absorbed in vivo. There is however increasing awareness of a so-called ‘Valley of Death’ between preclinical and clinical research [25]. A major challenge in preclinical gut microbiome research is the drastic compositional alteration of in vivo-derived microbiota, used to inoculate preclinical models, to form in vitro-adapted microbiota. This in vitro bias is highly pronounced for short-term models where fast-growing, aerotolerant taxa represent >$50\%$ of the communities within 24 h [26,27,28,29]. Similarly, the current generation of long-term gut models impose very defined nutritional and environmental conditions, thus enriching taxa that thrive under these specific conditions [30,31], within three days after inoculation [32]. A second drawback of many models is the low throughput, often resulting in less robust study designs, lacking parallel controls and/or replicates. It is, however, of key importance to include biological replicates to acknowledge that interpersonal differences are the main driver of differences in the human microbiota, largely exceeding differences between lumen/mucus or differences along colonic regions [33]. The relevance of interpersonal differences also follows from the observation that they impact the outcome of interventions [34]. This study investigated whether glyceryl tributyrate (tributyrin; TB) could enhance butyrate levels in an ex vivo simulated colonic environment when dosed as such and in combination with Limosilactobacillus reuteri ATCC 53608 (REU) or *Lacticaseibacillus rhamnosus* ATCC 53103 (LGG). TB is a triglyceride, i.e., a glycerol esterified with butyrate at the 1, 2, and 3 positions [24]. The rationale for combining TB with REU/LGG is that the REU/LGG could ferment glycerol derived from the hydrolysis of TB (to one glycerol and three butyrate molecules) and in doing so produce lactic acid, a precursor of butyrate production, thus providing a dual mode of action to boost butyrate levels. Further, both strains are of particular interest, as on the one hand, LGG is the most documented probiotic strain [35], while REU has been demonstrated to convert glycerol to reuterin, an antimicrobial compound [36], thus providing an additional unique mechanism for microbiota modulation upon tributyrin (and thus also glycerol) intake. The research question was addressed using the ex vivo SIFR® (Systemic Intestinal Fermentation Research) technology [37]. The SIFR® technology is a highly reproducible gut model that accurately preserves in vivo-derived microbiota throughout the entire duration of the experiment. Most importantly, using three structurally different carbohydrates, it was demonstrated that findings within 24–48 h in the SIFR® technology (down to species level) are predictive for findings of clinical studies where such carbohydrates are repeatedly administered over 2–6 weeks. Owing to its high throughput, the SIFR® technology also enables addressing interpersonal differences. In the current study, samples from six human adults were included to evaluate the consistency of ex vivo treatment effects of TB, REU, LGG and combinations thereof. In the current study TB, REU, and LGG were thus incubated ex vivo as described below and not administered directly to the human volunteers. ## 2.1. Microbiota of Study Subjects Covered Interpersonal Differences in Gut Microbiota Composition A PCA at the family level of the fecal microbiota of the six human adults used during the current study demonstrated that there were marked interpersonal differences in microbiota composition at baseline, mainly driven by different levels of Prevotellaceae, Ruminococcaceae, and Bacteroidaceae (Figure 1), which have previously been identified as key families to stratify the human gut microbiota according to the concept of enterotypes [38]. Samples of donors 1, 2, and 3 were positioned to the left side of the PCA due to high Prevotellaceae levels (7.2–$11.9\%$) (Figure S1). Further, the microbiota of donors 2 and 3 had high Ruminococcaceae levels (21.1–$22.4\%$), while high Bacteroidales_u_f levels ($16.5\%$) were noted for donor 1. Samples of donors 4, 5, and 6 were positioned to the right side of the PCA, due to remarkably high Bacteroidaceae levels for donor 4 ($19.6\%$), high Bifidobacteriaceae levels for donor 5 ($11.5\%$), and Rikenellaceae levels of around $10\%$ for donors 4 and 6. ## 2.2. REU and LGG Remained Viable throughout the Entire Duration of the 48 h Ex Vivo Experiment Upon inoculation, selective enumeration of the Lactobacillaceae species at 0 h showed that REU and LGG were, respectively, inoculated at 4.1 ± 0.5 × 107 CFU/mL and 8.7 ± 1.5 × 107 CFU/mL. After 48 h of incubation, LGG and REU were exclusively detected in reactors where they were inoculated, both by culture-independent (shallow shotgun sequencing; Figure 2A,B) and by culture-dependent techniques (LAMVAB agar; Figure 2B,D). This confirms the selectivity of both detection methods and suggests that LGG and REU were not present in the fecal samples of the tested donors prior to inoculation. Interestingly, viable levels of LGG and REU (CFU/mL) were similar or even slightly increased at 48 h compared to 0 h (on average +$5\%$ for LGG and +$43\%$ for REU), thus demonstrating that the SIFR® technology provided optimal conditions for LGG and REU to remain viable over the entire duration of the 48 h incubation. As a remark, LGG and REU levels were not impacted by the presence of TB. ## 2.3. TB Increased Butyrate Levels, Which Were Further Enhanced upon Probiotic Co-Administration A PCA based on fundamental fermentation parameters (pH, gas production, SCFA, bCFA) (Figure 3A) provided comprehensive insight into overall treatment effects as the first two components explained $92.4\%$ of the variation of the dataset. There was a marked differential clustering of 0 h and 48 h samples, reflecting the strong production of acetate, propionate, butyrate, bCFA, and gasses between 0 and 48 h. The expansion of a complex gut microbiota over the duration of the experiment is a core aspect of the ex vivo SIFR® technology [37]. At 48 h, there was a marked differential positioning of TB-treated samples compared to the NSC, upwards along PC2. Butyrate levels were primarily responsible for this TB-mediated effect as it significantly increased from, on average, 2.8 mM in the NSC up to 6.9 mM (TB) (Figure 3B). As the theoretical butyrate content of 1 g/L TB is 4.96 mM, a recovery of, on average, $83\%$ was obtained upon TB treatment (Figure 3C). Remarkably, while the Lactobacillaceae species as such did not impact butyrate levels (except for a minor increase with LGG), butyrate increased up to 9.6 mM (TB + REU) and 9.0 mM (TB + LGG) for the combinations of TB with the Lactobacillaceae species. Butyrate recoveries largely exceeded $100\%$ of the butyrate content in TB and reached values as high as $138\%$ and $126\%$ for TB + REU and TB + LGG, respectively, suggesting that glycerol fermentation could have contributed to a further butyrate increase. As the theoretical glycerol content of 1 g TB is 1.65 mmol glycerol, assuming a 1:1 glycerol to lactate/pyruvate conversion and 4:3 lactate to butyrate conversion [20], this would yield 1.24 mmol of butyrate or thus increase butyrate levels up to $125\%$ of the theoretical butyrate content of TB. While observed butyrate levels are in this range for TB + LGG ($126\%$), butyrate levels even increased further for TB + REU ($138\%$), suggesting a remarkable synergistic effect of TB and REU on butyrate. Interestingly, the synergistic effects of combinations of TB with REU/LGG were highly consistent across the six human adults tested. Finally, acetate, propionate, valerate, and bCFA levels were not affected or only mildly affected by the different treatments (Figure S2). ## 2.4. The Combination of TB with REU Increased Microbial Diversity First, both diversity indices suggested a similar or even higher diversity for NSC incubations at 48 h as compared to the original inocula (INO), confirming that the ex vivo SIFR® technology allows for the growth of a broad range of in vivo-derived gut microbes (Figure 4). This was further substantiated by the sustained similarity between the microbiota of the inoculum and the NSC at 48 h (Figure S3). Further, none of the treatments significantly affected estimated species richness, as measured by the Chao 1 diversity index, except for a tendency to higher richness for TB + REU (pnon-adjusted = 0.20) (Figure 4A). In contrast, microbial diversity in terms of both species’ richness and evenness (reciprocal Simpson diversity index) was strongly affected in specific conditions (Figure 4B). LGG treatment lowered species evenness, reflecting the presence of high LGG levels. In contrast, REU as such maintained species evenness, while TB + REU even significantly increased microbial diversity in terms of species evenness. ## 2.5. The Combination of TB with LGG and Especially REU Increased the Abundance of Specific Butyrate-Producing Species TB as such already impacted microbial composition, as TB significantly decreased Proteobacteria levels and significantly increased the *Firmicutes phylum* (Figures S3 and S4). Further, TB also tended to increase Actinobacteria due to a tendency towards higher *Bifidobacterium adolescentis* levels (Figure 5). Additionally, supplementation of LGG and REU as such already impacted microbial composition. At the phylum level, LGG and REU significantly increased Firmicutes levels (Figures S3 and S4), which was, in part, due to marked increases in Limosilactobacillus reuteri (NSC: <limit of detection (LOD), REU: 3.9 ± $0.3\%$) and *Lacticaseibacillus rhamnosus* (NSC: <LOD, REU: 16.6 ± $2.3\%$), respectively (Figure 5). Further, in contrast to REU, LGG also significantly boosted Coprococcus catus, a lactate-consuming, butyrate-producing species, while decreasing the abundances of a series of species belonging to the Actinobacteria, Bacteroidetes, Firmicutes, and *Proteobacteria phyla* (Figure 5). It should be noted that the current analysis was based on relative abundances and not absolute levels. Lower relative abundances of several taxa (e.g., B. adolescentis) upon REU/LGG addition do not necessarily indicate a decreased absolute level of these taxa but could rather reflect the higher total number of bacteria upon REU/LGG addition. This makes the increase in relative abundances of C. catus even more striking. Interestingly, combinations of TB with REU/LGG significantly increased Firmicutes at the expense of Bacteroidetes, not only compared to the NSC and TB but also compared to REU/LGG alone (Figures S3 and S4), suggesting that LGG and REU specifically alters microbial composition in the presence of TB. At the species level, TB + REU significantly stimulated butyrate-producing species belonging to both the Lachnospiraceae (*Coprococcus catus* and Eubacterium rectale) and Ruminococcaceae (Gemmiger formicilis) families (Figure 5 and Figure 6D–F). This demonstrates the potential of TB + REU to shift microbial composition towards butyrate-producing species. A key contribution of *Coprococcus catus* to butyrate production upon TB + REU treatment was suggested by its correlation with butyrate levels (Figure 6B). Similarly to LGG alone, its combination with TB increased *Coprococcus catus* levels (Figure 5). This increase was, however, not significant given the larger interpersonal variation of this treatment effect (e.g., no increase for donor 5, in contrast to marked increases for donors $\frac{1}{2}$) (Figure 6E). In samples containing LGG, butyrate levels were positively correlated with Coprococcus catus, Eubacterium rectale, and *Gemmiger formicilis* (Figure 6C). ## 3. Discussion This study evaluated the potential to manage butyrate supply to the host via tributyrin oil (TB), whether or not co-supplemented with a Lactobacillaceae species (REU or LGG). The research question was addressed using the ex vivo SIFR® technology, a recently developed gut model that, within 24–48 h, provides insights into gut microbiota modulation that are predictive for observations of repeated-intake clinical studies (down to species level resolution) [37]. In line with the aforementioned study, a high technical reproducibility, marked metabolite production, high microbial diversity, and, most importantly, sustained similarity between the original donor microbiota and untreated SIFR® reactors at 48 h was observed during the current study. Such sustained similarity is fundamentally different from consistent biases observed for the current generation of in vitro gut models [26,27,28,29,30,31,32] and is the basis of classifying the application of SIFR® technology as an ex vivo study, which is a study that uses an artificial environment outside the human body with minimum alteration of natural conditions. Further, owing to its high throughput, the SIFR® technology enabled the inclusion of multiple test subjects in the study design. Interestingly, the differences in microbiota composition among the six human adults were mainly driven by different levels of Prevotellaceae, Ruminococcaceae, and Bacteroidaceae, families that have previously been identified as key taxa to stratify the human adult gut microbiota according to the concept of enterotypes [38]. This suggests that the six human adults covered a spectrum of microbial composition that can occur in vivo. Despite this heterogeneity at baseline, LGG and REU remained viable upon administration to the microbiota of each human adult and even slightly increased in abundance towards the end of the incubation. Interestingly, remarkably consistent treatment effects on butyrate were noted for TB and its combinations with REU and LGG. First, when administered as such, TB consistently increased butyrate levels with 83 ± $6\%$ of the theoretical butyrate content of TB, suggesting an efficient hydrolysis of TB to glycerol and butyrate. Further, dosing 1 g TB/L already mildly shaped microbial composition based on tendencies towards higher *Bifidobacterium adolescentis* levels and significantly decreased Proteobacteria levels. While the translation of the data can be questioned given the very different host physiologies, these results are in line with studies where common and grass carp were supplemented with TB [39,40]. Proteobacteria are gut commensals usually present in low numbers, whereas, under specific triggers, they can increase in number and become colitogenic microbes causing inflammatory responses [41,42]. Therefore, a reduction in Proteobacteria members could be an additional mechanism to generate health benefits upon TB administration beyond the highly consistent increase in butyrate levels across donors due to the direct release of butyrate from TB. Co-administration of REU and LGG consistently increased butyrate levels up to 138 ± $11\%$ and 126 ± $8\%$ of the theoretical butyrate content of TB. The high consistency of this additional butyrate increase upon co-supplementation of REU/LGG is even more remarkable as REU/LGG are not able to produce butyrate themselves but require specific microbes from the indigenous microbiota to produce butyrate. Given the aforementioned heterogeneity of microbiota composition between human adults and the diversity of butyrate producers in the gut [43], the specific increase in C. catus by TB + LGG and particularly TB + REU suggests a strong complementarity between REU/LGG and C. catus in the presence of TB. While *Coprococcus catus* can convert lactate to propionate via the acrylate pathway [44], C. catus also has the enzymatic machinery to produce butyrate via the butyryl-CoA:acetate CoA-transferase route [19]. C. catus could thus thrive on lactate that can indeed be produced by LGG/REU from glycerol [45]. Nevertheless, other lactate-utilizing, butyrate-producing species such as *Anaerobutyricum hallii* were also consistently detected in the microbiota of each of the six donors at baseline levels (0.8 ± $0.1\%$) that even exceeded those of C. catus (0.4 ± $0.2\%$). While A. hallii strongly increased and correlated with butyrate production upon inulin and 2′FL treatment in previous SIFR® studies [37], A. hallii was unaffected by TB + REU/LGG treatment in the current study, further highlighting the remarkable complementarity between C. catus and REU/LGG in the presence of TB. As a potential explanation, Sheridan et al. [ 2022] recently demonstrated that glucose partially repressed lactate utilization (lct) cluster expression in A. soehngenii (another lactate-consuming, butyrate-producing species), while such repression was not observed for C. catus [46]. It will be interesting to unravel the underlying mechanisms that could render C. catus more competitive compared to other lactate-utilizing butyrate producers in the presence of TB and REU/LGG. In contrast to TB + LGG, the combination of TB with REU also significantly stimulated the butyrate-producing species Eubacterium rectale and *Gemmiger formicilis* while significantly increasing microbial diversity. A high microbial diversity is generally considered to contribute to ecosystem resilience after disturbance to the microbiome, and it has been reported to be generally higher in healthy compared to compromised subjects [47,48]. A unique effect of REU could potentially follow from its capability to convert glycerol not only to lactate but also to intermediate metabolites such as 1,3-propanediol (1,3-PDO) and 3-hydroxypropionate (3-HPA) [49,50,51,52]. 3-HPA, also known as reuterin, is a potent antimicrobial compound with inhibitory effects against multiple microorganisms, including Escherichia, Salmonella, Shigella, Proteus, Pseudomonas, Clostridium, and Staphylococcus, and to a lesser extent lactic acid bacteria [53]. Reuterin inhibits bacterial growth by affecting thiol groups and inducing oxidative stress [54]. The production of reuterin by REU could further regulate microbial composition by limiting the growth of reuterin-sensitive species, thus freeing ecological niches for other potentially butyrate-producing gut microbes, which could explain the more pronounced effect of TB + REU on butyrate and microbial diversity compared to TB + LGG. While the present study demonstrated an interesting strategy to supply butyrate to the host via a combined direct (via hydrolysis of TB) and indirect (via cross-feeding on glycerol) butyrate stimulation, the next critical step is to demonstrate that these mechanisms can be translated to an in vivo setting. For this purpose, combined delivery of TB and viable cells of LGG/REU in a GIT region where the Lactobacillaceae species can be metabolically active is compulsory. While the proximal colon could be targeted, the distal small intestine could be a more appropriate landing platform for this synbiotic concept given the lower density of the indigenous microbiota in this region [55], thus allowing REU/LGG to preferentially ferment glycerol and prepare for cross-feeding interactions with butyrate producers. Another important aspect to obtain health benefits is to optimize the test dose. As 1 g TB oil resulted in the direct release of around 4 mmol butyrate and an additional production of 2–3 mmol in the presence of LGG-REU, a total amount of around 6–7 mmol could be delivered from 1 g TB oil. To put these values in perspective, daily total SCFA production can be considered: assuming a daily intake of 20 g fiber/day in a healthy human adult, total daily SCFA production is in the range of 200 mmol/day [56]. If butyrate represents $20\%$ of total SCFA levels, 40 mmol butyrate would be produced per day due to fiber intake. This would suggest that consumption of 1 g TB per day could increase butyrate supply to healthy human adults with $10\%$ (TB alone) or even $15\%$ upon co-supplementation with LGG/REU. Considering that the fiber intake is reported to be well below 20 g/d in most countries [57,58], TB or symbiotic combinations are promising strategies to increase health-promoting butyrate in the human gut. There is, however, growing awareness that SCFA production upon fiber intake is prone to marked interpersonal differences. Further, when considering individuals with low fiber intake or subjects with a microbiota depleted in butyrate producers [59,60,61,62,63], daily butyrate production could be much lower than 40 mmol/day, in which case 6–7 mmol butyrate could represent a significantly larger fraction of the basal daily butyrate production. While a key advantage of the SIFR® technology is the absence of a host component, enabling unique insights into metabolite production and microbial composition that are hard to obtain in vivo, a related drawback is that findings of such ex vivo studies should be regarded as complementary to in vivo studies, rather than as a potential replacement of clinical studies. Despite the high predictivity of the SIFR® technology for clinical findings [37], clinical studies are required to demonstrate potential health benefits for the host upon TB and LGG/REU co-supplementation. In conclusion, both the direct butyrate stimulation (via hydrolysis of TB) and additional indirect butyrate increase (via REU/LGG-mediated cross-feeding on glycerol) were remarkably consistent across the six human adults tested ex vivo. Especially the latter was remarkable, as it involved the contribution of a specific species of the indigenous human gut microbiota, i.e., Coprococcus catus. This high consistency contrasts with the large interpersonal differences in butyrate production that are often observed upon prebiotic treatment. Combining TB with LGG and especially REU is thus a promising strategy to consistently supply butyrate to the host, potentially resulting in more predictable health benefits. While the study focused on potential health benefits due to butyrate supply, probiotic administration as such could also contribute to additional health benefits [35]. ## 4.1. Test Products: TB, LGG, and REU Tributyrin (TB) oil (≥$95\%$ purity) was obtained from NutriScience Innovations (Milford, United States of America) and tested at 1000 mg/L. Lacticaseibacillus rhamnosus GG ATCC 53103 (LGG) and Limosilactobacillus reuteri ATCC 53608 (REU) were obtained from the Belgian Coordinated Collections of Microorganisms-Laboratory for Microbiology Ghent (BCCM-LMG, Ghent, Belgium). LGG and REU were grown under anaerobic conditions for 24 h at 37 °C. A first subculture was pre-pared on a selective solid growth medium (LAMVAB agar [64]). Subsequently, cells derived from a single colony were grown in MRS broth under anaerobic conditions for 24 h at 37 °C, after which the strain was stored at −80 °C in MRS, with $20\%$ (vol/vol) of glycerol as a cryoprotectant. Prior to its use, the cryopreserved strain was inoculated in MRS broth and grown under anaerobic conditions for 24 h at 37 °C. Bacterial cells were centrifuged during 5′ at 3000× g and resuspended in anaerobic PBS prior to inoculation in the SIFR® reactors at a final density of around 5 × 107 CFU/mL. ## 4.2. SIFR® Technology The SIFR® technology was recently validated and enables the study of the human gut microbiota in a highly biorelevant manner for multiple test conditions (both treatments and test subjects) [37]. Briefly, individual bioreactors were processed in parallel in a bioreactor management device (Cryptobiotix, Ghent, Belgium). Each bioreactor contained 5 mL of nutritional medium-fecal inoculum blend supplemented with test products, then sealed individually, before being rendered anaerobic. Blend M0003 was used for the preparation of the nutritional medium (Cryptobiotix, Ghent, Belgium). After preparation, bioreactors were incubated under continuous agitation (140 rpm) at 37 °C for 48 h (MaxQ 6000, Thermo Scientific, Thermo Fisher Scientific, Merelbeke, Belgium). Upon gas pressure measurement in the headspace, liquid samples were collected for subsequent analysis. Fresh fecal samples were collected according to a procedure approved by Ethics Committee of the University Hospital Ghent (reference number BC-09977). This involved participants signing an informed consent to donate their fecal sample for the current study. The selection criteria for the 6 donors used were as follows: age 25–65, no antibiotic use in the past 3 months, no gastro-intestinal disorders (cancer, ulcers, IBD), no use of probiotic, non-smoking, alcohol consumption < 3 units/d, and BMI < 30. For this specific study, four male and two female donors were tested with an average age of 28.8 ± 1.6 years. ## 4.3. Study Design Six study arms were tested for each of the six fecal microbiota: (i) NSC containing background medium and fecal microbiota without products, (ii) LGG, (iii) REU, (iv) TB, (v) TB + LGG, and (vi) TB + REU (Figure 7). The NSC was tested in technical triplicate to confirm the previously demonstrated high technical reproducibility of the SIFR® technology [37], which allows focusing on biological replicates rather than technical replicates, as was also the case in the current study, where all treatments were tested for six independent donors (as biological replicates). Samples were collected at 0 h and 48 h for fundamental fermentation parameters (pH, gas, SCFA and bCFA) and microbial composition (shallow shotgun sequencing) (Figure 6). LGG and REU were additionally quantified via culture-based enumeration at 0 h and 48 h. The untreated no-substrate control (NSC) incubations were additionally run in $$n = 3$$ for each donor ($$n = 6$$). Coefficients of variation of pH, gas production, and the three main SCFA (acetate, propionate, and butyrate), were on average as low as $1.74\%$, which comprises all variation from medium and inoculum preparation up to sample analysis. Such high reproducibility renders the SIFR® technology sensitive to unraveling the impact of test ingredients on the complex gut microbiota. ## 4.4. Fundamental Fermentation Parameters SCFA (acetate, propionate, butyrate, and valerate) and branched-chain fatty acids (bCFA; sum of isobutyrate, isocaproate, and isovalerate) were determined via GC with flame ionization detection (FID) (Trace 1300, Thermo Fisher Scientific, Merelbeke, Belgium), upon diethyl ether extraction. Briefly, 0.5 mL samples were diluted in distilled water (1:3) and acidified with 0.5 mL $48\%$ sulfuric acid, after which an excess of sodium chloride was added along with 0.2 mL internal standard (2-methylhexanoic acid) and 2 mL diethyl ether. Upon homogenization and subsequent separation of the water and diethyl ether layer, diethyl ether extracts were analyzed on the GC-FID using nitrogen gas as carrier and makeup gas as previously described [65]. pH was measured using an electrode (Hannah Instruments Edge HI2002, Temse, Belgium). ## 4.5. Selective Enumeration of Lactobacillaceae species (LGG and REU) At 0 h and 48 h, samples were collected from different rectors and viable counts of Lactobacillaceae species were determined by making dilution series in PBS, followed by selective enumeration on LAMVAB agar [64], and incubated aerobically (LGG) or anaerobically (REU) during 48 h. ## 4.6. Microbiota Phylogenetic Analysis via Shallow Shotgun Sequencing Initially, a bacterial cell pellet was obtained by centrifugation of 1 mL sample for 5 min at 9000× g. DNA was extracted via the SPINeasy DNA Kit for Soil (MP Biomedicals, Eschwege, Germany), according to manufacturer’s instructions. Subsequently, DNA libraries were prepared using the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA) and IDT Unique Dual Indexes with total DNA input of 1 ng. Genomic DNA was fragmented using a proportional amount of Illumina Nextera XT fragmentation enzyme. Unique dual indexes were added to each sample followed by 12 cycles of PCR to construct libraries. DNA libraries were purified using AMpure magnetic Beads (Beckman Coulter, Brea, CA, USA), eluted in QIAGEN EB buffer, quantified using a Qubit 4 fluorometer and a Qubit dsDNA HS Assay Kit, and sequenced on an Illumina Nextseq 2000 platform 2 × 150 bp. Unassembled sequencing reads were converted to relative abundances (%) using the CosmosID-HUB Microbiome Platform (CosmosID Inc., Germantown, MD, USA) [66,67]. ## 4.7. 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--- title: Identification and Characterization of Metabolic Subtypes of Endometrial Cancer Using a Systems-Level Approach authors: - Akansha Srivastava - Palakkad Krishnanunni Vinod journal: Metabolites year: 2023 pmcid: PMC10054278 doi: 10.3390/metabo13030409 license: CC BY 4.0 --- # Identification and Characterization of Metabolic Subtypes of Endometrial Cancer Using a Systems-Level Approach ## Abstract Endometrial cancer (EC) is the most common gynecological cancer worldwide. Understanding metabolic adaptation and its heterogeneity in tumor tissues may provide new insights and help in cancer diagnosis, prognosis, and treatment. In this study, we investigated metabolic alterations of EC to understand the variations in metabolism within tumor samples. Integration of transcriptomics data of EC (RNA-Seq) and the human genome-scale metabolic network was performed to identify the metabolic subtypes of EC and uncover the underlying dysregulated metabolic pathways and reporter metabolites in each subtype. The relationship between metabolic subtypes and clinical variables was explored. Further, we correlated the metabolic changes occurring at the transcriptome level with the genomic alterations. Based on metabolic profile, EC patients were stratified into two subtypes (metabolic subtype-1 and subtype-2) that significantly correlated to patient survival, tumor stages, mutation, and copy number variations. We observed the co-activation of the pentose phosphate pathway, one-carbon metabolism, and genes involved in controlling estrogen levels in metabolic subtype-2, which is linked to poor survival. PNMT and ERBB2 are also upregulated in metabolic subtype-2 samples and present on the same chromosome locus 17q12, which is amplified. PTEN and TP53 mutations show mutually exclusive behavior between subtypes and display a difference in survival. This work identifies metabolic subtypes with distinct characteristics at the transcriptome and genome levels, highlighting the metabolic heterogeneity within EC. ## 1. Introduction Endometrial cancer (EC) is the most common gynecological cancer worldwide. EC emerges in the inner lining of the uterus and may spread to the outside of the uterus in advanced stages [1]. The number of EC cases is increasing, with major risk factors being infertility, obesity, and sedentary lifestyles [2]. Traditionally, EC is classified into Type 1 and Type 2 based on clinical, endocrine, and epidemiological observations, or into endometrioid, serous, and clear-cell adenocarcinomas based on histological characteristics [3]. Type 1 ECs are mostly endometrioid adenocarcinomas, estrogen-dependent, and have better survival outcomes [4]. In contrast, Type 2 ECs are predominately serous carcinomas, estrogen-independent, and have a poor survival rate [4]. However, the traditional classification system may not fully capture the complexity of cancers and are prone to differential diagnosis due to interobserver variation between pathologists [5,6]. A comprehensive genomic characterization of EC by the Cancer Genome Atlas (TCGA) provides opportunities for molecular classification of EC [7]. An improved understanding of how various molecular alterations contribute to EC patients’ survival will assist with treatment and therapeutic development. In this work, we hypothesized that EC patients could be stratified into metabolic subtypes based on gene expression profiles to predict patient survival. Metabolic reprogramming is one of the emerging hallmarks of cancer [8]. Cancer cells rewire their metabolism to fulfill their increased demand for nutrients and energy. Cancer cell metabolism is affected by different intrinsic factors, such as mutations, epigenetics, cellular composition, and microbial populations [9]. It is also influenced by extrinsic factors, such as tumor microenvironment, obesity, and diet [9]. Metabolic phenotypes transform over time as tumor growth progresses from early to late stages [9]. These factors contribute to metabolic heterogeneity, resulting in the diverse metabolic profiles of cancer patients. Therefore, comprehending the variations in metabolic processes is crucial. Different pan-cancer studies have used transcriptomic data of adjacent normal and tumor samples to study metabolic pathway changes across various cancers [10,11,12,13,14]. EC samples have significantly upregulated genes involved in carbohydrate metabolism, serine biosynthesis, fatty acid metabolism, TCA cycle, and glutaminolysis. Studies focusing on EC metabolism used differentially expressed genes between adjacent normal and tumor samples to build nomograms for the prognosis of cancer patients [15,16]. Alterations in choline homeostasis have been reported in EC using the nuclear magnetic resonance (NMR) technique [17]. These studies are limited to metabolic alterations between adjacent normal and tumor samples. The metabolic heterogeneity of EC patients is yet to be explored, and it requires an unsupervised approach without prior class label information to identify metabolic subtypes. A systems-level characterization of metabolic subtypes will provide a mechanistic understanding of the disease. Genome-scale metabolic models (GEMs) have been widely used for studying metabolism at the system levels with applications in biotechnology and medicine [18,19]. A GEM is a metabolic network comprising of enzymes, reactions, and metabolites, representing all biochemical reactions of an organism’s metabolism under given conditions. It serves as a scaffold for the integration of omics data. The constraint-based modeling approach (flux balance analysis) allows for integrating omics data with GEMs to generate disease-specific models [20,21]. The metabolic network topology from GEM reconstruction can also be used for the integration of omics data to identify metabolic hotspots and subnetworks specific to a disease condition [22,23,24]. In this work, we analyzed the transcriptomic data of EC patients to identify the metabolic subtypes of EC. A generic human genome-scale metabolic model was used as a scaffold for subtype identification and characterization. We also examined the characteristics of each subtype at the genomic level. Our study provides subtype-specific biomarkers and reporter metabolites, which will be helpful in the diagnosis and prognosis of EC. ## 2.1. Datasets and Data Pre-Processing We downloaded the TCGA RNA-*Seq data* (HTSeq Count) of EC using TCGAbiolink [25]. The TCGA MC3 files were retrieved from The Genomic Data Commons (GDC) portal to analyze the mutation profile of EC patients. The cBioportal was used to obtain the segmented copy number variation datasets [26]. We considered TCGA-Clinical Data Resource (CDR) to retrieve the corresponding clinical annotation for EC patients [27]. For validation, the microarray series dataset (GSE17025, Affymetrix Human Genome U133 Plus 2.0 Array), consisting of 91 EC samples, was downloaded from the NCBI GEO database using the GEOquery package [28]. We employed the human genome-scale metabolic model (HMR2.0) to study cancer metabolism. The model consists of 8181 reactions, 6006 metabolites, and 3765 genes, which describe the standard metabolic processes of a human cell. The TCGA RNA-Seq dataset consists of 565 samples, of which 542 are primary tumor samples (sample type code—01) and 23 are tumor-matched normal samples (sample type code—11). We used variance-stabilizing transformation (VST) to normalize the RNA-Seq raw count data. The validation microarray dataset comprises 79 endometrioid and 12 papillary serous samples with various grades. We normalized the microarray data using Affymetrix’s MAS5.0 algorithm and log2 transformation. ## 2.2. Identification of Metabolic Subtypes The pipeline for identifying and characterizing metabolic subtypes of EC using the transcriptomic data is shown in Figure 1. The metabolic genes present in the human genome-scale metabolic model (HMR2.0) were considered for the analysis. HMR2.0 has been extensively used for generating metabolic models of normal tissues and disease conditions [29,30,31,32,33]. Out of 3765 metabolic genes present in HMR2.0, 3584 were present in the gene expression dataset. The median absolute deviation (MAD) was computed for all metabolic genes. The top 1000 genes based on the MAD score were selected as a seed list for dimension reduction and clustering. This pre-filtering step eliminates the majority of genes and retains only genes with high MAD scores greater than 0.9. We adopted a Non-Negative Matrix Factorization (NMF)-based consensus clustering approach to identify clusters. NMF is a low-rank approximation technique that has been applied in cancer research for clustering gene expression to uncover the most representative genes of a cluster and identify the cancer subtypes [34]. NMF generates a compressed representation of a given matrix without losing relevant information. It facilitates the automatic extraction of meaningful sparse features from high-dimensional data, resulting in a straightforward interpretation of its factors, which is lacking in other matrix factorization techniques, such as SVD or PCA. In NMF, a data matrix X of dimension m×n (m represents the features and n represents the samples) containing non-negative values (i.e., xij>0) is written as an approximate product of the non-negative matrices W and H as follows:X ≈WH Here, W and H refer to the basis/meta-gene matrix and coefficient/meta-profile matrix of the dimensions m×r and r×n, respectively. r denotes the rank of the factor matrices/number of clusters/components, and its value must be an integer with value 0<r≪ minm,n. The objective of NMF is to factorize the matrix X into two low-rank matrices W and H such that it can introduce sparseness into its factors by solving the following non-linear optimization problem:min W∈ℝm×r, H ∈ℝr×n ∥X−WH∥KL2 such that W≥0 and H ≥0KL represents the Kullback–Leibler divergence, which computes the error between the given matrix X and its approximate factors WH. The consensus clustering combines the output of multiple runs of NMF-based clustering results to produce stable clusters. In each iteration, it subsamples the data and constructs a consensus matrix consisting of pairwise values corresponding to the fraction of times two samples were clustered together when they were subsampled. The NMF-based consensus clustering was carried out using the NMF R package (version 0.25) [35]. The silhouette width, dispersion, and cophenetic correlation coefficient were utilized to decide the optimal number of clusters. We also experimented with six different versions of NMF methods (brunet, KL, lee, Frobenius, offset, and nsNMF). The performance of all methods was evaluated on the same criteria used for determining the number of clusters. ## 2.3. Differential Gene Expression Analysis The differential gene expression analysis was performed using the DESeq2 R package (version 1.32.0) to identify metabolic alterations between metabolic subtypes [36]. We also performed differential gene expression analysis between 23 pairs of adjacent normal and tumor samples for a comparative study. The differentially expressed genes (DEGs) were identified based on log2 fold change (FC) (|log2FC|) > 1 and adjusted p-value (adj p-value) < 0.05. For the GEO dataset, we identified DEGs using the limma R package (version 3.48.3) with criteria of |log2FC| > 0.6 and adj p-value < 0.05 [37]. We considered different log2FC for RNA-Seq and microarray since differences in expression levels can emerge due to the differences in sampling and quantification methodology (sequencing vs. intensity-based). The univariate Cox regression analysis was performed to determine the DEGs significantly associated with the survival outcomes of EC patients. A p-value < 0.05 was considered for identifying prognostic genes. ## 2.4. Reporter Metabolite Analysis We adopted a metabolic-network-topology-based approach to integrate gene expression data with HMR2.0. *The* gene expression changes between subtypes were mapped to a bipartite undirected graph comprising metabolites and enzymes as nodes for identifying reporter metabolites. Integration was performed using p-value and log2FC score, obtained from DESeq2 analysis of metabolic subtypes. The reporter metabolite algorithm utilizes an inverse normal cumulative distribution to convert the p-value of an enzyme into the z-score [22]. Then, the method identifies the enzymes around each metabolite and computes the -Z-score of that metabolite using the following equation:[1]Zmetabolite=1k∑$i = 1$kzi Here, k represents the number of enzymes around each metabolite. A total of 100,000 sets of k enzymes were chosen randomly to correct the Z-score of each metabolite by subtracting the mean (μk) and dividing by the standard deviation (σk) of the aggregated Z-score of all sets. The corrected Z-score was transformed into a p-value. We selected reporter metabolites with a minimum of 3 neighboring genes and a p-value < 0.05. ## 2.5. Association of Metabolic Subtypes with Clinical Information The log-rank test was performed to assess the survival differences between metabolic subtypes. The Kaplan–Meier Plot was generated using the R package. The relationship of metabolic subtypes with clinical variables such as clinical stage, histological type, histological grade, and age was determined by Fisher’s exact test. Cramer’s V, which measures the relationship between categorical variables, was also computed to quantify the association of the clinical variables with the subtypes [38]. Its values vary from −1 to +1. A value of +1 dictates a stronger association, 0 represents no association, and −1 represents a strong association in the opposite direction. ## 2.6. Genomic Profile of Metabolic Subtypes The TCGA somatic mutation data and copy number variation (CNV) datasets were used to assess the unique characteristics of metabolic subtypes at the genome level. The number of somatic mutation and CNV samples was 525 and 534, respectively. The “maftool” R Package (version 2.8.5) was employed to analyze and visualize the mutation profile of metabolic subtypes [39]. The differentially mutated genes between subtypes were identified based on the minimum mutation frequency of 10 using Fisher’s exact test (p-value < 0.01). We used the Genomic Identification of Significant Targets in Cancer (GISTIC) 2.0 method to identify the significant recurrent CNVs specific to each subtype [40]. The analysis was performed with an amplification/deletion threshold > |0.1|, a confidence interval of 0.99, and a q-value < 0.05. The GISTIC results were also visualized with maftools. ## 3.1. Stratification of EC Samples into Two Metabolic Subtypes with Distinct Survival To study metabolic reprogramming in EC, we analyzed the gene expression data of 3765 metabolic genes in the human genome-scale metabolic model HMR2.0. The principal component analysis (PCA) using metabolic genes showed that normal samples had different metabolic gene expression profiles compared to tumor samples, with most of the variance captured by principal components PC1 and PC2 (Figure 2a and Figure S1). It also indicated that the metabolic profile of EC patients was heterogeneous. To discover the metabolic subtypes within EC, we applied the NMF method to cluster the EC patients using the expression profile of the top 1000 metabolic genes filtered based on the MAD score. We ran different NMF algorithms with default parameters for 2000 iterations. This was repeated 50 times with random subsampling to generate a consensus matrix. Different cluster sizes (2 to 7) were experimented with to tune the optimal number of clusters (Figure 2b). We identified the optimal number of clusters based on silhouette width, dispersion, and cophenetic correlation coefficient. The offset NMF technique achieved the best performance (silhouette width = 0.98, dispersion = 0.96, cophenetic = 0.995) among the different variants of NMF methods, which yielded two clusters (Figure 2c). We also varied the input metabolic genes and observed that considering all or only the top few features decreased the performance (Table S1). However, the optimal number of clusters obtained was always two with almost similar cluster sizes. The 542 EC patients were clustered into two subtypes: metabolic subtype-1 consisted of 309 patients, and metabolic subtype-2 consisted of 233 patients. To assess the survival difference between subtypes, we performed an overall survival analysis. Both subtypes showed significant differences in survival outcomes (p-value < 0.001). Metabolic subtype-1 was associated with better survival, while metabolic subtype-2 was associated with poor survival (Figure 2d). ## 3.2. Metabolic Subtypes Show Association with Histological Characteristics Figure 3 shows the subtype-wise distribution across stages, histological types, grades, and ages. Fisher’s exact test showed that both subtypes are significantly related to the clinical variables (p-value < 0.05) (Table S2). Metabolic subtype-1 is dominated by stage 1 samples, whereas metabolic subtype-2 is dominated by stage 3 and stage 4 samples (Figure 3a). Stage 2 samples are almost equally distributed into both subtypes. The Cramer’s V value of 0.36 shows a moderate association between clinical stage and metabolic subtypes. Metabolic subtype-1 mainly consists of endometrioid samples, while metabolic subtype-2 comprises all histological types (Figure 3b). Both serous and endometrioid types have an almost equal distribution in subtype-2 samples. The Cramer’s V value of 0.61 describes strong relationships between metabolic subtypes and histological types. Metabolic subtype-1 consists primarily of grade 1 to 3 samples (Figure 3c). However, the grade 3 samples are more in metabolic subtype-2 compared to metabolic subtype-1. All high grades samples only belong to metabolic subtype-2. The Cramer’s V value for a histological grade is 0.58, which indicates a strong relationship between them. In addition, we divided the samples into two categories to perform Fisher’s exact test between age and clusters (<50 years and ≥50 years). The association of age with metabolic subtypes is significant (p-value = 0.02), but Cramer’s V value for age is very small (0.098), indicating a negligible association of metabolic subtypes with age (Figure 3d). ## 3.3. Metabolic Gene Alterations in EC To identify the unique metabolic characteristics of metabolic subtypes at the transcriptome level, we performed differential gene expression analysis of 3584 metabolic genes between metabolic subtype-1 and subtype-2. There were 264 upregulated and 137 downregulated genes between metabolic subtype-1 and subtype-2 samples based on the criteria of |log2FC| > 1 and adj p-value < 0.05 (Data S1). The top candidate genes are shown in Figure 4a. We also analyzed differential gene expression between adjacent normal and tumor samples to study the overlap with metabolic subtypes. We identified 971 DEGs (517 upregulated and 454 downregulated) between normal and tumor samples (Data S1). The overlap of DEGs between both analyses shows that there are only 46 genes that are upregulated in both metabolic subtype-2 and tumor samples (Figure 4b). *Most* genes [151] were uniquely upregulated in metabolic subtype-2, indicating a different set of genes responsible for cancer progression in metabolic subtype-2 samples. Genes of the glycolysis pathway (SLC2A1, HK2, GPI, FBP1, FBP2, PFKFB1, PFKFB2, PFKFB4, TPI1, GAPDH, PGK1, ENO1, ENO2, and PKM) were upregulated in EC (Figure 4c). PDK1 inhibits oxidative decarboxylation of pyruvate by PDH and is upregulated in EC samples along with LDHA, which controls the interconversion of pyruvate and lactate. Further, two critical enzymes of the PPP: G6PD, which catalyzes the conversion of glucose-6-phosphate into 6-phosphogluconolactone, and PGD, which yields ribulose 5-phosphate by catalyzing the oxidative decarboxylation of 6-phosphogluconate, are upregulated in EC samples. PPP plays a role in the synthesis of nucleotides and in generating coenzymes to maintain redox homeostasis. Further, enzymes of the non-oxidative phase of the PPP (TKT, TALDO1) are also upregulated in EC samples. Interestingly, TKTL1, another critical enzyme that connects the PPP with glycolysis by converting D-xylulose 5-phosphate into D-glyceraldehyde 3-phosphate, is upregulated in metabolic subtype-2 samples (log2FC = 5.91). We observed that the genes (BHMT, PSAT1, AGXT, DAO, GLDC, and CBS) involved in glycine, serine, and threonine metabolism were upregulated in metabolic subtype-2 samples (Figure 4c). PSAT1 catalyzes the conversion of 3-phosphohydroxypyruvate to phosphoserine, which is further used in the formation of serine. Downregulation of PSAT1 promotes growth inhibition and induces apoptosis [41]. Cells with high PSAT1 levels increase the ratio of reduced GSH (glutathione) to oxidized GSSG (Glutathione disulfide) and lower ROS. GLDC catalyzes the conversion of glycine to 5,10-methyleneteTHF, which is an essential intermediate in the folate cycle. CBS, a vital gene of the transsulfuration pathway, catalyzes the conversion of serine to cystathionine, the precursor of L-cysteine. BHMT catalyzes the conversion of homocysteine to methionine and dimethylglycine using choline-derived betaine as a methyl donor. We also observed genes involved in glycine, serine, and threonine metabolism (GLDC, PSAT1, SHMT2, GCAT, and SDS) to be upregulated in EC samples. However, the expression of GLDC and PSAT1 was very high in metabolic subtype-2 samples. Estrogen sulfotransferase enzyme SULT1E1 was upregulated in metabolic subtype-2 samples. SULT1E1 catalyzes the sulfation of estrogens (estradiol and estrone) and catechol estrogens. UGT1A1 of the glucuronidation pathway was upregulated in metabolic subtype-2 samples. It encodes the UDP-glucuronosyltransferase enzyme, a major contributor to the glucuronidation activity associated with estrogens and catechol estrogens. Cytochrome P450 gene CYP1A1 is also upregulated in metabolic subtype-2 samples. CYP1A1 catalyzes the 2-OH hydroxylation of estrogens. This suggests that metabolic subtype-2 may be less related to estrogen exposure compared to metabolic subtype-1 samples. 17β-hydroxysteroid dehydrogenases HSD17B7 and HSD17B2, involved in the interconversion between estrone and estradiol, were upregulated in EC samples. On the other hand, CYP1B1, which catalyzes the 4-OH hydroxylation of estrogens, was downregulated in EC samples. The glutathione S-transferase enzymes (GSTA1, GSTA2, GSTA3, GSTM1, GSTM2, GSTM3, and GSTM5) were also downregulated in EC samples. GSTs play a role in the inactivation of catechol estrogen. These observations indicate that estrogen exposure plays a critical role in the development of EC. On the other hand, we observed genes (GGT1, GGCT, OPLAH, ANPEP, G6PD, PGD, IDH1, IDH2, GPX2, GPX7, and GSR) that control the intracellular content of glutathione through de novo synthesis and regeneration of GSH from GSSG to be upregulated in EC samples, consistent with previous studies [42]. GGT1, GGCT, OPLAH, and ANPEP play critical roles in synthesizing glutathione from glutamate, cysteine, and glycine. Similarly, the upregulation of G6PD, PGD, IDH1, and IDH2 can increase NADPH, which is required to reduce glutathione. GPX2 and GPX7 are involved in converting GSH to GSSG to reduce hydrogen peroxide and superoxide radicals, while GSR catalyzes the reduction of GSSG to GSH. The expression of genes in the urea cycle (ASS1, CPS1, OTC, SLC25A13, and SLC25A15) is altered in EC samples. Urea cycle dysregulation promotes nitrogen utilization for pyrimidine synthesis [43]. Downregulation of ASS1 expression promotes cancer proliferation by diversion of its aspartate substrate toward the pyrimidine synthesis pathway [44,45]. SLC25A13, which exports aspartate from the mitochondria, is upregulated in EC samples. ## 3.4. Prognostic Metabolic Genes of EC We performed a univariate Cox regression analysis to discover the prognostic genes, which are differentially expressed between metabolic subtypes. We observed that 225 DEGs in metabolic subtype-2 samples are associated with the survival of EC patients (Data S1). Among them, the high expression of 156 genes is associated with poor survival (hazard ratio > 1), while the high expression of 69 genes is related to better survival outcomes (hazard ratio < 1). There are 86 genes that are only upregulated in metabolic subtype-2 samples and have a significant association with survival outcomes. These include genes of amino acid metabolism (PNMT, DDC, BHMT, CBS, TH, and GLS), estrogen metabolism (SULT1E1, UGT1A1, CYP1A2, and ERBB2), fatty acid synthesis (ELOVL2, ELOVL4, and ELOVL7), and amino acid transporters (SLC38A1 and SLC38A3). High expression of these genes corresponds to poor survival of EC patients. On the other hand, genes involved in glycerophospholipid metabolism (LPCAT2, PLA2G2C, PLA2G2D, PLA2G10, GPCPD1, and PLPP2) were downregulated in metabolic subtype-2 samples, and their low expression is correlated with poor survival outcomes. We also identified GCK, PSAT1, GLDC, and UGT3A1 as prognostic markers for EC. They were DEGs in normal vs. tumor and metabolic subtype-1 vs. metabolic subtype-2 comparisons. ## 3.5. Reporter Metabolites Further, we performed reporter metabolite analysis to identify altered metabolites between metabolic subtype-1 and subtype-2 and adjacent normal and tumor samples. The analysis was performed with all DEGs, upregulated DEGs, and downregulated DEGs in metabolic subtype-2 and all tumor samples. We mapped the reporter metabolites with HMR2.0 metabolic pathways to infer the altered pathway. The metabolites of one-carbon metabolism (betaine, Choline, Glycine, serine, threonine, homocysteine, methionine, and THF) and the PPP (fructose-6-phosphate, ribose-5-phosphate, D-Xylulose-5-phosphate, and erythrose-4-phosphate) are reporter metabolites of metabolic subtype-2 samples (Figure 5). Both one-carbon metabolism and PPP are at the crossroads of anabolism and redox homeostasis. We also found glutamine to be a reporter metabolite in metabolic subtype-2 samples. In addition, the metabolites of fatty acid synthesis, fatty acid elongation, omega-3 fatty acid metabolism, and omega-6 fatty acid metabolism are associated with upregulated genes of metabolic subtype-2 samples (Figure S2). In EC samples, we observed SAM and SAH to be reporter metabolites, along with metabolites of glycolysis (fructose-6-phosphate, fructose-2,6-bisphosphate, and Glyceraldehyde-3-phosphate (GAP)), PPP (ribose-5-phosphate and ribulose-5-phosphate), TCA cycle (succinyl-CoA, isocitrate, and oxalate) and lysine metabolism (L-lysine, N6,N6-dimethyl-L-lysine, N6,N6,N6-trimethyl-L-lysine, Histone-L-lysine, and histone-N6-methyl-L-lysine). On the other hand, the metabolites associated with downregulated genes of metabolic subtype-2 samples map to phenylalanine, tyrosine, and tryptophan biosynthesis, sphingolipid metabolism, and glycerophospholipid metabolism (Figure 5 and Figure S2). ## 3.6. Genomic Alterations of Metabolic Subtypes Next, we utilized somatic mutation and CNV datasets to characterize each subtype at the genome level. The somatic mutation datasets for metabolic subtype-1 and subtype-2 consisted of 300 samples (out of 309) and 225 samples (out of 233), respectively. Table S3 summarizes the mutation profile of metabolic subtype-1 and subtype-2 samples. The mean Tumor Mutation Burden (TMB) per Mb of metabolic subtype-2 (32.38) was higher compared to metabolic subtype-1 (25.78) samples. The five most frequently mutated genes in metabolic subtype-1 samples were PTEN ($90\%$), AR1D1A ($56\%$), PIK3CA ($55\%$), TTN ($40\%$), and PIK3R1 ($39\%$) (Figure 6). On the other hand, TP53 ($70\%$), PIK3CA ($44\%$), TTN ($39\%$), PTEN ($32\%$), and PPP2R1A ($30\%$) were the top five frequently mutated genes in metabolic subtype-2 samples (Figure 6). TTN is frequently mutated in both subtypes. We compared the mutation profiles of metabolic subtypes and identified 72 differentially mutated genes (p-value < 0.01) between the subtypes. Out of 72, 16 genes were enriched in metabolic subtype-1, while 56 were differentially mutated in metabolic subtype-2 samples. Interestingly, we found four metabolic genes (UBIAD1, PDK1, GOT2, and CYP1A1) to be enriched in metabolic subtype-2 samples. UBIAD1 plays a crucial role in cholesterol and phospholipid metabolism. It has tumor suppressor function, and its loss leads to tumor progression with elevated cholesterol levels [46]. GOT2 encodes a mitochondrial enzyme that maintains aspartate-malate shuttle and redox balance and helps cancer cells to proliferate by raising the intracellular aspartate level [47]. CYP1A1, a key enzyme of estrogen metabolism, is also associated with breast cancer proliferation and survival [48]. The forest plot shows the differentially mutated genes, including PTEN, TP53, PPP2R1A, AR1D1A, CTNNB1, PIK3R1, KRAS, CTCF, GOLGA8, and CSNK1A1 (Figure 7a). Metabolic subtype-2 includes samples with TP53 mutation, while metabolic subtype-1 has PTEN mutations. To further investigate, we analyzed the co-occurrence/mutually exclusive relationships of the 20 most frequently mutated genes in both subtypes. Figure 7b shows that TP53 and PTEN exhibit mutually exclusive behavior (p-value < 0.01). TP53 is also mutually exclusive with other frequently mutated genes in metabolic subtype-2 samples, except for PPP2R1A. It has also been reported that PPP2R1A mutation is associated with poor survival in breast cancer, lung cancer, and melanoma [49]. The co-occurrence of PTEN along with OBSCN, ZFHX3, KMT2D, MUC16, and TTN was observed in metabolic subtype-1 and metabolic subtype-2 samples (Figure 7b). Further, we performed a survival analysis of the frequently mutated genes to reveal their impact on the survival outcomes of EC patients. Among these genes, six genes had a significant (p-value < 0.05) association with survival (Table S4). Patients with PTEN mutation have better survival than those without PTEN mutation (Figure 8). Similarly, the genes AR1D1A, MUC16, PIK3CA, and CTNNB1 are related to better survival (hazard ratio < 1) of EC patients (Figure 8). In contrast, patients with TP53 are significantly associated with poor survival. The CNV datasets consist of 534 samples, with 303 samples in metabolic subtype-1 and 231 in metabolic subtype-2. We employed GISTIC 2.0 to examine the CNVs in each subtype and identified 27 (10 amplified and 17 deleted) and 108 (53 amplified and 55 deleted) significant CNVs in metabolic subtype-1 and metabolic subtype-2 samples, respectively. These CNVs of metabolic subtype-1 and metabolic subtype-2 mapped to 23 and 103 chromosome loci, respectively. There were 19 common chromosome loci in metabolic subtype-1 and subtype-2 samples. We observed that metabolic subtype-1 samples have very few CNVs (amplifications and deletions) compared to metabolic subtype-2 samples (Figure 9a). The genome plot shows the chromosome locus of the top 10 most significant CNVs (sorted based on q-value) of metabolic subtype-1 and subtype-2 samples (Figure 9b). We found four chromosome locations were only altered in metabolic subtype-2 samples: 19p13.3, 17q12, 5q12.1, and 4q34.3. Two CNVs corresponding to chromosome locus 19p13.3 were deleted in over $50\%$ of metabolic subtype-2 samples. Frequent deletion of 19p13 has been observed in ovarian cancer and metastatic melanoma [50,51]. Further, the significant CNVs of metabolic subtype-1 and subtype-2 samples mapped to 1567 and 4264 genes, respectively. Interestingly, we found 11 metabolic gene alterations that also showed consistent changes at the transcriptomic level in metabolic subtype-2 samples. These include eight amplified genes (PNMT, ERBB2, ZDHHC19, OXCT2, CARNS1, SLC38A3, SLC6A19, and SLC6A3) and three deleted genes (DPEP1, GCNT3, and FTMT) that are upregulated and downregulated in metabolic subtype-2 samples, respectively. PNMT, a key enzyme of catecholamine (CAT) synthesis, catalyzes the synthesis of adrenaline from noradrenaline by transferring the methyl group from SAM. We also found PNMT to be a prognostic marker for EC. PNMT, along with the ERBB2 gene, is located on chromosome 17q12, which is amplified in $35\%$ of metabolic subtype-2 samples. ERBB2 controls the activation of estrogen receptors (ESR1 and ESR2) and regulates estrogen metabolism. ZDHHC19 is amplified in more than $60\%$ of metabolic subtype-2 samples. It is an oncogene involved in leukotriene metabolism and is present on chromosome locus 3q29 along with PPP1R2. OXCT2 plays an essential function in ketone body catabolism by converting fatty acids to ketone bodies. CARNS1(11q13.2), SLC38A3 (3p21.31), and SLC6A19 (5p15.33) are involved in the synthesis of carnosine, transportation of glutamine, and neutral amino acid, respectively. The high expression of dopamine transporter SLC6A3 (5p15.33) has been observed in multiple cancers [52,53]. DPEP1 (16q24.3) is deleted in more than $60\%$ of metabolic subtype-2 patients, and it catalyzes the conversion of leukotriene D4 to leukotriene E4. FTMT (5q12.3) regulates the iron levels in mitochondria and cytosol. The high expression of this gene affects cellular iron homeostasis and inhibits the proliferation of cancer cells [54]. GCNT3 (15q14) was also deleted in metabolic subtype-2 samples (>$50\%$). It plays an essential role in mucin biosynthesis and is a prognostic marker in EC. ## 3.7. Validation of Metabolic Subtypes We used independent GEO microarray data to validate our results. Out of 1000 MAD genes used for clustering, 932 metabolic genes that overlap with the GEO dataset were considered for NMF clustering with identical parameters. We obtained two metabolic subtypes with cophenetic and silhouette coefficients of 0.98 and 0.91, respectively, which displayed consistency with the TCGA cohort (Figure S3a). Metabolic subtypes correlated significantly (p-value < 0.05) with histological types and grades. Further, the DEGs identified between subtypes overlapped with candidates from the TCGA cohort and showed similar expression patterns (Figure S3b). The expression patterns of some candidate genes are shown in Figure 10. ## 4. Discussion Previous studies demonstrated that cancer tissues exploit different metabolic pathways to produce energy and biomolecules, along with maintaining redox homeostasis [10,11]. The utilization of various mechanisms depends on intrinsic and extrinsic factors which contribute to heterogeneity in the metabolic profiles of cancer patients. Earlier studies on EC analyzed the difference in the expression of metabolic genes between adjacent normal and tumor samples [15,16]. In this study, we aimed to explore the metabolic heterogeneity within EC. To this end, we applied an unsupervised technique to stratify EC samples into metabolic subtypes based on a genome-scale metabolic model (HMR2.0) and characterized each subtype for survival outcomes, clinical features, metabolic pathways, and genomic alterations. We also compared the metabolic dysregulation of subtypes with changes between normal and tumor conditions. In addition, we leveraged the transcriptomic data to extract reporter metabolites for distinguishing subtypes and normal and tumor conditions. The consensus clustering of metabolic genes of HMR2.0 based on transcriptomic data of EC revealed two metabolic subtypes (Figure 2). These subtypes significantly correlated to clinical characteristics, including survival, tumor stages, grades, and histological types (Figure 3). This indicates that transcriptomic changes of metabolic genes capture the genotypic-phenotypic relationship. Metabolic subtyping provides molecular insights into the previously established classification scheme of EC. Our analysis of differences between subtypes showed the co-activation of the PPP and one-carbon metabolism in metabolic subtype-2 with poor survival characteristics (Figure 4 and Figure 5). This intersection of metabolic pathways may facilitate the balance between the production of nucleotides and antioxidant species, which support a high proliferation rate and provide defense against oxidative stress [55]. Accordingly, we also observed glycolytic genes to be upregulated in EC, which is consistent with previous studies [15,56]. The candidate genes of PPP include TKTL1, which is upregulated in metabolic subtype-2 samples. The transketolase enzyme is part of the non-oxidative branch of PPP that plays a crucial role in the ribose synthesis required for nucleotides. TKTL1 protein has also been shown to be overexpressed in EC [57]. It is related to poor survival in different cancers, and inhibition of TKTL1 leads to a significant reduction in the proliferation of many cancers [58]. GCK, a prognostic candidate gene of the hexokinase family, is upregulated in metabolic subtype-2 samples, and its high expression is associated with poor survival. We observed metabolites of one-carbon metabolism as reporter metabolites (Figure 5). Overexpression of genes involved in the serine biosynthesis pathway is also related to poor survival in breast cancer [55]. Serine and glycine provide one-carbon units for nucleotide synthesis through the folate cycle and contribute toward mitochondrial NADPH production. We found folate receptor FOLR3 to be upregulated in metabolic subtype-2 samples, and its overexpression has been reported in ovarian cancer (Figure 4a) [59]. One-carbon metabolism also contributes to the production of SAM, which is a reporter metabolite in EC samples. SAM is used in the methylation of biomolecules through the methionine cycle. In metabolic subtype-2 samples, we observed choline and betaine as reporter metabolites used in the production of methionine from homocysteine (Figure 5). These are unreported changes in EC, and the upregulation of BHMT is associated with poor survival. Serine can also be used in the production of cysteine (through the transsulfuration pathway), which is utilized in the synthesis of glutathione. CBS, involved in the first step of the transsulfuration pathway, is upregulated in metabolic subtype-2 samples and is associated with poor survival. The elevated expression of CBS is responsible for inducing tumor growth in other gynecological cancers, including ovarian and breast cancer [60]. The changes in one-carbon metabolism may mirror the DNA methylation frequency observed in high-grade tumors [61]. The serum metabolic signature of EC includes serine and homocysteine [62,63]. The upregulation of choline in one-carbon metabolism is also consistent with the metabolic profiling using NMR [17]. The prognostic candidates include genes of estrogen metabolism. EC is characterized by elevated estrogen exposure. Upregulation of SULT1E1 can inactivate the estrogens in metabolic subtype-2 samples and contribute to the difference in estrogen levels of both subtypes. In metabolic subtype-2 samples, we observed high expression of ERBB2, which is correlated with poor survival of EC patients [64]. GLS, an essential gene involved in the hydrolysis of glutamine, is also upregulated in metabolic subtype-2 samples. It has been shown that GLS in EC is regulated by estrogen [65]. Although only metabolic gene expression data was used for clustering, subtypes identified are described by distinct mutation and CNV patterns capturing the relationship between genomic alterations and metabolic gene expression (Figure 6 and Figure 7). Metabolic subtype-1 samples are associated with PTEN mutation and low CNVs, whereas metabolic subtype-2 samples are associated with TP53 mutation and high CNVs. Both PTEN and TP53 are tumor suppressor genes, and their suppressor functions are associated with cytoplasm and nucleus, respectively [66]. PTEN and TP53 also regulate various metabolic processes to maintain cellular homeostasis [67,68]. We observed a mutually exclusive PTEN and TP53 mutation pattern in metabolic subtype-2 samples. Kurose et al. [ 2002] showed that PTEN and TP53 mutations are mutually exclusive in breast cancer [69]. We also observed that PTEN and TP53 mutations have opposite survival outcomes in EC (Figure 8). Somatic mutation in PTEN is associated with better survival, while TP53 mutation is related to poor survival. This finding is consistent with the observations made by Risinger et al. [ 1998] [70]. ARID1A mutation exists in the preneoplastic stages, and its loss may not be enough to develop EC [71]. In addition, PNMT and ERBB2 were upregulated, amplified, and present in the same chromosome locus, 17q12, in metabolic subtype-2 samples (Figure 9b). We identified PNMT and ERBB2 as prognostic genes for EC. Gene amplification and coexpression of PNMT and ERBB2 have been observed in breast cancer patients [72]. Further, 17q12 amplification is related to high-grade breast cancer and has been associated with poor outcomes [73]. In the TCGA study, Levine et al. [ 2013] identified four clusters using CNV data from 363 EC patients [7]. The TCGA cluster-1 samples have a few genomic alterations, while cluster-2 and cluster-3 samples are distinguished by 1q amplification. Cluster-4 comprises many amplified chromosome locations, including 8q11.23 (SOX17), 19q12 (CCNE1), and 4p16.3 (FGFR3) and deletion of LRP1B. In our study, we observed very few significant CNVs in metabolic subtype-1 samples and amplification of 1q, 8q11.23 (SOX17), 19q12 (CCNE1), and 4p16.3 (FGFR3) in metabolic subtype-2 samples. These observations indicate that metabolic subtype-1 has the characteristics of TCGA cluster-1 and cluster-2 samples based on CNV data, while metabolic subtype-2 has the characteristics of TCGA cluster-3 and cluster-4 samples. Additionally, metabolic subtype-1 samples exhibit characteristic features of Type 1 EC, while metabolic subtype-2 samples have the characteristics of Type 2 EC based on the association of clusters with survival outcomes, mutation status, and distinct CNVs. ## 5. Conclusions Our study revealed the metabolic heterogeneity within EC and identified subtypes with distinct transcriptomic, genomic, and clinical features. Although there are fewer mutations, amplifications, and deletions in metabolic genes, the metabolic changes observed at the transcriptome level are associated with the overall genomic changes observed in EC, highlighting the relationship between different data. Metabolic subtyping also suggested that some early and late-stage samples are clustered together, which requires further investigation to understand the molecular variation. Metabolomic profiling of EC tumor samples is required to validate reporter metabolites. 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--- title: Association of physical activity and fine motor performance in individuals with type 2 diabetes mellitus and/or non-alcoholic fatty liver disease authors: - Ali A. Weinstein - Dung Ngo - Leyla de Avila - Jillian K. Price - Pegah Golabi - Patrick Austin - Carey Escheik - Lynn H. Gerber - Zobair M. Younossi journal: Annals of Medicine year: 2023 pmcid: PMC10054279 doi: 10.1080/07853890.2023.2193422 license: CC BY 4.0 --- # Association of physical activity and fine motor performance in individuals with type 2 diabetes mellitus and/or non-alcoholic fatty liver disease ## Abstract ### Background Fine motor performance may serve as an early warning sign for reduced cognitive function. Physical activity can help preserve cognitive function; however, the relationship between fine motor performance and physical activity is not well understood. Therefore, this study examined the relationship between fine motor performance and physical activity in individuals at risk for developing cognitive impairment (those with diabetes and/or non-alcoholic fatty liver disease (NAFLD)). ### Patients and methods Individuals aged 25–69 with and without diabetes and NAFLD were enrolled. For this cross-sectional study, all participants completed the Human Activity Profile and fine motor performance tasks (Grooved Pegboard Test and Trail Making Test). ### Results There were 93 participants in the study (NAFLD only ($$n = 29$$); diabetes + NAFLD ($$n = 34$$), controls ($$n = 30$$)). Individuals with both diabetes and NAFLD were less physically active and performed slower on the fine motor performance task. A statistically significant correlation was found between physical activity and motor speed among those with NAFLD only ($r = 0.436$, $p \leq .05$), which remained statistically significant after controlling for body mass index ($r = 0.385$; $p \leq .05$). ### Conclusions This study suggests that those with diabetes + NAFLD have lower levels of physical activity and slower fine motor performance. The relationship between physical activity and fine motor performance was only statistically significant in the group of individuals with NAFLD only. Future research needs to explore the mechanisms that impact fine motor performance and physical activity in individuals at risk for mild cognitive impairment. Individuals with diabetes and/or NAFLD should be identified, advised and encouraged to engage in physical activity. Key MessagesThose with NAFLD and T2DM have lower levels of physical activity and slower fine motor performance compared to controls and those with NAFLD only. Future research needs to explore the mechanisms that impact fine motor performance and physical activity in those with T2DM with or without NAFLD.Individuals with impaired fine motor performance should be identified and encouraged to engage in physical activity. ## Introduction There has been a great deal of interest in understanding the relationships that exist among physical activity, cognitive performance and overall health and longevity [1–3]. As of now, no universally accepted measure is available for assessing mild (early) cognitive impairment (MCI), but some diagnoses have been reported to associate with a higher likelihood of MCI. Type 2 diabetes mellitus (T2DM) is one such condition [4, 5], specifically with performance decrements in the attention, concentration and processing speed domains [6–8]. A highly related diagnosis to T2DM is non-alcoholic fatty liver disease (NAFLD) [9], which is a growing public health problem and the most common chronic liver disease in the world [10,11]. However, only a small portion of research has investigated the specific relationship between NAFLD and cognitive performance [12,13]. T2DM and NAFLD have overlapping risk factors (i.e. obesity) and physical activity is related to reducing risks with both NAFLD [14] and T2DM [15]. An area of cognitive performance that may serve as an early warning sign for overall cognition is reduction in fine motor performance [16,17]. Fine motor performance refers to the coordinated, often purposeful activities of small muscles of the upper extremity and includes prehensile activities, handwriting and manually dexterous tasks. In addition, fine motor performance is related to engagement in physical activity [18–22]. Physical activity, which engages large muscle groups, is associated with arm and lower extremity activity rather than hand and wrist; it increases muscle strength, balance and mobility, thereby promoting function and longevity. In fact, high levels of physical activity can reduce the development of dementia [18, 19,22,23]. As mentioned above, physical activity is an important behaviour for both individuals with T2DM and those with NAFLD [24–26]. An exercise regimen, usually aerobic, is a treatment for these groups to improve metabolic and cardiovascular status. Adherence to this recommendation is notoriously difficult and may be especially ineffective in a population that prefers sedentary behaviours [27]. Determining if fine motor performance correlates with physical activity would help to further justify the prescription of exercise. Therefore, the relationship between physical activity and fine motor performance is an important area to understand, specifically in individuals with NAFLD and/or T2DM, because these individuals are at a greater risk for developing MCI and dementia [28,29]. An area that is particularly challenging is the evaluation of early (mild) cognitive impairment due to a paucity of instruments designed to evaluate this. This is one reason we decided to pursue the use of fine motor performance, an objective, reliable, sensitive and possible early warning sign for cognitive decline [30], see Figure 1 for a conceptual model of the current investigation. The purpose of the current study was to assess the relationship between physical activity and fine motor performance in individuals at risk for developing MCI (individuals with T2DM and/or NAFLD). **Figure 1.:** *Conceptual model of study. Populations are represented with round shapes, behaviours/cognitive performance variables represented in rectangular shapes, and the condition (mild cognitive impairment) represented by a triangle. The variables that are the focus of the current investigation, physical activity and fine motor performance, are represented by filled shapes.* ## Methods Individuals aged 25–69 were enrolled in a cross-sectional research study conducted at the Center for Liver Diseases at Inova Fairfax Hospital in Northern Virginia. Individuals with and without NAFLD and T2DM were recruited throughout the greater Washington D.C., Maryland and Virginia region from September of 2017 through March of 2020. Patients of the Center for Liver Diseases, identified from existing databases, were also recruited. Participants signed an informed consent document and the research was reviewed and approved by Inova Fairfax Hospital’s Institutional Review Board. A total of 93 participants were included for analysis and were divided into the following enrolment groups: [1] NAFLD only ($$n = 29$$); [2] T2DM + NAFLD ($$n = 34$$); and [3] controls ($$n = 30$$) (Figure 2). **Figure 2.:** *Participant flow diagram.* Presence of NAFLD was determined by a radiologist via ultrasound classification and exclusion of other liver diseases (hepatitis B, C, autoimmune liver disease, copper and iron overload, and use of steatogenic medication as determined by review of available clinical records) and excessive alcohol consumption (greater than 14 units/week for males and 7 units/week for females) (one unit of alcohol is ½ pint of beer (285 mL), one glass of spirits (25 mL) or one glass of wine (125 mL)). Presence of T2DM was defined as having a prior diagnosis of T2DM or having a glycated haemoglobin A1C value ≥6.5 upon enrolment. Exclusion criteria were: history of traumatic brain injury, pregnant women or women who were less than 3 months post-partum, and any condition, which in the opinion of the investigator, would make the participants unsuitable for enrolment, or which could interfere with the participant completing the protocol. Participants attended a one-time research visit at the Center for Liver Diseases clinic, where clinical, demographic, questionnaire and neurocognitive data were collected. To measure fine motor performance, the Grooved Pegboard Test (GPEG) was conducted. For GPEG testing, we used a standard GPEG device (Lafayette Instrument Company, Lafayette, IN) and followed published testing procedures [31]. The GPEG test consists of a manual pegboard in which examinees are instructed to: [1] insert pegs one at a time; [2] manipulate the peg, with one hand, in order to match the groove of the peg with the groove of the hole in the board; and [3] fill the rows in a given direction as quickly as possible without skipping any slots. This test is used to measure eye–hand coordination and motor speed, and there are two different trials: dominant hand and non-dominant hand. The score for GPEG is the time (in seconds) it takes for the examinee to finish placing all of the pegs into the board. To further measure fine motor performance, the Trail Making Test (TMT) from the Delis Kaplan Executive Function System (DKEFS) battery was administered [32]. The Motor Speed condition of the TMT was used, as it is the purest measure of fine motor performance. In this condition, the examinee must connect circles together by drawing a line over an existing dotted line as quickly as possible. The Human Activity Profile (HAP) Questionnaire [33] was administered in order to measure level of physical activity and it has previously been used in similar populations [34–36]. It consists of 94 items representing different activities, ranging from very easy (e.g. walking 30 yards) to very strenuous activities (e.g. running 3 miles). Participants were asked to indicate whether they still perform the activity, stopped doing the activity or never performed the activity. Three scores were calculated from the HAP: Maximal Activity Score (MAS), Average Activity Score (AAS) and Metabolic Equivalents Score (METS). MAS is the highest oxygen-demanding activity that the participant still performs representing the current maximum activity level of the respondent; AAS is the number of activities below the MAS that the participant reports as ‘stopped doing’ subtracted from the MAS representing the respondent’s average daily activity level; METS is the level of energy expenditure required to successfully engage in the highest oxygen-demanding activity. The HAP is free to use for research purposes with permission of the senior author of the instrument (D. Daughton). Data were reported as mean ± standard deviation or number and percentages, as appropriate. A p value <.05 was considered statistically significant. To analyse statistically significant differences between the groups, one-way analysis of variance (ANOVA) was used for continuous data, chi-square tests were used for categorical data, and Kruskal–Wallis tests were used for ordinal data. Post hoc tests were used to determine differences between specific treatment groups when the omnibus ANOVA or Kruskal–Wallis test was statistically significant. Pearson’s correlation (for continuous data) and Spearman’s correlation (for ordinal data) analyses were used to investigate relationships between fine motor performance and physical activity. Partial correlation was then used to control for the impact of body mass index (BMI) on bivariate correlations. Statistical analyses were performed using SPSS, Version 27 software (IBM Corp., Armonk, NY). To determine sample size, a power analysis was conducted. The main research question was to examine the relationship between fine motor performance and physical activity; therefore, the study was powered for a correlation analysis. To detect a moderate correlation ($r = 0.05$) [37] with an alpha (two-tailed) level of 0.05 and beta level of 0.20, 29 participants were required for each group. Once each group had at least 29 participants, recruitment was stopped [38]. ## Demographic and participants characteristics The participant characteristics are presented in Table 1. The study included 93 participants with 38 females ($40.9\%$) and 55 males ($59.1\%$). The average age of the participants was 52.2±12.1 years. **Table 1.** | Unnamed: 0 | All (n= 93) | T2DM + NAFLD (n= 34) | NAFLD (n= 29) | Controls (n= 30) | p Value, omnibus test | | --- | --- | --- | --- | --- | --- | | Age (years) | 52.2 (12.1) | 55.9 (9.7) | 50.8 (11.9) | 49.4 (14.0) | .075 | | Gender (female) | 38 (40.9%) | 15 (44.1%) | 9 (31.0%) | 14 (46.7%) | .422 | | BMI (kg/m2) | 30.7 (6.6) | 34.4 (5.3)a | 32.8 (6.4)b | 24.7 (3.0)ab | <.001 | | Race | Race | Race | Race | Race | Race | | White (non-Hispanic) | 58 (62.4%) | 22 (64.7%) | 20 (69.0%) | 16 (53.3%) | .201 | | Hispanic | 6 (6.5%) | 3 (8.8%) | 3 (10.3%) | 0 | .201 | | African American | 11 (11.8%) | 3 (8.8%) | 1 (3.4%) | 7 (23.3%) | .201 | | Asian | 14 (15.1%) | 6 (17.6) | 4 (13.8%) | 4 (13.3%) | .201 | | Other | 3 (3.2%) | 0 | 1 (3.4%) | 2 (6.7%) | .201 | | Highest level of education | Highest level of education | Highest level of education | Highest level of education | Highest level of education | Highest level of education | | High school diploma | 13 (14.0%) | 8 (23.5%) | 3 (10.3%) | 2 (6.7%) | .124 | | College degree | 35 (37.6%) | 13 (38.2%) | 14 (48.3%) | 8 (26.7%) | .124 | | Post graduate degree | 44 (47.3%) | 13 (38.2%) | 12 (41.4%) | 19 (63.3%) | .124 | | Alcohol consumption | Alcohol consumption | Alcohol consumption | Alcohol consumption | Alcohol consumption | Alcohol consumption | | | 40 (43.0%) | 16 (47.1%) | 15 (51.7%) | 9 (30.0%) | .264 | | 1 drink per month | 21 (22.6%) | 7 (20.6%) | 7 (24.1%) | 7 (23.3%) | .264 | | 1–2 drinks per week | 15 (16.1%) | 5 (14.7%) | 1 (3.4%) | 9 (30.0%) | .264 | | 3–6 drinks per week | 10 (10.8%) | 2 (5.9%) | 5 (17.2%) | 3 (10.0%) | .264 | | 1–2 drinks a day | 4 (4.3%) | 2 (5.9%) | 1 (3.4%) | 1 (3.3%) | .264 | | HbA1c (mmol/L) | 6.0 (1.4) | 7.2 (1.7)ab | 5.4 (0.3)a | 5.3 (0.3)b | <.001 | | Hypertension | 44 (47.3%) | 26 (76.5%)ab | 12 (41.4%)a | 6 (20.0%)b | <.001 | | Arthritis | 20 (21.5%) | 9 (26.5%) | 6 (20.7%) | 5 (16.7%) | .588 | | Depression (diagnosed) | 12 (12.9%) | 3 (8.8%) | 3 (10.3%) | 6 (20.0%) | .393 | | Hyperlipidaemia | 44 (47.3%) | 25 (73.5%)ab | 12 (41.4%)a | 7 (23.3%)b | .001 | Statistically significant clinical differences were found between the T2DM + NAFLD group and the control group for BMI, HbA1c, hypertension and hyperlipidaemia ($p \leq .05$, Table 1). In addition, statistically significant differences were found between the T2DM + NAFLD and NAFLD only group for HbA1c, hypertension and hyperlipidaemia. The only statistically significant difference between the NAFLD group and the control group was BMI (Table 1). ## Fine motor performance Statistically significant differences between the T2DM + NAFLD and NAFLD only group were observed for GPEG dominant time and GPEG non-dominant time ($p \leq .05$, Table 2). Significant differences were also observed between the T2DM + NAFLD group and control group for the GPEG dominant time. For all of these, the T2DM + NAFLD group performed slower than their counterparts. However, there were no statistically significant differences between the groups for the TMT Motor Speed Scores. **Table 2.** | Unnamed: 0 | All (n= 93) | T2DM + NAFLD (n= 34) | NAFLD (n= 29) | Controls (n= 30) | p Value, omnibus | | --- | --- | --- | --- | --- | --- | | Motor Speed Score for DKEFS Trail Making Test | 11.3 (1.6) | 10.7 (1.9) | 11.7 (1.2) | 11.5 (1.6) | 0.053 | | Grooved Pegboard Test dominant time | 79.9 (14.8) | 86.9ab (15.1) | 76.8a (13.2) | 75.1b (13.3) | 0.002 | | Grooved Pegboard Test non-dominant time | 86.1 (16.9) | 92.0a (19.9) | 81.9a (13.2) | 83.7 (15.1) | 0.042 | | HAP Maximal Activity Score | 83.7 (10.6) | 79.6a (11.7) | 84.0 (9.1) | 88.2a (8.9) | 0.005 | | HAP Adjusted Activity Score | 80.0 (12.8) | 74.4a (14.3) | 81.0 (10.5) | 85.3a (10.9) | 0.003 | | HAP Metabolic Equivalents | 7.9 (1.5) | 7.2a (1.5) | 8.1 (1.3) | 8.5a (1.3) | 0.002 | ## Physical activity Statistically significant differences between the T2DM + NAFLD group and control group were observed for HAP MAS, HAP AAS and HAP METS (p’s<.05, Table 2). The HAP scores for the control group were significantly higher (indicative of higher activity levels) than the scores for the T2DM + NAFLD group. There were no statistically significant differences in physical activity levels comparing the T2DM + NAFLD group to the NAFLD only group and comparing the NAFLD only group to the control group (Table 2). ## Relationship between fine motor performance and physical activity The correlations between the TMT Motor Speed Score and HAP MAS and HAP AAS were statistically significant for the NAFLD only group (p’s<.05, Table 3). HAP AAS had a slightly higher correlation with the Motor Speed Score compared to HAP MAS for this group. The correlation between the GPEG non-dominant time and HAP AAS (Figure 3) and METS for the NAFLD group was also statistically significant (p’s<.05). HAP METS had a slightly higher correlation with GPEG non-dominant time compared to HAP AAS for the NAFLD group. These statistically significant correlations demonstrated that the higher levels of physical activity were related to better fine motor performance. No statistically significant relationships were found between fine motor performance and physical activity in the control and T2DM + NAFLD groups (p values>.05, Table 3). The correlations between fine motor performance and physical activity were then investigated further by controlling for BMI. The only correlation that remained statistically significant was the relationship between AAS and the Motor Speed Score for the NAFLD Group ($r = 0.385$, Table 4). **Figure 3.:** *Relationship between physical activity and fine motor performance. Scatterplot of the Human Activity Profile Adjusted Activity Score and the Grooved Pegboard Test using the non-dominant hand. The three groups are represented by different colour markers and gender is represented by shape of the marker. The fit lines represent each of the group’s correlation (control: r=–0.077; NAFLD: r=–0.380; T2DM + NAFLD: $r = 0.094$).* TABLE_PLACEHOLDER:Table 3. TABLE_PLACEHOLDER:Table 4. ## Discussion This study aimed to determine the relationship between fine motor performance and physical activity for individuals at risk for developing MCI. In addition, we examined overall differences in fine motor performance and physical activity for a sample of 93 participants categorized by T2DM and NAFLD status. The T2DM + NAFLD group demonstrated slower performance on the GPEG compared to the control group. The T2DM + NAFLD group had consistently lower levels of physical activity than the NAFLD and control groups. Collectively, the data trend reflected that the NAFLD only group performed in between the T2DM + NAFLD and the control group for both physical activity and fine motor performance. The relationship between physical activity and fine motor performance was statistically significant only in the NAFLD group. Specifically, the Motor Speed Score and the GPEG non-dominant time were statistically significantly correlated with physical activity, with the Motor Speed Score correlation with physical activity remaining statistically significant even after controlling for BMI. Previous studies have also established the association between fine motor performance and physical activity [18–21]. Research findings revealed that an increased level of total daily activity and motor abilities can independently increase cognition and reduce dementia [19]. Moreover, physical activity can help alleviate the effects of white matter hyperintensity and motor function [20]. Physical activity can help individuals lead a healthy lifestyle [18–21] by protecting the brain from adverse neurobiological effects [20]. It can also improve motor abilities which provides a cognitive reserve to help maintain cognitive function [19]. In a study completed by Bossers et al. [ 18], a combination of aerobic and strength exercise was effective in decreasing the motor decline seen in dementia patients. Further research is still needed in order to understand the mechanisms that connect fine motor function and physical activity. In the present investigation, only those with NAFLD demonstrated a statistically significant correlation between physical activity and fine motor performance. Previous work in populations with minimal hepatic encephalopathy (related to liver cirrhosis) have demonstrated deficits in fine motor performance [39]. The current population does not have liver cirrhosis, but does demonstrate the beginnings of this motor impairment. Important to identify this early to prevent the continued development of fine motor performance deficits. It is interesting to note, that the correlation between physical activity and fine motor activity in the individuals with T2DM + NAFLD was not statistically significant. A meta-analysis [40] found that dexterity, grip strength and pinch strength did not statistically significantly differ between those with diabetes and those without diabetes. In addition, individuals with diabetes are at increased risk of decreased physical activity that may reflect a link between the metabolic and mechanical functions of muscle [41]. This is in concert with the current findings, that individuals with NAFLD demonstrated a relationship between physical activity, but those with T2DM + NAFLD did not. Those with T2DM + NAFLD may have limited physical activity levels that are independent of fine motor performance. The physical activity level of individuals with only NAFLD may not have been impacted by the link between metabolic and mechanical functions of muscle specific to T2DM, keeping the relationship between physical activity levels and fine motor performance intact. Further research needs to investigate the impact of T2DM metabolic parameters on both physical activity and fine motor performance. NAFLD is a growing public health problem and is the most common chronic liver disease in the world [10,11]. T2DM is frequently associated with NAFLD and research has shown that the prevalence of NAFLD in individuals with T2DM can range from $55\%$ to $87\%$ as there are many common risk factors shared between the two conditions, including hypertension, hyperlipidaemia and obesity [42,43]. An individual’s risk of developing diabetes is increased fivefold if they have NAFLD [44,45]. Therefore, it is important to understand potential differences in those with NAFLD and those with both NAFLD and T2DM. Physical activity may be an effective early intervention for those with NAFLD, as it may prevent progression to developing T2DM + NAFLD. The T2DM + NAFLD group in the current investigation were less physically active and had slower fine motor performance than those with NAFLD. Physical activity can be implemented in an individual’s daily routine to help protect motor functions and has also been shown to prevent complications of NAFLD [14]. Exercise can also be used as an intervention for fat mobilization from the liver [25,46,47]. The combination of exercise and dietary interventions was effective in reducing intrahepatic triglycerides; however, the implementation of exercise only was also beneficial in reducing hepatic lipid levels [25]. Additional evidence also found a reduction in intrahepatic triglyceride to be proportional to the amount of weight loss that occurred [46]. Specifically, the amount of reduction is twofold greater when weight loss is achieved [46]. Therefore, engagement in physical activity can be promoted to mobilize hepatic fat, prevent the development of T2DM, and potentially protect fine motor performance. There were limitations to the current study. The sample recruited was a community-based convenience sample; however, it was not representative of the general population, as it mainly included White (non-Hispanic) and highly educated individuals. Another limitation was the identification of NAFLD, which was determined by a radiologist using ultrasound. Ultrasound is a non-invasive, accessible and accurate tool in detecting NAFLD [48]; however, liver biopsy is the gold standard in diagnosing NAFLD and the most accurate in detecting fibrosis level. The procedure can be invasive and risky due to potential complications [49]. Lastly, while the findings of lower activity levels and slower fine motor performance are statistically correlated, we cannot comment on a causal relationship between the two findings. Nonetheless, recommendations for reducing the likelihood of developing T2DM is likely to be effective in also preserving fine motor performance. ## Conclusions In summary, this study suggests that those with T2DM + NAFLD have lower levels of physical activity and slower fine motor performance compared to controls and those with NAFLD only. Reduced fine motor performance may be an early warning signal for developing MCI [16]. Further research needs to explore the mechanisms that impact fine motor performance and physical activity in those with NAFLD with or without T2DM in order to maintain functional levels and prevent comorbidities and early mortality. Individuals with NAFLD should be identified, advised and encouraged to engage in physical activity. ## Data availability statement The data from this study are available from author AAW (aweinst2@gmu.edu), upon reasonable request. ## Author contributions Study conception and design: Austin, de Avila, Escheik, Gerber, Golabi, Price, Weinstein and Younossi. Acquisition, analysis and interpretation of the data: Austin, de Avila, Escheik, Gerber, Golabi, Ngo, Price and Weinstein. Drafting of the manuscript: de Avila, Ngo and Weinstein. Critical revision of the paper for intellectual content: Austin, de Avila, Escheik, Gerber, Golabi, Ngo, Price, Weinstein and Younossi. All authors approved the final version of the paper. ## Disclosure statement No potential conflict of interest was reported by the author(s). ## References 1. 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--- title: 'Serum Cystatin C within 24 hours after admission: a potential predictor for acute kidney injury in Chinese patients with community acquired pneumonia' authors: - Dawei Chen - Linglin Jiang - Yan Tan - Jing Zhao - Wenjuan Huang - Binbin Pan - Xin Wan journal: Renal Failure year: 2023 pmcid: PMC10054292 doi: 10.1080/0886022X.2023.2194444 license: CC BY 4.0 --- # Serum Cystatin C within 24 hours after admission: a potential predictor for acute kidney injury in Chinese patients with community acquired pneumonia ## Abstract ### Background Acute kidney injury (AKI) is common in patients with community-acquired pneumonia (CAP), and is associated with poor prognosis. Therefore, in this study, we evaluated whether AKI in Chinese patients with CAP could be well predicted by serum Cystatin C within 24 h after admission. ### Methods Univariate and multivariate logistic regression analyses were used to investigate independent factors of AKI in patients with CAP. ### Results Totally, 2716 patients with CAP were included in this study. 766 ($28\%$) patients developed AKI. After multivariate logistic regression analysis, serum Cystatin C (odds ratio [OR] 4.27, $95\%$ confidence interval [CI] 3.36–5.44; $p \leq 0.001$) was an independent factor for AKI in patients with CAP. Serum Cystatin C had an area under the receiver operating characteristic curve (AUC) of 0.81 for predicting AKI, with an optimal cutoff value of 1.37 mg/L, computing $68\%$ sensitivity, $80\%$ specificity. Furthermore, serum Cystatin C within 24 h after admission still had a good and stable prediction efficiency for AKI in various subgroups (age, gender, hypertension, diabetes, coronary artery disease, cardiac insufficiency, cerebrovascular disease, atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, and tumor, albumin, anemia, platelet count, white blood cell count, and uric acid, confusion, uremia, respiratory rate, blood pressure, and age 65 years or older [CURB-65] score, acute respiratory failure, intensive care unit admission, and mechanical ventilation) of patients with CAP (AUCs: 0.69–0.84). ### Conclusion Serum Cystatin C within 24 h after admission appears to be a good biomarker for predicting AKI in Chinese patients with CAP. ## Introduction Community-acquired pneumonia (CAP) is responsible for substantial mortality, with a third of patients dying within 1 year after being discharged from the hospital for pneumonia [1]. Acute kidney injury (AKI) is a common complication of CAP, with incidence rates from 18 to $34\%$ [2–4]. Moreover, AKI is associated with a poor prognosis in patients with CAP [2,3,5,6]. Lakhmir S. et al. found that patients who were admitted to the hospital for pneumonia and developed AKI had a poor effect on long-term prognosis. They were at high risk for death, dialysis, and permanent loss of renal function [6]. Even among patients diagnosed with non-severe pneumonia, AKI could increase higher long-term mortality risk [3]. Recently, our team also found that patients with CAP who developed AKI had worse short-term prognosis. They were more likely to require admission to an intensive care unit, mechanical ventilation, invasive mechanical ventilation, or noninvasive mechanical ventilation, had higher in-hospital mortality, and experienced a longer duration of hospital stay [5]. Serum creatinine (SCr) is affected by multiple factors, such as muscle mass, dehydration, and dietary protein intake. [ 7], and the increase in SCr during AKI is delayed, which leads to deferred diagnosis [8]. However, unlike SCr, the level of serum Cystatin C is not affected by age, sex, body muscle mass, and diet [9]. A previous study showed that Cystatin C was a good biomarker in the prediction of AKI in other clinical settings [9], as it was not influenced by age, gender, race, muscle mass, and protein intake [10]. However, the evidence regarding the prediction efficiency of Cystatin C for AKI in Chinese patients with CAP is scarce. Therefore, in this study, we evaluated whether AKI in Chinese patients with CAP could be well predicted by serum Cystatin C within 24 h after admission. ## Patient selection This is a case-control study. We reviewed the medical records of 5851 patients, who were ≥18 years of age and admitted to the hospital for CAP at Nanjing First Hospital from January 2014 to May 2017. Exclusion criteria were as follows: patients without serum Cystatin C, patients with less than two repeated SCr, patients with a history of end-stage renal disease or requiring dialysis, and patients lacking complete medical records. Finally, 2716 patients were enrolled in this study. ( Figure 1) **Figure 1.:** *Flowchart for patient selection. CAP: community-acquired pneumonia; AKI: acute kidney injury.* ## Definitions of CAP and AKI Pneumonia is diagnosed based on the detection of interstitial infiltrate changes on chest radiography or CT in patients with one or more of (a) recent presence of dyspnea, cough, or sputum; (b) core body temperature > 38.0 °C; or (c) peripheral white blood cell > counts10 × 109/L or < 4 × 109/L. In addition, illness onset was specifically in the community, rather than in the healthcare setting [11,12]. The definition of AKI in our study adhered to the Kidney Disease Improving Global Outcomes (KDIGO) criteria, which defined AKI as an increase in SCr levels by ≥1.5-fold from baseline within 7 days of illness onset or an increase in SCr levels by ≥0.3 mg/dL (26.4 μmol/L) within 24 h of illness onset [13]. Baseline SCr values were defined as the lowest levels measured during hospitalization. Due to the lack of data concerning urine output, urine output standards were not considered in this study. ## Data collection Demographics (gender and age), comorbid conditions (hypertension, diabetes mellitus, coronary artery disease, cardiac insufficiency, atrial fibrillation, chronic obstructive pulmonary disease [COPD], chronic kidney disease, pulmonary hypertension, cerebrovascular diseases, and tumor), complication (acute respiratory failure [14]), severity scoring on admission (confusion, uremia, respiratory rate, blood pressure, and age 65 years or older [CURB-65]) [15], and laboratory tests (albumin, uric acid, serum Cystatin C, hemoglobin, platelet count, and white blood cell count) within 24 h after admission were collected from the hospital records. ## Data analysis Baseline characteristics were presented as means ± SDs or medians and interquartile ranges for continuous variables if appropriate, and proportions for categorical variables. Students’ t tests or Mann–Whitney tests were used to compare continuous variables between groups. Chi-square tests or Fisher exact were conducted to tell the differences in categorical variables between groups. Univariate and multivariate logistic regression analysis were used to identify independent risk factors of AKI. The prediction performance of all independent factors for AKI was measured using the area under the receiver operating characteristic (ROC) curves (AUCs). We found that the maximum AUC was reported for serum Cystatin C within 24 h after admission. To determine the optimal cutoff value for serum Cystatin C in discriminating AKI, the Youden index was utilized to calculate the cutoff value (Youden index = sensitivity + specificity − 1, ranging from 0 to 1). As a stratification analysis to evaluate the performance of serum Cystatin C within 24 h after admission for predicting AKI in various subgroups, we conducted a multivariate logistic regression analysis to explore whether serum Cystatin C was still an independent predictor for AKI in various subgroups. The various subgroups were classified by age, gender, comorbidities (hypertension, diabetes, coronary artery disease, cardiac insufficiency, cerebrovascular disease, atrial fibrillation, COPD, chronic kidney disease, and tumor), laboratory investigations (albumin, anemia [for male, hemoglobin <120 g/L; for female, hemoglobin <110 g/L] [16], platelet count, white blood cell count, and uric acid), CURB-65 Score, and complication (acute respiratory failure). Stratification analyses adjusted for all the above factors except the stratification factor itself. For the subgroups of intensive care unit (ICU) admission, and mechanical ventilation, stratification analyses adjusted for all the above factors (demographics, comorbid conditions, complications, and laboratory investigations). Furthermore, the prediction performance of serum Cystatin C for AKI was also measured by AUCs in various subgroups. P values < 0.05 were considered as statistically significant. Statistical analysis was using SPSS software version 22 (IBM, Armonk, NY, USA), the EmpowerStats (www.empowerstats.net, X&Y solutions, Inc. Boston MA) and R version 3.6.1 (http://www.r-project.org). ## Patient characteristics Totally, 2716 patients were included in this study. The mean (median, range) age of the patients was 71.6 (75, 63–83) years and most of the study population consisted of males ($60.9\%$). 487 ($17.9\%$) patients complicated with acute respiratory failure. 447 ($16.5\%$) patients required mechanical ventilation, and 597 ($22.0\%$) patients needed admission to ICU. ## AKI characteristics 766 ($28\%$) patients developed AKI. The characteristics of patients with AKI were shown in Table 1. Compared with non-AKI group, male gender ($67.2\%$ versus $58.4\%$; $p \leq 0.001$) and older age (78.2 years versus 69.0 years; $p \leq 0.001$) had significant differences between the two groups. Hypertension, diabetes mellitus, coronary artery disease, cardiac insufficiency, atrial fibrillation, chronic kidney disease, and cerebrovascular diseases were more common in the AKI group. However, no statistically significant comorbidities were in COPD, pulmonary hypertension, and tumor between the two groups. Patients in the AKI group were more commonly complicated with acute respiratory failure ($39.2\%$ versus $9.6\%$; $p \leq 0.001$) and had a higher CURB-65 score than the no-AKI group. In addition, patients with AKI had higher levels of uric acid, serum Cystatin C, and white blood cell count, while they had lower levels of albumin, hemoglobin, and platelet count. **Table 1.** | Variables | All (n = 2716) | Non-AKI (n = 1950) | AKI (n = 766) | p Value | | --- | --- | --- | --- | --- | | Demographics | | | | | | Gender (male), n (%) | 1653 (60.9) | 1138 (58.4) | 515 (67.2) | <0.001 | | Age (years) | 71.6 ± 15.8 | 69.0 ± 16.2 | 78.2 ± 12.3 | <0.001 | | Comorbid conditions, n (%) | | | | | | Hypertension | 1380 (50.8) | 903 (46.3) | 477 (62.3) | <0.001 | | Diabetes mellitus | 553 (20.4) | 346 (17.7) | 207 (27.0) | <0.001 | | Coronary artery disease | 779 (28.7) | 481 (24.7) | 298 (38.9) | <0.001 | | Cardiac insufficiency | 618 (22.8) | 335 (17.2) | 283 (36.9) | <0.001 | | Atrial fibrillation | 317 (11.7) | 182 (9.3) | 135 (17.6) | <0.001 | | COPD | 336 (12.4) | 234 (12.0) | 102 (13.3) | 0.349 | | Chronic kidney disease | 184 (6.8) | 71 (3.6) | 113 (14.8) | <0.001 | | Pulmonary hypertension | 87 (3.2) | 57 (2.9) | 30 (3.9) | 0.186 | | Tumor | 238 (8.8) | 159 (8.2) | 79 (10.3) | 0.073 | | Cerebrovascular diseases | 883 (32.5) | 535 (27.4) | 348 (45.4) | <0.001 | | Complication | | | | | | Acute respiratory failure | 487 (17.9) | 187 (9.6) | 300 (39.2) | <0.001 | | Severity scoring | | | | | | CURB-65 scores | | | | <0.001 | | 0 | 587 (21.6) | 561 (28.8) | 26 (3.4) | | | 1 | 1211 (44.6) | 916 (47.0) | 294 (38.6) | | | 2 | 741 (27.3) | 416 (21.3) | 323 (42.4) | | | ≥3 | 177 (6.5) | 56 (2.9) | 121 (15.8) | | | Laboratory tests | | | | | | Baseline SCr (mmol/L) | 64 (51–82) | 62 (51–78) | 69 (50–103) | <0.001 | | SCr (mmol/L) | 74 (58–98) | 68 (55–83) | 104 (76–151) | <0.001 | | Albumin (g/L) | 33.2 ± 5.3 | 34.2 ± 4.8 | 30.7 ± 5.4 | <0.001 | | Uric acid (umol/L) | 257 (186–360) | 239 (178–314) | 345 (228–477) | <0.001 | | Cystatin C (mg/L) | 1.3 ± 0.7 | 1.1 ± 0.4 | 1.9 ± 0.9 | <0.001 | | Hemoglobin (g/L) | 118.4 ± 21.6 | 121.3 ± 19.5 | 111.0 ± 24.8 | <0.001 | | Platelet count (109/L) | 198 (148–255) | 188 (147–228) | 155 (121–203) | <0.001 | | White blood cell count (109/L) | 7.4 (5.5–10.1) | 6.9 (5.3–9.2) | 8.8 (6.2–12.7) | <0.001 | ## Independent factors for AKI Multivariate logistic regression analysis revealed that serum Cystatin C (odds ratio [OR] 4.27, $95\%$ confidence interval [CI] 3.36–5.44; $p \leq 0.001$), acute respiratory failure (OR 3.96, $95\%$ CI 2.29–3.83; $p \leq 0.001$), albumin (OR 0.91, $95\%$ CI 0.89–0.94; $p \leq 0.001$), uric acid (OR 1.002, $95\%$ CI 1.001–1.003; $p \leq 0.001$), platelet count (OR 0.997, $95\%$ CI 0.996–0.998; $$p \leq 0.001$$), white blood cell count (OR 1.08, $95\%$ CI 1.05–1.10; $p \leq 0.001$), and CURB-65 score were independent factors for AKI in patients with CAP (Table 2). **Table 2.** | Variable | OR | 95% CI | p Value | | --- | --- | --- | --- | | Cystatin C (mg/L) | 4.27 | 3.36–5.44 | <0.001 | | Albumin (g/L) | 0.91 | 0.89–0.94 | <0.001 | | Uric acid (umol/L) | 1.002 | 1.001–1.003 | <0.001 | | Platelet count (109/L) | 0.997 | 0.996–0.998 | 0.001 | | White blood cell count (109/L) | 1.08 | 1.05–1.10 | <0.001 | | CURB-65 scores | | | | | 0 | Reference | | | | 1 | 3.03 | 1.82–5.05 | <0.001 | | 2 | 4.10 | 2.38–7.08 | <0.001 | | ≥3 | 7.14 | 3.74–13.62 | <0.001 | | Acute respiratory failure | 2.96 | 2.29–3.83 | <0.001 | ## Prediction efficiency of serum Cystatin C for AKI in patients with CAP We performed ROC analysis for all independent factors for AKI to determine their prediction performance, respectively. Figure 2 showed the comparisons of AUCs for all independent factors of AKI in patients with CAP. The maximum AUC was reported for serum Cystatin C within 24 h after admission. Table 3 presented the accuracy of serum Cystatin C for detecting AKI in patients with CAP. Serum Cystatin C had an AUC of 0.81 ($95\%$ CI: 0.79–0.83, $p \leq 0.001$) for predicting AKI, with an optimal cutoff value of 1.37 mg/L, computing $68\%$ sensitivity, $80\%$ specificity, $57\%$ positive predictive value and $86\%$ negative predictive value. **Figure 2.:** *Comparisons of AUCs for all independent factors of AKI in patients with CAP. AUC: area under the receiver operating characteristic curve; AKI: acute kidney injury; CAP: community-acquired pneumonia.* TABLE_PLACEHOLDER:Table 3. ## Subgroup analysis In the stratification analyses, serum Cystatin C within 24 h after admission was still an independent predictor in all the various subgroups. Figure 3 showed the ORs, AUCs, cutoff values, sensitivity, and specificity of serum Cystatin C in all the different subgroups. Moreover, serum Cystatin C still had a good performance for predicting AKI in all the subgroups (AUCs: 0.69–0.84). **Figure 3.:** *Prediction efficiency of serum Cystatin C for AKI in various subgroups of patients with CAP. AKI: acute kidney injury; CAP: community-acquired pneumonia.* ## Discussion Previously, serum Cystatin C had been demonstrated to be a biomarker for the early detection AKI in other clinical settings, such as patients with traumatic brain injury, neonates, patients with cardiac surgery, patients with liver, and so on [9,17–20]. To our best knowledge, this present study analyzed the largest number of Chinese patients with CAP to investigate serum Cystatin C within 24 h after admission for predicting AKI, and it indeed proved to be a good predictor of AKI in patients with CAP. In this study, the incidence rate of AKI was $28\%$. Previous studies had demonstrated similar incidence rates of AKI in patients with CAP, ranging from 18 to $34\%$ [2–4]. We found that serum Cystatin C was an important independent factor for predicting AKI in patients with CAP. Cystatin C is a 13 kDa proteinase inhibitor, and it is a member of the cystatin superfamily of cysteine protease inhibitors, which play an important role in intra-cellular catabolism of proteins and peptides [21]. It is synthesized and released into plasma by all nucleated cells at a constant rate [22]. Cystatin C can be more than $99\%$ freely filtered through glomeruli and does not show significant protein binding. It is considered to be neither actively secreted into the tubular lumen nor reabsorbed into the plasma. After filtration, it is normally completely reabsorbed by proximal renal tubular epithelial cells, and catabolized by megalin receptor-induced endocytosis [23]. In addition, unlike SCr, the level of serum Cystatin C is not affected by age, sex, body muscle mass, and diet [9]. Therefore, serum Cystatin C is considered a good biomarker for the early detection of AKI. In our study, AUC of serum Cystatin C level to predict AKI was 0.81 ($95\%$ CI, 0.79–0.83), with an optimal cutoff value of 1.37 mg/L, computing $68\%$ sensitivity, $80\%$ specificity, $57\%$ positive predictive value and $86\%$ negative predictive value. Recently, Cigdem et al. conducted a single-centre, retrospective, observational cohort study with 348 hospitalized COVID-19 patients, and found that serum Cystatin C showed a good predictive power for AKI in patients with COVID-19. The AUC value of serum Cystatin C to predict COVID-19-related AKI was 0.96 (0.90 to 1.0), with the best cutoff value of 1.00 mg/L [24]. Albina et al. prospectively enrolled 341 patients presenting to the emergency department with CAP, and investigated the potential of plasma N-terminal prohormone B-type natriuretic peptide (NT-proBNP), mid-regional pro-atrial natriuretic peptide (MR-proANP) and B-type natriuretic peptide (BNP) levels within the first 48 h to predict early AKI in hospitalized patients with CAP. They found that the AUCs for the prediction of AKI of NT-proBNP, MR-proANP and BNP were 0.79, 0.79, and 0.74, respectively [25]. In this study, we also found that albumin, uric acid, platelet count, white blood cell count, CURB-65 score, and acute respiratory failure were independent factors for AKI in patients with CAP. CURB-65 [15] and the pneumonia severity index (PSI) [26] were two scoring systems that assessed the severity of CAP. Ahsan et al. reported that PSI was an important factor in predicting AKI in patients with CAP [2]. In our study, we found CURB-65 was also an independent risk factor to develop AKI in patients with CAP. Low albumin levels had been reported that it was a modifiable risk factor linked to increased risk of AKI in different clinical settings [27]. Recently, a study found that hypoalbuminemia was independently associated with the occurrence of AKI in COVID-19 patients with acute respiratory distress syndrome [28]. Albumin could improve renal perfusion and glomerular filtration by inhibiting apoptosis in renal tubular cells by carrying protective lysophosphatidic acid and scavenging reactive oxygen species [29]. Albumin could prolong potent renal vasodilation, which was induced by serum albumin reacting with the oxides of nitrogen to form S-nitroso-albumin [30]. In addition, several studies suggested that exogenous albumin administration was beneficial to protect the kidneys from AKI [31,32]. Hyperuricemia was associated with AKI in various statuses [33]. A recent report showed that serum uric acid was an independent predictor of AKI in patients with COVID-19 [34]. Platelet count and white blood cell count were two biomarkers for AKI, and a low level of platelet count and a high level of white blood cell count could increase the risk of AKI [35–38], which was consistent with our findings. The present study had several strengths. First, to our best knowledge, this study may first report that serum Cystatin C within 24 h after admission could well predict AKI in patients with CAP. Second, stratified analyses made the use of data better. In subgroup analysis, serum Cystatin C within 24 h after admission still had a good prediction efficiency in different subgroups (AUCs: 0.69–0.84). Third, interestingly, serum Cystatin C had slightly better prediction performance for AKI in the subgroups of the non-elderly, female, and patients without the serious condition. We acknowledge several limitations. First, it is a retrospective single-center study, and the conclusion will need to be confirmed by a multicenter prospective study with a larger patient cohort. Second, AKI is defined according to the KDIGO criteria, based on SCr and urine output [13]. However, the urine output data could not be obtained. Therefore, our analysis lacks the urine output standard for AKI. Third, *Staphylococcus infections* have increased the risk of AKI and are associated with mortality [39]. However, most of the patients in this study lack this data. Forth, we exclude the patients without sufficient SCr in the present study, and the potential selection bias might have also limited the generalizability of the study. In summary, AKI is common in patients with CAP. 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--- title: Dietary Fats and Cognitive Status in Italian Middle-Old Adults authors: - Walter Currenti - Justyna Godos - Amer M. Alanazi - Giuseppe Lanza - Raffaele Ferri - Filippo Caraci - Giuseppe Grosso - Fabio Galvano - Sabrina Castellano journal: Nutrients year: 2023 pmcid: PMC10054310 doi: 10.3390/nu15061429 license: CC BY 4.0 --- # Dietary Fats and Cognitive Status in Italian Middle-Old Adults ## Abstract The increase in life expectancy led to a significant rise in the prevalence of age-related neurological diseases, such as cognitive impairment, dementia, and Alzheimer’s disease. *Although* genetics certainly play a role, nutrition emerged as a key factor in maintaining optimal cognitive function among older adults. Therefore, the study aimed to investigate whether specific categories and subcategories of dietary fats, based on carbon-chain length, are associated with cognitive status in a cohort of 883 Italian participants over the age of 50. Methods: The intake of total, single class of dietary fat, such as saturated fatty acids (SFA), monounsaturated fatty acid (MUFA), and polyunsaturated fatty acid (PUFA), and also single fatty acids grouped according to carbon-chain length, were evaluated by food frequency questionnaires (FFQs). Cognitive health was assessed using the short portable mental status questionnaire (SPMSQ). Results: After adjustment for potential confounding factors subjects with a moderate consumption of both short-chain SFA (for Q2 vs. Q1, OR = 0.23, $95\%$ CI: 0.08, 0.66) and middle-chain SFA specifically lauric acid (C12:0) intake (for Q2 vs. Q1, OR = 0.27, $95\%$ CI: 0.09, 0.77) were less likely to suffer from cognitive impairment. Among single MUFAs, erucic acid (C22:1) intake resulted in an inverse association, in a linear way, with cognitive impairment (for Q4 vs. Q1, OR = 0.04, $95\%$ CI: 0.00, 0.39). Conversely, moderate intake of linoleic acid (C18:2) was associated with cognitive impairment (Q3 vs. Q1, OR = 4.59, $95\%$ CI: 1.51, 13.94). Regarding other PUFAs, individuals consuming moderate intake alpha linolenic acid (C18:3) were less likely to have cognitive impairment (for Q3 vs. Q1, OR = 0.19, $95\%$ CI: 0.06, 0.64). Conclusions: Total SFA intake appeared to be inversely associated with cognitive impairment. Regarding specific subtypes of fatty acids, the results mostly referred to short- and middle-chain SFA. Further studies are needed to validate the results of the present study. ## 1. Introduction The important rise in life expectancy strongly increased the impact of neurodegenerative diseases related to aging. It is estimated that there are more than 55 million people affected by dementia [1], with 150 million cases predicted by 2050 worldwide [2]. These are alarming figures considering that a non-specifical global decline in cognition was found in approximately 25–$50\%$ of the community-dwelling older adults [3]. Progressive loss in memory, difficulties in orientation, reduction in comprehension and judgment are typical features of cognitive decline [4] and usually evolve into pathological diagnosis [5]. To date, despite pharmacological progress, there are no successful therapies to cure cognitive impairment [6]; thus, it is important to understand how to prevent or delay cognitive deterioration. Despite the fact that the onset of cognitive impairment is multifactorial and significantly genetically determined, modifiable risk factors such as lifestyle and nutrition [7,8], including the Western diet characterized by high intake of trans and saturated fatty acids, refined sugars, salt, and ultra-processed foods, were linked to an increased risk of dementia [9]. Conversely, adherence to a plant-based diet such as the Mediterranean diet, rich in unsaturated fats, fibers, and polyphenols, was associated with a lower risk of age-related cognitive decline [10,11]. Regarding single vitamins, observational studies showed an inverse association between higher vitamin C, pyridoxine (B6), folic acid (B9), cobalamin (B12) intakes and cognitive decline [12], probably also affecting the homocysteine metabolism that is, in turn, linked to cognitive impairment and cardiovascular risk [13]. Considering that metabolic syndrome and hyperinsulinemia are associated with worse cognition [14], it is also important to lower insulin and caloric intake; this justifies the interesting suggestion regarding the potential beneficial effects of a ketogenic diet [15] and intermittent fasting on cognitive impairment [16]. Additionally, a vitamin D deficiency may increase the risk of dementia and reduce cognitive performance [17]. Regarding macronutrients intake, dietary fats, and especially saturated fatty acids (SFA), were incriminated for being the main nutritional determinant for cognitive impairment in older adults [18]. On the other hand, both monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) may have positive effects toward cognition acting directly on neuronal membrane [19] to the point that their isocaloric substitution to SFAs is usually considered to provide global health benefits [20]. However, recent data showed possible beneficial effects of SFAs on mental health [21,22] due to the different length of the carbon chain that, in turn, determines differential absorption and metabolic effects [23]. Short chain fatty acids are produced by gut microbiota through fermentation of dietary fiber or directly ingested from dairy foods. Interestingly, SCSFAs seem to have several positive effects toward mental health reducing neuroinflammation, regulating the HPA axis and increasing the production of neurotransmitters [22,24]. The study objective was to examine the potential association between cognitive status and specific categories and subcategories of dietary fats based on carbon-chain length in a cohort of middle-aged subjects residing in southern Italy. ## 2.1. Study Population The MEAL study was a cross-sectional investigation that sought to explore the link between dietary and lifestyle habits of the Mediterranean region and non-communicable diseases (NCDs). The study cohort included 2044 male and female adults who were randomly selected from the major districts of Catania, a city in southern Italy, between 2014 and 2015 (Supplementary Figure S1). Deepening and details about the study protocol were reported elsewhere [25]. Considering that the investigated outcome had a major relevance in the elderly, the analysis was restricted only on participants of 50 years old or older ($$n = 916$$). Written consent was obtained only after informing everyone about the purposes of the study. The study protocol was approved and reviewed by the relevant ethical committee, and all procedures were conducted in accordance with the World Medical Association’s Declaration of Helsinki [1989]. ## 2.2. Data Collection An expert operator conducted individual-assisted interviews to collect data, which were electronically recorded using tablets. The socio-demographic data collected included age at recruitment, gender, and highest educational degree attained, with educational level classified as (i) low (primary/secondary), (ii) medium (high school), or (iii) high (university). Physical activity was assessed using the international physical activity questionnaire (IPAQ), which comprised five domains that enabled classification of participants into (i) low, (ii) moderate, or (iii) high physical activity categories [26]. Participants were categorized as (i) non-smokers, (ii) ex-smokers, or (iii) current smokers. Lastly, individuals were grouped according to body mass index (BMI) cut-offs, with under/normal weight defined as a BMI < 25 kg/m2, overweight as BMI between 25 and 29.9 kg/m2, and obese as a BMI ≥ 30 kg/m2 [27]. ## 2.3. Dietary Assessment Two food frequency questionnaires (FFQs; a short and a long version) were previously validated in a sample of 178 Sicilian adults living in Sicily, south Italy [28,29]. FFQs contained a total of 110 food items consumed in the last 6 months. The determination of the food ingested, calories introduced, and, in particular, micro- and macro-nutrient intake was calculated using food composition tables of the Research Center for Foods and Nutrition. The reported frequency of consumption in standard portions sizes from FFQs allowed us to obtain, in milliliter or grams, the mean daily consumption of each food. From these data, the total amount of specific fatty acids, taking the values of nutritional food composition tables as reference, was calculated. Adherence to the Mediterranean diet was evaluated through a literature-based score system that assigned positive points for typical foods belonging to Mediterranean habits as legumes, fruits, olive oil, fish, and vegetables, while negative points were assigned for dairy products, meat, and ultra-refined foods. The system contained nine food groups and the score ranged from 0 points (low adherence) to 18 points (high adherence), in order to allow the classification of individuals in tertiles (low, medium, or high adherence to the Mediterranean diet) [30]. After excluding incomplete or unrealistic FFQs (<1000 or >6000 kcal/d), a total of 883 individuals were finally analyzed. ## 2.4. Cognitive Evaluation The short portable mental status questionnaire (SPMSQ) [31] was used to evaluate cognition in both general and hospitalized populations. This 10-item tool, administered by clinicians in either an office or hospital setting [32], assessed the level of cognitive decline. The tool was helpful for interpreting results, as it provided predetermined classes based on the number of errors: intact (less than 3 errors), mild (3 to 4 errors), moderate (5 to 7 errors), and severe (8 or more errors). In this study, cognitive impairment was defined as more than 2 errors. ## 2.5. Statistical Analysis Continuous variables were described by means and standard deviations (SDs), while categorical variables were presented as frequencies and percentages. Participants were divided into quartiles based on their total fat intake, and socio-demographic data were compared between groups. Differences in variables were analyzed using the chi-squared test for categorical variables, ANOVA for normally distributed continuous variables, and the Kruskall–Wallis test for non-normally distributed variables. To examine the association between dietary fat intake and cognitive health, energy-adjusted and multivariate logistic regression models were employed. The multivariate model was adjusted for age, sex, BMI, physical activity, educational status, smoking status, and adherence to the Mediterranean diet as an indicator of diet quality, to determine whether the observed associations were independent of these variables. All p-values were reported as two-sided and compared to a significance level of $5\%$. Statistical calculations were performed using SPSS 17 software (SPSS Inc., Chicago, IL, USA). ## 3. Results A total of 883 participants were finally analyzed. Table 1 showed socio demographic data of the cohort, distributed by quartiles of total dietary fat intake. First, individuals consuming more total fats were younger. A significant difference in the distribution of smoking status and adherence to the Mediterranean diet were found. In particular, in the fourth quartile, there were more former smokers and individuals with moderate adherence to the Mediterranean diet, compared to the lower quartiles. Similar significant differences were found in the distributions of sex and physical activity levels, but without a linear trend. No significant differences between quartiles of dietary fat consumption were observed when considering the educational level and BMI categories. Table 2 showed the association between total and classes of dietary fats and cognitive status. A multivariate-adjusted analysis revealed a significant inverse association between SFAs and cognitive status in a linear way (for Q4 vs. Q1, odds ratio (OR) = 0.27, $95\%$ CI: 0.09, 0.87). No associations were found between intake of total fats, total MUFAs and PUFAs, and cognitive status. Table 3 shows the association between specific sub-classes of fats and cognitive status. Interestingly, participants with a moderate consumption of both short-chain saturated fatty acids (SCSFA) (for Q2 vs. Q1, OR = 0.23, $95\%$ CI: 0.08, 0.66) and medium-chain saturated fatty acids (MCSFA), specifically C12:0 (for Q2 vs. Q1, OR = 0.27, $95\%$ CI: 0.09, 0.77), were less likely to have a cognitive impairment. Among single MUFAs, C22:1 intake resulted in an inverse association with cognitive status (Q4 vs. Q1, OR = 0.04, $95\%$ CI: 0.00, 0.39). Conversely, moderate intake of C18:2 was associated with higher odds of having impaired cognition (for Q3 vs. Q1, OR = 4.59, $95\%$ CI: 1.51, 13.94). Regarding other PUFAs, only participants with moderate intake C18:3 were less likely to have a cognitive impairment (for Q3 vs. Q1, OR = 0.19, $95\%$ CI: 0.06, 0.64). No associations were found for other investigated fatty acids and cognitive status. Table 4 showed the association between individual food sources of fats and cognitive status. Most of the food groups were not associated with the outcome of interest with exception for higher consumption of yogurt (for Q3 vs. Q1, OR = 0.39, $95\%$ CI: 0.19, 0.79) and low intake of sweets and snacks (for Q2 vs. Q1, OR = 0.30, $95\%$ CI: 0.12, 0.71). ## 4. Discussion In this study, we assessed the possible association relationship between dietary subtype fat intake and cognitive status in a sample of middle-old participants living in a Mediterranean area. Although SFAs have always been considered detrimental toward cognitive health, in our study, after multivariate analysis, higher total SFA intake was associated with lower cognitive impairment. In fact, previous research on rodents showed that a high SFAs diet may affect the hippocampus and prefrontal cortex morphology [33], mainly through a reduced branching and spine density with a consequence on memory loss [34]. Moreover, it appeared that higher SFAs levels increase the concentrations of the protein amyloid beta [35] with a compromission of the blood–brain barrier [36]. Human research was mainly in line with data found in animal models; cross-sectional and longitudinal studies showed that a diet rich in SFAs worsened different cognitive functions; for example, visuospatial learning [37] and prospective and verbal memory performance [38]. Another possible mechanism that links SFAs to cognitive decline may be the rise in cholesterolemia associated with their consumption; in fact, high levels of blood cholesterol play a detrimental role in amyloid beta production and deposition [39]. This hypothesis lost its strength due to new data, showing that SFAs are not the main determinant of LDL cholesterol and cardiovascular risk [21,40], especially in individuals without the APOE ε4 allele that favors the accumulation of intracellular cholesterol [41]. A recent meta-analysis of prospective cohort studies showed higher SFA intake was associated with increased odds of suffering from a cognitive impairment; however, the authors concluded that the results should be interpreted with caution due to the great heterogeneity in the sample size, with regard to the considered cognitive outcomes and dietary subtype of fat [42]. A cohort study with younger participants (average age of 55 years) failed to find a detrimental relationship between high SFAs intake and cognitive decline [43]. Two other cohort studies conducted on older women [44] and women at high vascular risk [45] also showed the absence of detrimental association between SFAs and cognitive decline, leaving the debate open. A possible reason for these disputable results may be due to different subtypes of SFAs mainly ingested from the diet according to the length of their carbon chain that affect their absorption and metabolism [23]. Interestingly, in our cohort, we found that individuals with a higher intake of SCSFA and MCSFA, especially lauric acid (C:12), were less likely to have cognitive impairment. SCSFA may influence cognition firstly regulating the gut-brain-axis. SCFAs were shown to improve gut barrier function, promoting bacterial promoting bacterial diversity [46] and increasing expression of tight junction proteins, which regulate the permeability toward molecules as LPS that may be harmful if pass into the bloodstream [47,48]. SCSFAs activate many types of neurons in the enteric nervous system modulating neurotransmitter release such as serotonin, gamma-aminobutyric acid (GABA), and acetylcholine, which have all been implicated in the regulation of mood and behavior [49]. A recent study showed that supplementation with a mixture of SCFAs increased microbiota diversification and improved cognition and stress in healthy human participants [50]. SCFAs can also influence the production of brain-derived neurotrophic factor (BDNF), a neurotrophin that is involved in neuronal growth and plasticity [51]. In animal models, butyrate directly affects the expression of BDNF in the prefrontal cortex thus improving spatial learning and working memory [52]. Secondarily SCSFAs may influence cognition reducing neuroinflammation binding to G-protein-coupled receptor 43 (GPR43) inhibiting NF-κB signaling [53] and to transform macrophage into anti-inflammatory M2-type [54]. In addition, they have an impact on neuroinflammation by regulating microglia activation, leading to a decrease in the levels of pro-inflammatory cytokines [55]. SCFAs can also protect against oxidative stress that recognized to be a risk factor for mental diseases [56], modulating the activity of nuclear factor erythroid 2-related factor 2 (Nrf2) and the synthesis of antioxidant enzymes such as catalase and superoxide dismutase (SOD) [57]. Finally, SCSFAs may have also effect on mental health through epigenetic regulation; they can inhibit histone deacetylases (HDACs) that in turn leads to increased acetylation of histones and thus changes in gene expression involved in inflammation, synaptic plasticity, and stress response, which are all implicated in the development of mental health disorders [58,59]. A proof that carbon length matter is that long chain saturated fatty acids (LCSFA) as palmitate was found to stimulate inflammation in macrophages and affect microglial and astrocytic signaling pathways [60,61]. Also, MSCSFA as lauric acid may have beneficial effects on cognition reducing the inflammation induced by LPS in microglia [62] and regulating the production of cytokines and neurotrophic factors [63]. In our cohort, a large part of dietary SCSFA-MCSFAs derive from the consumption of dairy products such as yogurt. Interestingly, individuals consuming yogurt have lower odds to manifest cognitive impairment as previously reported in a community-dwelling older adults cohort of the Canadian Longitudinal Study [64]. Regarding MUFAs, only the consumption of erucic acid (C22:1) was inversely associated with cognitive impairment in a linear way in our study. Erucic acid is an omega 9 fatty acid derived from vegetable oils that was previously considered toxic from animal research, however new studies on humans reveal that it may enhance cognitive function especially memory [65] interacting with peroxisome proliferator-activated receptors (PPARs), and inhibit elastase and thrombin, thereby modulating neuroinflammation and reducing the levels of pro-inflammatory cytokines [66]. Among PUFAs subcategories, we showed an inverse association between alpha linolenic acid (ALA, C18:3) and cognitive impairment while the contrary was found for linoleic acid (LA, C18:2) intake. These results are in line with a recent meta-analysis that reported a beneficial effect of PUFAs especially n-3 on cognitive impairment, dementia and also Alzheimer’s disease [42]. n-3 PUFAs as ALA, which is precursor of DHA and EPA, and was shown to ameliorate learning, semantic [67], spatial [68] and short-term memory [69] in older adults thus preventing cognitive decline [70]. From a mechanistic point of view n-3 PUFAs may affect cognitive health directly increasing membrane fluidity [71], regulating serotonin levels from presynaptic neurons [72] increasing TGF-β1 production [73], and reducing cerebral glutamate [74] which may be neurotoxic [75]. Moreover n-3 PUFAs may act indirectly improving insulin [76], that is a key hormone linked to oxidative stress and neuroinflammation [77]. On the other hand, in line with our results, previous literature showed a possible detrimental role of n-6 PUFAs as LA toward cognitive health. Preclinical studies reported that high intake of LA may induce inflammation into the nervous system through the production of oxidized metabolites [78]. A 12-week dietary trial consists of reducing LA intake from $7\%$ to $2\%$ adding 1.5 g of DHA and EPA, reduced migraine occurrence and ameliorated quality of life in chronic headache patients [79]. Moreover, a lower n-6/n-3 ratio predicts better hippocampus-dependent spatial memory and cognition in older adults [68]. Despite this evidence, the role of LA in cognition remains to be investigated considering that the function of its oxidized metabolites is not yet fully understood and that it has low concentration in the brain [80]. Albeit this is the first study in the literature to examine the role of each fat subcategory on cognition, the results may have some limitations. First, it is not possible to determine causal relationship between variables but only association due to the epidemiological study design. Although a multivariate-adjusted logistic regression analysis was done, any additional confounding factors may not have been considered. Another limitation of the study may be related to the use of FFQ for the assessment of dietary intake; in fact, although they are the most widely used tools in epidemiological studies, it is well known that they may potentially over or under-estimate dietary intake due to portion size miscalculation or recall bias. Finally, the evaluation of cognitive health should be carried out in a clinical setting in which a battery of neuropsychological tests can be used rather than just one. Despite it all, SPMSQ is widely used in epidemiological studies and best perform as a screening tool of cognitive decline. ## References 1. Li X., Feng X., Sun X., Hou N., Han F., Liu Y.. **Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990–2019**. *Front. Aging Neurosci.* (2022) **14** 937486. 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--- title: Essential Oil Nanoemulsion Hydrogel with Anti-Biofilm Activity for the Treatment of Infected Wounds authors: - Kun Cai - Yang Liu - Yan Yue - Yuancheng Liu - Fengbiao Guo journal: Polymers year: 2023 pmcid: PMC10054311 doi: 10.3390/polym15061376 license: CC BY 4.0 --- # Essential Oil Nanoemulsion Hydrogel with Anti-Biofilm Activity for the Treatment of Infected Wounds ## Abstract The formation of a bacterial biofilm on an infected wound can impede drug penetration and greatly thwart the healing process. Thus, it is essential to develop a wound dressing that can inhibit the growth of and remove biofilms, facilitating the healing of infected wounds. In this study, optimized eucalyptus essential oil nanoemulsions (EEO NEs) were prepared from eucalyptus essential oil, Tween 80, anhydrous ethanol, and water. Afterward, they were combined with a hydrogel matrix physically cross-linked with Carbomer 940 (CBM) and carboxymethyl chitosan (CMC) to prepare eucalyptus essential oil nanoemulsion hydrogels (CBM/CMC/EEO NE). The physical-chemical properties, in vitro bacterial inhibition, and biocompatibility of EEO NE and CBM/CMC/EEO NE were extensively investigated and the infected wound models were proposed to validate the in vivo therapeutic efficacy of CBM/CMC/EEO NE. The results showed that the average particle size of EEO NE was 15.34 ± 3.77 nm with PDI ˂ 0.2, the minimum inhibitory concentration (MIC) of EEO NE was 15 mg/mL, and the minimum bactericidal concentration (MBC) against S. aureus was 25 mg/mL. The inhibition and clearance of EEO NE against S. aureus biofilm at 2×MIC concentrations were 77.530 ± $7.292\%$ and 60.700 ± $3.341\%$, respectively, demonstrating high anti-biofilm activity in vitro. CBM/CMC/EEO NE exhibited good rheology, water retention, porosity, water vapor permeability, and biocompatibility, meeting the requirements for trauma dressings. In vivo experiments revealed that CBM/CMC/EEO NE effectively promoted wound healing, reduced the bacterial load of wounds, and accelerated the recovery of epidermal and dermal tissue cells. Moreover, CBM/CMC/EEO NE significantly down-regulated the expression of two inflammatory factors, IL-6 and TNF-α, and up-regulated three growth-promoting factors, TGF-β1, VEGF, and EGF. Thus, the CBM/CMC/EEO NE hydrogel effectively treated wounds infected with S. aureus, enhancing the healing process. It is expected to be a new clinical alternative for healing infected wounds in the future. ## 1. Introduction Wound infection represents a severe complication of skin injuries and is usually formed when pathogenic bacteria, such as S. aureus, attach to a wound and multiply on it [1,2]. Wound infection can impede the normal healing process, greatly prolonging healing time. Lacking effective treatment measures, wound infection can be lethal for patients [3]. It has been previously shown that biofilms are present in over $80\%$ of infected wounds [4,5,6]. Biofilms act as a physical barrier and prevent the penetration of immune cells and therapeutic agents. This physical barrier can make wound healing more difficult, increase the consumption of medical resources, and intensify the suffering experience of patients [7,8,9]. Antibiotic treatment is still one of the most common methods for treating infected wounds in clinical practice. However, bacteria wrapped in biofilms are about 1000 times more antibiotic-resistant than planktonic bacteria, diminishing the overall effects of antimicrobials and challenging their widespread use for treating infectious wounds [10]. Moreover, the overuse of antimicrobials can lead to severe cytotoxicity and bacterial resistance, making treating infected wounds even more difficult and creating a vicious circle [9,11]. It is, therefore, essential to develop a wound dressing that effectively inhibits biofilm formation and growth to treat bacterially infected wounds. Researchers have developed different types of antimicrobial agents for treating infections of traumatic surfaces against bacteria and biofilms. Commonly used antimicrobial agents are classified into three categories based on the type of materials used: inorganic, biological, and organic antimicrobial agents [12]. Inorganic antimicrobial agents can be divided into two categories: metal-based and carbon-based. Typical materials include silver nanoparticles, titanium dioxide nanoparticles, graphene, etc. However, the use of these inorganic antimicrobial agent materials is accompanied by high manufacturing costs, short and insufficient antimicrobial capacity, and an unknown impact on human health and the environment [12,13,14,15,16,17,18]. Biological antibacterial agents, such as enzymes, peptides, and bacteriophages, originate from living organisms. Compared to inorganic antibacterial agents, biological antibacterial agents can be combined with different substrates using various surface modification reactions and intermolecular interactions. So, biological antibacterial agents have a wider range of applications. However, the use of biological antibacterial agents is expensive and limited by the longevity of their biological sources and environmental factors [12,19,20,21]. Organic antibacterial agents can be divided into synthetic and naturally derived materials. Synthetic organic antibacterial agents include common organic antimicrobials, such as penicillin and amoxicillin, which are widely used but prone to developing resistance in pathogenic bacteria [11,12,22]. Among naturally derived organic antimicrobial agents, essential oils have gained widespread interest due to their low toxicity, broad-spectrum antibacterial activity, multiple pharmacological activities, and relatively low cost [23,24,25]. Our laboratory has screened an essential oil extracted from the eucalyptus tree—eucalyptus essential oil (EEO)—by screening the antibacterial activity in vitro in the early stage. The essential oil showed a strong in vitro inhibitory effect on S. aureus. However, the volatile and slightly pungent smell of essential oil affects its long-term antibacterial performance, limiting its further application and development [26]. Therefore, researchers have developed different carrier systems to load and deliver essential oils, including biopolymers, surfactants, and lotions [27,28]. Among them, nanoemulsions represent a lotion-based carrier system that has attracted increasing attention because they can effectively enhance the physical stability and antibacterial activity of essential oils [29]. The preparation process of nanoemulsions is simpler than that of other carrier systems and the cost is relatively low. In addition, the composition of nanoemulsions can be tailored using a wide range of sources and is not limited to the synthesis of surfactants [30,31,32,33,34,35]. Therefore, EEO can be encapsulated in a nanoemulsion to enhance its stability and antibacterial activity. To address the recovery of infected wounds more effectively, researchers usually combine antibacterial agents with various matrix materials to prepare wound dressings with different properties. Common matrix materials mainly include hydrogels, nanofibers, films, and nanomaterials. Among these, hydrogels are a popular choice for wound dressing due to their biocompatibility, flexibility, and high-water content [36,37]. S. A. Razack et al. [ 38] prepared a trauma dressing by combining an oregano essential oil nanoemulsion with a hydrogel matrix prepared from chitosan and gelatin. The dressing exhibited good antibacterial properties and effectively promoted wound recovery. In addition, nanoparticle-loaded hydrogels have a wide range of other applications in the biomedical field. They can be used as a reaction platform for qPCR [39], or as a method for continuous, extreme lubrication of hydrogels in applications ranging from tissue engineering to clinical diagnostics [40]. They can also be used as drug carriers for the treatment of bone infections caused by bacteria [41]. Our laboratory has developed a hydrogel based on the physical cross-linking of carboxymethyl chitosan (CMC) and Carbomer 940 (CBM). It exhibits good water retention and water vapor permeability properties, and provides a stable, moist, and breathable environment for wounds as required, according to the theory of moist wound healing. Moreover, this hydrogel can also be used as a matrix material combined with various active substances to meet different wound repair requirements [26]. In this study, EEO was encapsulated in a nanoemulsion carrier and creatively compounded with a CBM/CMC matrix. A trauma dressing with essential oil nanoemulsions (EEO NEs) as an antimicrobial agent was developed for the treatment of infected wounds. The physicochemical properties, in vitro antibacterial and antibiofilm activity, biocompatibility, and in vivo repair capacity of EEO NEs and hydrogels were examined to evaluate their potential in the treatment of infected wounds and to provide an idea for further research of new materials for the treatment of infected wounds. ## 2.1. Materials Eucalyptus essential oil was purchased from ZRZR biotechnology Co. (Guangzhou, China). carboxymethyl chitosan (carboxylation degrees ≥ $80\%$) and Carbomer 940 (CAS. NO. 54182-57-9) were supplied by Yuanye biotechnology Co. (Shanghai, China). Triethanolamine (CP, ≥$99.0\%$) was procured from Aladdin Reagent Co. (Shanghai, China). Tween 80 (Oleic acid approx$.70\%$), Luria-Bertani (LB) Broth, a CCK-8 detection kit, and an ELISA kit were supplied by Solarbio (Beijing, China). Chloral hydrate was obtained from Macklin Biochemical Co. (Shanghai, China). All other reagents used were of analytical grade (AR, ≥$99.7\%$). ## 2.2. Preparation of EEO NEs and EEO NE Hydrogels Nanoemulsions were prepared via low-energy emulsification [42] using EEO, Tween 80, anhydrous ethanol, and water as raw materials. Tween 80 was the surfactant, and anhydrous ethanol was the co-surfactant, and they were used in a 2:1 mass ratio to prepare the surfactant mix. A total of 3 g of EEO was added to 7 g of the surfactant blend and stirred, followed by the dropwise addition of 25 mL of deionized water using a burette to obtain a nanoemulsion master batch. Deionized water was dropwise added to the nanoemulsion master batch until the total nanoemulsion system reached 100 g. Then, the eucalyptus essential oil nanoemulsion with an essential oil content of $3\%$ (g/g) was prepared. Preparation of hydrogel was conducted with reference to Wang’s method [26]. A total of 0.5 g of CBM was dissolved in 50 mL of deionized water and left to swell overnight at room temperature. 5 mL of a $10\%$ CMC solution was added and stirred well; then, triethanolamine was added dropwise to adjust the pH to neutral. At this point, a blank hydrogel—CBM/CMC was obtained when water was added to the total system up to a mass of 100 g and stirred well; when the nanoemulsion master batch prepared above was added and then deionized, water was poured to a total gel mass of 100 g, so the eucalyptus essential oil nanoemulsion hydrogels (CBM/CMC/EEO NE) was obtained. ## 2.3.1. Basic Properties and the Particle Size Distribution of EEO NE The basic criteria for characterizing EEO NEs were determined by pure optical observation: 1. Is the emulsion clear and transparent? 2. Does the emulsion exhibit a blue or light blue opalescence? 3. Is there a Tyndall effect when parallel light is applied? The pH of the EEO NE was determined using a pH meter. The water-soluble dye methylene blue and the oil-soluble dye Sudan red III were added dropwise to the emulsion at the same time, and the type of emulsion was determined by the rate of diffusion of the two dyes in the emulsion. The properties of nanoemulsions were determined with reference to the method of Hou et al. [ 33]. The prepared EEO NE was diluted 50 times with distilled water to prepare the sample for testing, and the particle size, particle size distribution, and polydispersity index were determined using a nanoparticle size analyzer (ZETASIZER NANO ZS9 Malvern, Malvern, UK). ## 2.3.2. Rheological Measurements of CBM/CMC/EEO NE The rheological properties of the hydrogels were determined with reference to the method of Wang et al. [ 26]. In this experiment, a TA-AR2000ex rheometer was used to measure the energy storage modulus (G’) and loss modulus (G’’) of CBM/CMC and CBM/CMC/EEO NE composite hydrogel samples using dynamic frequency scanning ($0.01\%$ strain). These two parameters reflect the elasticity and viscosity of the object, respectively. The measurements were performed at 25 °C and in the scanning range of 0.1–10 Hz. ## 2.3.3. Water Loss Rate of CBM/CMC/EEO NE The assay was performed with reference to the method of Wang et al. [ 26]. All samples were measured in triplicate. A total of 1 g of each CBM/CMC and CBM/CMC/EEO NE composite hydrogel sample was weighed in 2 mL EP tubes, and their initial mass was accurately determined (M0). The hydrogel samples were then placed in a silica gel desiccator for 36 h at 37 °C and weighed accurately at regular intervals (Ma). The final mass was measured after 36 h (Mb). The water loss rate (%) was calculated using Equation [1]:Water loss rate (%) = (Ma − M0)/(M0 − Mb) × $100\%$.[1] ## 2.3.4. Porosity of CBM/CMC/EEO NE An assay was performed with reference to the method of Lin et al. [ 43]. All samples were measured in triplicate. Appropriate amounts of CBM/CMC and CBM/CMC/EEO NE lyophilized samples were measured and denoted as M0. Furthermore, we measured their volume, denoted as V0. The samples were soaked in 50 mL of ethanol, and the mass of an empty bottle (M1) was measured before being put in a sonicator to remove air bubbles for 2 min so that the liquid filled the pores of the gel. Next, we pour out the excess ethanol and measure the total mass (M) of the remaining substance. The experiment was repeated three times in parallel to calculate the porosity using Equation [2], where the ethanol density was 0.789 g/cm3:Porosity (%) = (M − M1 − M0)/0.789/V0 × $100\%$.[2] ## 2.3.5. Water Vapor Transmission Rate (WVTR) Test for CBM/CMC/EEO NE An assay was performed with reference to the method of Wang et al. [ 26]. All samples were measured in triplicate. A glass vial 18 mm in diameter was filled with 10 mL of deionized water, and the mouth of the vial was covered with a layer of gauze. A total of 0.5 g of the measured CBM/CMC and CBM/CMC/EEO NE composite hydrogels was weighed and evenly covered with gauze, and the mouth of the vial was sealed. Their initial mass was accurately weighed (M0). The hydrogel-covered bottles were placed in a silica gel desiccator and removed at 37 °C for 12, 24, 36, and 48 h to accurately measure their mass (Ma). The WVTR (mg/m2/day) was calculated as follows [3]:WVTR (mg/m2/day) = (M0 − Ma)/106 A × T,[3] where A is the area of the bottle opening and T is the number of days. ## 2.4.1. Determination of the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of EEO NE The MIC and MBC of EEO NE against S. aureus were determined with minor modifications of existing experimental methods [44,45]. S. aureus was incubated in the LB medium up to the logarithmic growth phase, and the concentration was adjusted to 1 × 106 CFU/mL via absorbance testing. The diluted bacterial solution was added to a 96-well plate with 100 μL per well, and then 100 μL of the gradiently diluted EEO NE was added to each well to ensure that the concentration of EEO NE in wells ranged from 0.05 to 50 mg/mL. After incubation at 37 °C for 24 h, the minimum sample concentration without significant turbidity or precipitation in the wells was the MIC. Afterward, 100 μL of the culture solution was taken from the wells without visible bacterial growth, coated in LB solid medium plates, and incubated at 37 °C for 24 h. The growth of colonies in the plates was monitored, and the minimum sample concentration represented by the plate without visible bacterial growth was the MBC. Each experiment was repeated at least twice. ## 2.4.2. Inhibitory Activity Assay of EEO NE and CBM/CMC/EEO NE against Suspended S. aureus The antimicrobial activities of EEO NE and CBM/CMC/EEO NE were determined against S. aureus bacterial strains using the turbidimetric analysis method [26,46]. S. aureus was incubated in the LB medium to the logarithmic growth phase, and the concentration was adjusted to 1 × 106 CFU/mL via absorbance testing. A total of 100 μL of the negative control (sterile water), positive control (50 μg/mL of gentamicin sulfate solution), EEO NE, and CBM/CMC/EEO NE were added to each well of a 96-well plate, followed by the addition of 100 μL of the bacterial solution to each well and incubated at 37 °C for 48 h, during which 100 μL of the culture solution was taken at 12 h intervals, and the absorbance values were measured at 595 nm using an enzyme marker (ELX-80, Burton Instruments, Rockville Maryland, USA) with at least 3 parallels in each group. The antibacterial rate (%) was calculated as follows [4]:Antibacterial rate (%) = (OD0 − OD1)/OD0 × $100\%$,[4] where OD0 indicates the absorbance value of the negative control well and OD1 indicates the absorbance value of the positive control/sample well. ## 2.4.3. Inhibitory Activity of EEO NE on the S. aureus Biofilm Formation The activity of EEO in inhibiting biofilm formation was determined using crystalline violet staining [47]. A 96-well plate was incubated at a concentration of 1 × 106 CFU/mL in 100 μL per well, followed by the addition of 100 μL of negative control (sterile water), positive control (50 μg/mL of gentamicin sulfate solution), and EEO NE (0.5 × MIC, 1 × MIC, and 2 × MIC gradients) to the wells. It was incubated at 37 °C for 24 h, followed by aspiration of the bacterial solution. After the incubation, 200 μL of $1\%$ crystalline violet solution was added to each well for 30 min; the staining solution was aspirated and rinsed with PBS, then 200 μL of $33\%$ acetic acid solution was added to each well for 30 min, after which 100 μL of the solution was taken, and the absorbance value was measured at 595 nm, with at least 3 parallels in each group. The biofilm eradication rate was calculated according to formula [5] to evaluate the inhibitory activity on biofilm formation:Biofilm eradication rate (%) = (OD0 − OD1)/OD0 × $100\%$,[5] where OD0 indicates the absorbance value of the negative control well and OD1 indicates the absorbance value of the positive control/sample well. ## 2.4.4. Determination of the Scavenging Activity of EEO NE on S. aureus Biofilms A 96-well plate was incubated at 37 °C for 48 h at a concentration of 1 × 106 CFU/mL in 200 μL per well to form a mature biofilm. After aspiration and rinsing with PBS, 200 μL of negative control (sterile water), positive control (50 μg/mL of gentamicin sulfate solution), and EEO NE (0.5 × MIC, 1 × MIC, and 2 × MIC gradients) were added to each well and incubated at 37 °C for 4 h. The biofilm clearance activity was then evaluated as the biofilm elimination rate, as described in Section 2.4.3. ## 2.5.1. In Vitro Cytotoxicity Assay An assay was performed with reference to the method of Wang et al. [ 26]. A total of 0.1 g of CBM/CMC and CBM/CMC/EEO NE hydrogels were immersed in 1 mL of the DMEM medium and soaked at 37 °C for 24 h to make a master batch of 0.1 g/mL hydrogel extract. The mother liquor was then diluted with the DMEM medium to 1, 10, 100, 1000, and 10,000 μg/mL of gel extracts, which were subsequently UV-irradiated for 2 h and then decontaminated with a 0.22-μm filter membrane and set aside. L929 cells were inoculated in 96-well plates at a density of 1 × 105 per well, incubated at 37 °C for 24 h until the cells were plastered, then the medium was aspirated, the blank group was replaced with the fresh DMEM medium, and the gel group was replaced with each gel extract and incubated again for 24 h. Then, the cells were assayed according to the CCK-8 kit, and the cell survival rate was calculated. All samples were measured in triplicate. ## 2.5.2. Blood Compatibility Test 10,000 μg/mL of CBM/CMC and CBM/CMC/EEO NE hydrogel extracts were prepared according to 2.5.1. A total of 100 μL of a $4\%$ chicken blood erythrocyte suspension was added to 1 mL of each saline (negative control), deionized water (positive control), and the above gel extracts in a centrifuge tube and incubated at 37 °C for 1 h. The supernatant was centrifuged at 8000 r/min for 5 min, and the absorbance was measured at 545 nm, with at least 3 parallels in each group. The hemolysis rate (%) was calculated according to the following formula:Hemolysis rate (%) = (ODS − OD−)/(OD+ − OD−) × $100\%$,[6] where ODS is the OD value of the sample supernatant and OD+ and OD− are the OD values of the negative control and positive control, respectively. ## 2.6.1. Infected Trauma Molding The infected trauma model was constructed with reference to the method of Zhang et al. [ 4]. Age-appropriate male mice weighing 30–40 g were divided into negative, positive, and experimental groups. The mice were anesthetized before the experiment, and then the hair on their back skin was removed using an animal electric shaver. The surgical area on the back skin was disinfected with $75\%$ alcohol, and an 8 mm circular wound was created on each mouse. 100 μL of a suspension of S. aureus at a concentration of 1 × 107 was added to the wound and left for 15 min to allow bacteria to colonize the wound and construct a wound with chronic S. aureus infection. ## 2.6.2. Analysis of Wound Healing Rates Daily administration was started 24 h after molding with no treatment in the negative group, $1\%$ erythromycin ointment in the positive group, and the CBM/CMC/EEO NE composite hydrogel in the experimental group. On days 1, 4, 8, 12, and 16, the area of each wound treated in the different groups was measured and calculated using ImageJ software, with at least 6 parallels in each group. The wound healing rate (%) was calculated according to the following formula:Wound healing rate (%) = (S1 − Sn)/S1 × $100\%$,[7] where S1 is the area of the trauma on the first day of molding and *Sn is* the area of the trauma on the day n of molding. ## 2.6.3. Trauma Tissue Sampling Eight mice from each group were executed on days 1, 4, 8, 12, and 16, respectively, and the entire skin wound was cut off about 1 cm along the outer edge of the wound and washed with cold saline. The tissue was divided into three parts, one fixed in $10\%$ formalin for histopathological sectioning, one frozen at −80 °C for cytokine detection, and one for bacterial load detection. ## 2.6.4. Trauma Bacterial Load Testing The tissue was weighed and ground into a 0.1 g/mL tissue homogenate with saline, diluted in a gradient, spread on LB solid medium plates, and incubated for 24 h at 37 °C, and colonies were counted to calculate the bacterial load in the tissue. ## 2.6.5. Histological Testing The fixed skin tissues were trimmed, washed, and dehydrated, and then made transparent in xylene, paraffin-embedded, and sectioned at 4–6 μm. The obtained tissue sections were dewaxed with lignin and stained with Hematoxylin-Eosin (H&E) and Masson’s Trichrome Staining, respectively, and the changes in tissue morphology were examined using a light microscope (AXIO IMAGER Z1 Zeiss, Oberkochen, Germany). ## 2.6.6. Tissue Cytokine Assays The trauma skin was first mixed in a ratio of 1:19 with saline at low temperature and put into a glass homogenizer to make a $5\%$ tissue homogenate, centrifuged at 2000~3000 r/min for 20 min, and the supernatant, i.e., the sample to be tested, was taken. Then, the levels of interleukin-6 (IL-6), tumor necrosis factor α (TNF-α), transforming growth factor β1 (TGF-β1), vascular endothelial growth factor (VEGF), and epidermal growth factor (EGF) in the trauma tissue were measured using an ELISA kit. ## 2.7. Statistical Analysis All measurements were performed in triplicate and were reported as calculated means and standard deviations (mean ± SD). Statistical analysis (ANOVA analysis and Dunnett’s multiple comparison Test) was performed using SPSS 22.0 software, professional edition. The level of significance was determined as $p \leq 0.05.$ ## 3.1. Characteristics of EEO NE and CBM/CMC/EEO NE Optical observation provides a direct insight into the relevant properties of nanoemulsions. As shown in Figure 1, the resulting EEO NEs are clear and transparent, exhibiting a light blue color and showing a Tyndall effect when parallel light is directed at them. These phenomena are consistent with the basic criteria for nanoemulsions. When both Sudan III and methylene blue dyes are added, water-soluble methylene blue dye diffuses more rapidly in the emulsion, indicating that the emulsion type is oil-in-water. The average particle size of the prepared EEO NE is 15.34 ± 3.77 nm, and the PDI value is 0.173 ± 0.058, i.e., less than 0.2, indicating that the emulsion exhibits a uniform particle size distribution. The EEO NE shows a neutral pH value of 7, which is suitable for treating skin wounds. The examination of the rheological properties of hydrogels reflects the changes in their viscosity and elasticity. As shown in Figure 2A, the elastic modulus of both CBM/CMC and CBM/CMC/EEO NE hydrogels is slightly higher than the loss modulus, indicating that both hydrogels exhibit solid state properties. Combined with the fact that both moduli of the hydrogels are slightly frequency dependent, we assume that both hydrogels exhibit a weak gelation behavior. *In* general, the storage modulus G’ corresponds to the elasticity of the measured fluid, while the loss modulus G” corresponds to the fluid’s viscosity. Figure 2A shows that the elasticity and viscosity of the hydrogel with added EEO NE are improved compared to the sample without EEO NE, and the performance improvement can be better applied to improve wound repair. The lower the water loss rate, the better the water retention properties of the hydrogel. Water retention is an important indicator of the properties of hydrogel dressings, as it creates a moist environment that facilitates the growth, migration, and differentiation of trauma cells, thus promoting wound healing. As shown in Figure 2B, the water loss rate of CBM/CMC and CBM/CMC/EEO NE hydrogels increases over 24 h, reaching 54.942 ± $2.962\%$ and 60.268 ± $1.053\%$, respectively, at the 24th hour, wherein CBM/CMC/EEO NE exhibits a slightly higher value than CBM/CMC. It is speculated that the addition of EEO NE may have reduced the ability of the hydrogel to bind water, resulting in higher water loss. However, both hydrogels exhibit a long-lasting water-retention capacity, which is conducive to maintaining a moist environment on wounds, promoting collagen production and autoimmune repair. It is important that the moist environment created by a hydrogel dressing has an appropriate water vapor transmission rate, since only then it maintains the moisture content around the wound and promotes cell proliferation and wound healing [48,49]. When the water vapor transmission rate is too high, it tends to dry out the wound, which is not conducive to cell growth and the maintenance of a moist environment; furthermore, when the water vapor transmission rate is insufficient, it may allow exudate to accumulate on the wound, resulting in slow wound healing. As shown in Figure 2D, the water vapor transmission rate of CBM/CMC/EEO NE is lower than that of CBM/CMC during the 48 h test, but the change in the water vapor transmission rate is more stable than that of CBM/CMC, indicating that CBM/CMC/EEO NE has a stable water vapor transmission rate and can maintain a moist and permeable environment for the wound surface. The water vapor transmission rate is closely related to porosity. As shown in Figure 2C, the porosity of CBM/CMC and CBM/CMC/EEO NE is 70.430 ± $6.193\%$ and 63.586 ± $10.166\%$, respectively. Lower porosity results in a lower water vapor transmission rate, i.e., the water vapor transmission rate of CBM/CMC/EEO NE is lower than that of CBM/CMC. ## 3.2. In Vitro Antibacterial Activity The minimum inhibitory concentration and the minimum bactericidal concentration of EEO NE were determined by the standard broth dilution method. The experimental results show that the minimum use concentration of EEO NE without visible bacterial growth is 15 mg/mL; i.e., the MIC value of EEO NE is 15 mg/mL. By observing the colony production of the well plate culture on the plate, it is determined that the minimum use concentration of EEO NE without visible bacterial growth is 25 mg/mL; i.e., the MBC value of EEO NE is 25 mg/mL. The inhibition activities of EEO NE and CBM/CMC/EEO NE against suspended S. aureus were measured by absorbance value assay at 48 h. As shown in Figure 3A, the inhibition rates of EEO NE and CBM/CMC/EEO NE are higher than $50\%$ from 24 h onward, and they increase in the subsequent time, indicating that both EEO NE and CBM/CMC/EEO NE exhibit good long-lasting inhibition activity against the suspended S. aureus. The inhibition rate of EEO NE is higher than that of the treatment group of the gentamicin sulfate solution positive control within 48 h, indicating that the inhibition activity of the nano-emulsified EEO is comparable to or even slightly higher than that of the usual antimicrobials. This suggests that EEO NE has the potential to replace antimicrobials as a bacteriostatic substance. When EEO NE is combined with the hydrogel matrix to form the CBM/CMC/EEO NE hydrogel, its bacterial inhibition activity is reduced compared to EEO NE within 48 h, presumably due to the reduced release of EEO NE in the bacterial solution after combining it with the gel matrix. However, the inhibition rate after 24 h is greater than $50\%$, still exhibiting excellent bacterial inhibition ability. In the in vitro anti-biofilm formation and biofilm clearance assay of EEO NE (shown in Figure 3B,C), the inhibitory effect of EEO NE on the biofilm formation and clearance of S. aureus is dose-dependent. The 2×MIC concentration of EEO NE shows the highest inhibitions of the biofilm formation and clearance of S. aureus, 77.530 ± $7.292\%$ and 60.700 ± $3.341\%$, respectively, which are higher than the positive control of 73.775 ± $0.720\%$ and 44.900 ± $3.035\%$. This indicates that EEO NE has a superior ability to inhibit biofilm formation and remove mature biofilms compared to common antimicrobials. It further demonstrates the potential of EEO NE as a biofilm-inhibiting active substance that can be added to hydrogels for the treatment of infected chronic wounds. ## 3.3. In Vitro Biocompatibility The biocompatibility of CBM/CMC/EEO NE needs to be evaluated in vitro by cytotoxicity assay and hemolysis assay before in vivo experiments. As shown in Figure 4A, the survival rates of L929 cells under separate cultures of 1, 10, 100, 1000, and 10,000 μg/mL CBM/CMC/EEO NE hydrogel extracts range from 88.235 to $98.799\%$, and all of these are higher than $85\%$. This indicates that the hydrogel is not cytotoxic at concentrations equal to or below 10,000 μg/mL and can be used as a safe trauma dressing. In the hemolysis experiment (Figure 4B), hemolysis appeared in the positive control group, while the hydrogel group had no hemolysis. The calculated hemolysis rates of the CBM/CMCP and CBM/CMC/EEO NE groups are both less than $5\%$, meeting the clinical requirements for the hemolysis rate of biological materials. It can be concluded that the CBM/CMC/EEO NE hydrogel has good hemocompatibility. ## 3.4.1. Analysis of Wound Healing The therapeutic effect of the CBM/CMC/EEO NE hydrogel on the wounds infected with S. aureus was evaluated by recording the change in the wound area in mice. As shown in Figure 5A, by comparing the trauma changes in the negative control group, positive control group, and hydrogel group, it can be visualized that the use of CBM/CMC/EEO NE effectively promotes the reduction of the trauma area. By day 12, compared with the negative group, the trauma in the hydrogel treatment group no longer had blood crust, and the appearance of new skin tissue could be clearly seen. By day 16, the wounds treated with the hydrogel and positive groups almost returned to normal, while the negative group still exhibited visible scabs. Combined with results presented in Figure 5B, the wound healing rate of both the hydrogel and positive groups was higher than that of the negative treatment group throughout the treatment process. By day 12, the wound healing rate of the hydrogel treatment group reached 89.863 ± $2.608\%$, while that of the negative group was 82.576 ± $5.240\%$, showing a significant difference ($p \leq 0.05$). This indicates that using the CBM/CMC/EEO NE hydrogel showed more efficacy than the negative treatment group, so the EEO NE-added hydrogel significantly promotes the healing of infected wounds. ## 3.4.2. Trauma Bacterial Load Analysis The in vivo bacterial inhibition performance of the CBM/CMC/EEO NE hydrogel on S. aureus infected wounds was evaluated by measuring the change in bacterial load in trauma tissue. Figure 5C shows that using CBM/CMC/EEO NE hydrogel effectively inhibits bacterial growth in the infected trauma tissue. The bacterial load continually decreases with the duration of treatment, like the effect of antimicrobial treatment in the positive group. Combined with the results shown in Figure 5D, the bacterial load on the trauma surface of the hydrogel treatment group was already significantly lower than that of the negative group from day 4 onward. This indicates that the in vivo use of CBM/CMC/EEO NE has good inhibitory activity on the bacterial growth on infected trauma surfaces, preventing further deterioration of the trauma surface via infection, and thus facilitating trauma surface repair. ## 3.4.3. Histological Analysis of the Trauma Surface The histological effects of the CBM/CMC/EEO NE hydrogel on wound repair were evaluated from a histological perspective by observing and analyzing H&E and Masson’s Trichrome Staining histological sections of traumatized skin from mice. As shown in Figure 6, on the 4th day of molding the infected trauma of mice, the epidermis and dermis of all groups were destroyed, the epidermal cells were broken, and various fibrous tissues of the dermis were severely necrotic. A large amount of necrotic collagen was present, the skin appendages disappeared, and many inflammatory cells infiltrated the trauma. The inflammatory infiltration and collagen necrosis were relatively more severe in the negative group. On the 8th day, the epidermal and dermal cell tissues of the positive and hydrogel groups started to reorganize, with a large reduction in necrotic collagen, a significant appearance of new collagen, and a reduction in inflammation, while the negative group showed hyperplasia of the traumatized skin, a lack of flatness in the formation of the skin layer, and some areas with more severe inflammation and collagen necrosis remained. On the 12th day, the positive group and the gel group almost returned to normal; the skin structure was complete, the appendages began to appear, and the collagen fibers in the dermis began to arrange in an orderly manner. However, the negative group only showed initial improvement in the skin condition. There were still epidermal fractures and abnormal thickening. The skin was basically devoid of hair follicles, sweat glands, and other appendages. On the 16th day, the skin tissue of the positive group and the gel group further recovered. The epidermis and dermis cells were ordered and smooth, and hair follicles, sweat glands, and other skin accessory tissues were further formed. Additionally, the negative group still exhibited an abnormal thickening of the epidermis, and the skin accessory organs were not recovered. The above histological analysis shows that the CBM/CMC/EEO NE hydrogel is as effective as erythromycin ointment in the recovery of S. aureus-infected wounds, reducing the inflammatory response, promoting the formation of new collagen, accelerating the recovery of the epidermis and dermis in a smooth and ordered manner, and regenerating skin appendages. ## 3.4.4. Trauma Tissue Cytokine Analysis Inflammatory and growth factors, as products secreted by lymphocytes, are important in regulating the differentiation and proliferation of inflammatory cells. They can also set immune cells to injury sites, playing an important role in tissue healing or angiogenesis. In this study, five cytokines, IL-6, TNF-α, TGF-β1, VEGF, and EGF, which have important roles in skin tissue repair, were selected as the main indicators to investigate the effects of CBM/CMC/EEO NE hydrogels on infected wounds at the cellular level. IL-6 and TNF-α factors are related to inflammation. As shown in Figure 7A,B, IL-6 and TNF-α increased to different degrees in all treatment groups after successful molding. However, the hydrogel and positive groups had significantly lower values than the negative group. As the treatment continued, the levels of two factors, IL-6 and TNF-α, decreased continuously in the hydrogel and positive groups, being always significantly lower than in the negative group ($p \leq 0.05$). TGF-β1, VEGF, and EGF cytokines are associated with cell growth and differentiation, granulation formation, and anti-inflammatory hemostasis. As shown in Figure 7C–E, mice also showed varying degrees of increase in TGF-β1, VEGF, and EGF cytokines after injury and infection. Since wounds require a high expression of these three cytokines to promote wound healing, the increase in the factor content was more significant in the hydrogel and positive groups relative to the negative group. This indicates that the use of the CBM/CMC/EEO NE hydrogel significantly promotes the expression of TGF-β1, VEGF, and EGF growth factors at the cellular level as a mean to promote rapid wound healing. ## 4. Summary In the present study, we designed a nanoemulsion of eucalyptus essential oil with good in vitro antibacterial and anti-biofilm activity and combined it as an active substance with a hydrogel matrix physically cross-linked with Carbomer 940 and carboxymethyl chitosan to develop eucalyptus essential oil nanoemulsion hydrogels. The study results show that EEO NE has a good inhibitory and scavenging effect on the S. aureus biofilm. CBM/CMC/EEO NE exhibits good rheology, water retention, porosity, water vapor transmission, and biocompatibility as a trauma dressing. In vivo experiments have shown that CBM/CMC/EEO NE can effectively promote wound healing, reduce the bacterial load of wounds, and accelerate the recovery of epidermal and dermal tissue cells. 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--- title: Identification of m6A-associated LncRNAs as predict factors for the immune infiltration and prognosis of thyroid cancer authors: - Yongcheng Su - Beibei Xu - Jiangquan Li - Qianwen Shen - Ziyu Lei - Miaomiao Ma - Fuxing Zhang - Tianhui Hu journal: Annals of Medicine year: 2023 pmcid: PMC10054316 doi: 10.1080/07853890.2023.2192049 license: CC BY 4.0 --- # Identification of m6A-associated LncRNAs as predict factors for the immune infiltration and prognosis of thyroid cancer ## Abstract ### Objective This study aims to evaluate the prognostic value of m6A-associated long noncoding RNAs (lncRNAs) and their interaction with tumour microenvironment in thyroid cancer (THCA). ### Methods The clinical and gene expression data of tumours from 502 patients with THCA and 58 adjacent normal tissues were retrieved from The Cancer Genome Atlas (TCGA)–THCA dataset. The Pearson test was utilized to identify potential m6A-associated lncRNAs ($p \leq 0.001$ and Pearson correlation coefficient > 0.4). Quantitative real-time polymerase chain reaction was performed to verify the expression levels of lncRNAs in tissues. MTT, EdU, colony formation and wound-healing assays were performed to determine the functions of m6A-associated lncRNAs in THCA cell proliferation and metastasis. ### Results M6A-associated lncRNAs were identified in three cluster groups. A significant survival difference was found among them, with cluster 1 patients showing worse survival. Moreover, lower immune and estimate scores were correlated to poorer prognosis, and CD8+ T cell and memory CD4+ T cell levels were increased in cluster 1. Cluster 2, with better overall survival, had high expression of PD-L1 and CTLA-4. Eleven of the m6A-associated lncRNAs were screened to establish the risk model, including AC007365.1, AC008555.1, AC040160.1, AC064807.1, AC126773.4, AL023583.1, AL512306.2, EIF2AK3-DT, LINC00667, LYPLAL1-DT and MIR181A2HG. Based on the median risk score, THCA patients were stratified into low-risk and high-risk groups. Overall survival analysis showed a dramatic difference between the two groups. qRCR was performed to verify the expression levels of lncRNA (LYPLAL1-DT, EIF2AK3-DT and MIR181A2HG) in THCA and adjacent normal tissues. Furthermore, functional experiments showed that knockdown of MIR181A2HG obviously inhibited the proliferation and migration of papillary thyroid cancer (PTC) cells in vitro, whereas LYPLAL1-DT overexpression promoted PTC cell proliferation and migration. ### Conclusions Eleven of the m6A-associated lncRNAs were identified as a risk model to predict clinical outcomes and provide a novel and efficient immunotherapeutic strategy for THCA patients. Key messagesm6A-associated lncRNAs can be used to predict the clinical outcomes of thyroid cancer patients. An m6A-associated lncRNAs risk model, which can accurately evaluate the immune status and risk stratification in individual thyroid cancer patients, was established. Knockdown/overexpression of representative lncRNAs in the risk model significantly affected the proliferation and migration of papillary thyroid cancer cells. ## Introduction Thyroid cancer (THCA) is the most common endocrine malignancy worldwide, accounting for more than 586,202 new cancer cases and 43,646 deaths worldwide in 2020 [1]. Depending on histological differences, THCAs can be classified into differentiated thyroid carcinoma (DTC) and anaplastic thyroid carcinoma (ATC) [2]. DTCs, including thyroid, follicular and poorly DTCs, contribute to approximately $90\%$ of all patients with THCA [3]. The ATC subtype is associated with rapid progression and poor prognosis, and no effective therapy is currently available for the ATC subtype [2]. Therefore, the identification of new and more innovative and ideal therapeutic targets for THCA is urgent. Long noncoding RNAs (lncRNAs) are a class of RNAs of more than 200 nucleotides in length that do not code for a protein [4–9], previously considered ‘junk’ [10]. The rapid evolution in high-throughput biome sequencing technologies has allowed an increasing number of potential functions of lncRNAs to be discovered [11]. Moreover, an increasing amount of research has shown that lncRNAs play a key role in various physiological and pathological processes, including cancer initiation and progression [12,13] and regulation of immune responses [14,15]. For instance, lncRNA can activate the Wnt/β-catenin signaling pathway by interacting directly with β-catenin, subsequently promoting colon cancer epithelial-to-mesenchymal transition and metastasis [16]. Interest in the potential function of lncRNAs is increasing, and various types of studies on lncRNAs are rapidly emerging [17]. N6‐methyladenosine (m6A) modification is a type of eukaryotic RNA modification [18] that has been shown to play a regulatory role in numerous human diseases, especially in cancer initiation and progression [19], such as in lung [20], endometrial [21] and liver cancers [22]. It is reported that the upregulation of the m6A regulatory gene METTL14 contributes to pancreatic cancer metastasis [23]. LNCAROD can promote cancer progression through m6A methylation mediated by METTL3 and METTL14 in patients with head and neck squamous cell carcinoma [24]. Similarly, METTL3, a vital m6A methyltransferase, regulates the m6A modification of LINC00958 and affects the prognosis of patients with liver cancer [25]. In addition, recent studies have also shown that the m6A modification is related to immunoregulation [18, 26–29]. However, the underlying mechanism of how m6A-associated lncRNAs are involved in tumour regulation through immune infiltration in THCA remains unclear. To date, few studies have attempted to explore the association between m6A modification and the tumour immune response in THCA. We attempted to evaluate the prognostic value of m6A-associated lncRNAs in THCA. Subsequently, consensus clustering groups and risk scores were generated to further assess the relationship between m6A-associated lncRNAs and the tumour microenvironment (TME), including immune checkpoints, tumour immune cell infiltration and immune scores in THCA patients. ## Thyroid cancer samples collection Fourteen pairs of thyroid cancer and the adjacent normal tissue samples were collected from the first affiliated hospital of Xiamen University; all thyroid cancer samples were confirmed by pathological examination. This study was approved by the Institutional Review Board of the first affiliated hospital of Xiamen University and conducted with the informed consent of all patients. ## Cell lines, cell culture and cell transfection Papillary thyroid cancer cell lines (KTC-1 and BCBAP) were obtained from the Chinese Academy of Sciences (Shanghai, China) Cell Bank of Type Culture Collection. KTC-1 and BCBAP cells were grown in 1640 with $10\%$ fetal bovine serum (FBS) and cultured at 37 °C in a $5\%$ CO2 incubator. The LYPLAL1-DT overexpression and short hairpin RNA (shRNA) of MIR181A2HG were induced with lentiviral expression system. All sequence information is presented in Supplementary Table S1. ## Cell proliferation assay Cell proliferation was measured using the methyl thiazolyl tetrazoliym (MTT) assays, the MTT assays were performed following the manufacturer’s instructions. Approximately 3000 PTC cells were incubated for 24, 48, 72 and 96 h in 96-well plates, and 20 l of MTT ((5 mg/ml, Sigma-Aldrich; Merck KGaA) was added to each well for 4 h until the purple precipitate was fully yielded. Absorbance at 490 nm was measured in 15 min after 150 l DMSO was added into each well to dissolve the precipitates. ## EdU cell proliferation assays EdU assay was used to detect the DNA synthesis of growing PTC cells by using the EdU imaging kit (RiboBio, China), and the EdU assay steps were performed following the manufacturer’s instructions. ## Colony formation assays Approximately 500 cells per well were seeded into a 6-well culture plate and incubated at 37 °C for 2 weeks. After washing with PBS twice, cells were fixed with $4\%$ paraformaldehyde for 15 min and then dyed with crystal violet. Only colonies ≥ 50 cells were counted under a microscope. Each experiment was repeated three times. ## Wound healing Wound-healing assays were performed according to previously described methods [30]. ## Quantitative real-time polymerase chain reaction According to the manufacturer’s instructions, total RNA was extracted with the Trizol (Invitrogen) reagent. 1 μg of mRNA was reversely transcribed to cDNA by the reverse transcription system (AG11711, Accurate Biology, Hunan, China). qPCR amplification was subsequently performed with the SYBR Master Mix (YEASEN Biotech, Shanghai, China). The GAPDH gene level was used as reference. The primers for quantitative real-time polymerase chain reaction (qRCR) amplification were listed in Supplementary Table S2. ## Bioinformatic analysis The clinical and gene expression data (FPKM value) of tumours from 502 patients with THCA and 58 adjacent normal tissues were retrieved from The Cancer Genome Atlas (TCGA)–THCA dataset. Moreover, the expression profiles of 23 m6A regulatory genes in TC patients, including writers (METTL3, METTL14, METTL16, WTAP, VIRMA, ZC3H13, RBM15 and RBM15B), readers (YTHDC1, YTHDC2, YTHDF1, YTHDF2, YTHDF3, HNRNPC, FMR1, LRPPRC, HNRNPA2B1, IGFBP1, IGFBP2, IGFBP3 and RBMX) and erasers (FTO and ALKBH5), were extracted from the TCGA–THCA database. The Pearson test was utilized to identify potential m6A-associated lncRNAs ($p \leq 0.001$ and Pearson correlation coefficient > 0.4). Subsequently, m6A-associated prognostic lncRNAs in THCA were distinguished using univariate Cox regression analysis. The ‘ConsensusClusterPlus’ package in R was applied to perform cluster analysis [31]. The proportion of 22 human immune cell types in THCA patients was evaluated using the CIBERSORT algorithm, and the ESTIMATE algorithm, which included Immunoscore, ESTIMATE and stromal scores, was used to estimate the immune score in THCA patients [32]. An R script of the ESTIMATE algorithm was downloaded from http://bioinformatics.mdanderson.org/estimate. Higher ImmunoScores or StromalScores indicate greater levels of immune or stromal components in the TME. The ESTIMATE score is the sum of the ImmuneScore and StromalScore, and denotes the overall proportion of immune and stromal components in the TME. The formula for risk score was as follows: risk score=∑$i = 1$nexpression of ln cRNAn*coefficient ln cRNAn The TCGA–THCA dataset wa s randomly divided into a training dataset ($50\%$) and a test dataset ($50\%$). A LASSO analysis was performed to identify lncRNAs with prognostic value for THCA patients. ## Statistical analyses Statistical analysis was performed using R studio (version 4.1.1), the R packages ‘survminer’ and ‘survival’ were used to perform survival analysis, and the significance between groups was assessed using the log-rank test. Receiver operating characteristic (ROC) curves were applied to assess the risk score. All experiments were representative of three independent experiments. And the data (mean ± SD) were evaluated by GraphPad Prism version 8.0.2. Differences between two groups were analysed by Student’s t test and differences among multiple groups by one-way ANOVA. p Values less than 0.05 were considered statistically significant. ## Identification of m6A-associated lncRNAs in THCA We extracted and analysed the expression levels of 23 m6A regulatory factors in 502 THCA patients. Pearson correlation analysis was utilized to identify potential m6A-associated lncRNAs based on the TCGA–THCA cohort, when the Pearson correlation coefficient (R) was < 0.4 and p value was < 0.001, the lncRNA was defined as m6A-associated lncRNA. Ultimately, 322 lncRNAs were proposed to be m6A-associated lncRNAs (Supplementary Table S3), and the m6A regulator genes and m6A-associated lncRNA co-expression network was built based on Pearson correlation coefficients (Figure 1(A)). According to the univariate Cox analysis, 70 m6A-associated lncRNAs were closely correlated to the overall survival (OS) of THCA patients (Table S4). Figure 1(B) shows a forest plot of m6A-associated lncRNAs according to univariate Cox risk regression analysis, a lncRNA with HR > 1 was considered a risk lncRNA, and a gene with HR < 1 was considered a protective lncRNA. The heatmap (Figure 1(C)) and box plot (Figure 1(D)) display the differentially expressed m6A-associated lncRNAs in normal and THCA tissues. This indicates significant differences in the expression of m6A-associated lncRNAs between normal and cancer tissues and that these differences are correlated with the prognosis of patients with thyroid cancer. **Figure 1.:** *Identification of N6-methyladenosine (m6A)-associated long noncoding RNAs (lncRNAs) in thyroid cancer (THCA). (A) m6A-lncRNA co-expression network in THCA patients. (B) Forest plot of m6A-associated prognostic lncRNAs in THCA. (C) Heatmap of m6A-associated prognostic lncRNAs in THCA. (D) The expression levels of m6A-associated prognostic lncRNAs between normal and cancer tissues. *p < 0.05; **p < 0.01; ***p < 0.001.* ## Consensus clustering of m6A-associated lncRNAs in THCA The ‘ConsensusClusterPlus’ package in R was used to perform cluster analysis [31], which demonstrated that clustering with $k = 3$ resulted in the greatest stability. When $k = 3$, the consensus matrix was divided into three distinct clusters (Figure 2(A,B)). Subsequently, 502 THCA patients were assigned to three different clusters according to their expression of 70 m6A-associated prognostic lncRNAs: cluster1 ($$n = 180$$), cluster 2 ($$n = 249$$), and cluster 3 ($$n = 73$$). For details regarding cluster comparisons (see Supplementary Table S5). Survival analysis revealed differences in survival among the clusters, with patients in cluster 1 having poorer prognoses than the other clusters (Figure 2(C)). Notably, higher expression levels of m6A-associated lncRNAs were observed in cluster 1 (Figure 2(D)), suggesting that higher levels of m6A-associated lncRNAs predict poorer prognosis. And the upper bar of the heatmap also showed the distribution of clinicopathological features among three clusters, including TMN stage, age, gender and stage. **Figure 2.:** *Consensus clustering of m6A-associated lncRNAs in THCA. (A) Consensus clustering matrix for k = 3. (B) The relative change in area under cumulative distribution function curve for k = 2 to 9. (C) Kaplan–Meier curves of overall survival for the three clusters in THCA. (D) Heatmap depicting the clinicopathologic features among the three clusters.* ## Immune characteristics among the three clusters in THCA patients Previous studies have shown that treatment with immunotherapy and chemotherapy can be influenced by the expression of immune checkpoint proteins. Therefore, we first explored the differential expression of immune checkpoint genes (CTLA-4, PD-1 and PD-L1). There was no significant difference between cancer tissue and the adjacent healthy tissue (Figure 3(A,C,E)), whereas cluster 2 had a high level of expression of PD-L1 (Figure 3(B)) and CTLA-4 (Figure 3(D)). The CIBERSORT algorithm, a deconvolution approach to assess the level of immune cell infiltration, was used to assess the different immune cell infiltration levels among various clusters (Figure 4). The box plot showed that the proportion of CD8+ T cells (Figure 4(A)) and memory CD4+ T cells (Figure 4(B)) in cluster 1 were higher, whereas resting mast cell levels were significantly lower in clusters 2 and 3 (Figure 4(C)). As for macrophages, we found that the levels of M1 macrophages were lower in cluster 3 (Figure 4(D)), and M2 macrophages had higher levels in cluster 3 (Figure 4(E)). However, the expression of resting memory CD4+ T cells was not significantly different among the various clusters (Figure 4(F)). Together, these results suggest that the immune microenvironment plays an important role in the occurrence and progression of THCA and is closely related to the prognosis of THCA patients. **Figure 3.:** *Immune characteristics among the three clusters. (A) Programmed death-ligand 1 (PD-L1) expression in THCA based on The Cancer Genome Atlas (TCGA) database. (B) The expression level of PD-L1 in three clusters based on the TCGA database. (C). Cytotoxic lymphocyte associated antigen-4 (CTLA-4) expression in THCA based on the TCGA database. (D) The expression level of CTLA-4 in the three clusters based on the TCGA database. (E) Programmed cell death protein 1 (PD-1) expression in THCA based on the TCGA database. (F) The expression level of PD-1 in the three clusters based on the TCGA database. ns: not significant, *p < 0.05; **p < 0.01; ***p < 0.001.* **Figure 4.:** *The numbers of CD8+ T cells (A), memory-activated CD4+ T cells (B), resting mast cells (C), M1 macrophages (D), M2 macrophages (E), and resting memory CD4+ T cells (F) in the three clusters based on TCGA database. Correlation analysis between expression of programmed death-ligand 1 (PD-L1) and N6-methyladenosine (m6A)-associated prognostic long noncoding RNAs (lncRNAs) based on the Pearson coefficient (G). Correlation analysis between levels of programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) and m6A-associated lncRNAs based on the Pearson correlation coefficient. The upper right corner depicts the correlation between PD-L1 and m6A-associated lncRNAs in THCA, and the color of the dots represents the type of correlation (purple indicates a positive correlation and yellow indicates a negative correlation). The lower left corner depicts the correlation between PD-1 and m6A-associated lncRNAs in THCA, and the color of the dots represents the type of correlation (red indicates a positive correlation and green indicates a negative correlation). The size of the dots represents the magnitude of the correlation, with larger dots representing a stronger correlation. *p < 0.05.* Subsequently, a correlation analysis of immune checkpoint genes (PD-1/PD-L1) with m6A-associated lncRNAs was also performed based on Person correlation analysis, the results indicated that PD-L1 and PD-1 expression were found to have a significantly negative association with m6A-associated prognostic lncRNAs (Figure 4(G) and Supplementary Table S6). The ESTIMATE algorithm is used to infer the level of infiltrating stromal and immune cells in tumour tissues and tumour purity using gene expression data. The predictive ability of this method has been validated in large and independent data sets. As shown in Figure 5(A–C), significant differences in the immune and ESTIMATE scores were observed among three clusters; the immune score and ESTIMATE score in cluster 2 are clearly higher than those in clusters 1 and 3. In addition, the OS of patients in cluster 2 with higher immune and ESTIMATE scores was greater than that of clusters 1 and 3 (Figure 2(C), $$p \leq 0.007$$). Overall, cluster 2 was characterized by high TME scores and higher levels of immune checkpoint proteins (PD-L1 and CTLA-4), suggesting that THCA patients in cluster 2 are more likely to respond to immune checkpoint inhibition than patients in the other clusters. **Figure 5.:** *Immunoscore (A), ESTIMATE score (B), and stromal score (C) in clusters 1, 2 and 3. Gene set enrichment analysis of the N6-methyladenosine-associated long noncoding RNAs in cluster 2 (D–F) and cluster 1 (G–I), respectively. NES: normalized enrichment score; NOM p value: normalized p value; FDR: false discovery rate.* Additionally, gene set enrichment analysis (GSEA) indicated that cancer hallmarks, including leukocyte transendothelial migration genes (Figure 5(D)), Notch signaling pathways (Figure 5(E) and p53 signaling pathways (Figure 5(F)) were more strongly correlated with cluster 2. Glycine, serine and threonine metabolism (NES = −2.140, false discovery rate [FDR] q-value = 4.64E − 04, Figure 5(G), tryptophan metabolism (NES = −1.99, FDR q-value = 0.009, Figure 5(H)) and fatty acid metabolism (NES = −1.98, FDR q-value = 0.009, Figure 5(I)) signaling pathways were enriched in cluster 1. These results suggest that m6A-associated lncRNAs may play an important role in regulating cancer-related pathways. ## Construction of the m6A-associated lncRNA risk model in THCA patients According to the univariate Cox analysis, 70 m6A-associated lncRNAs were strongly correlated with the OS of THCA patients. Subsequently, LASSO regression analysis [33] selected 11 of the 70 m6A-associated lncRNAs for use in establishing a risk model to accurately evaluate risk stratification in individual samples (Figure 6(A,B)). These 11 lncRNAs included AC007365.1, AC008555.1, AC040160.1, AC064807.1, AC126773.4, AL023583.1, AL512306.2, EIF2AK3-DT, LINC00667, LYPLAL1-DT and MIR181A2HG. Risk scores were calculated using the following formula: risk score = AL023583.1 × 0.82 + AC007365.1 × 0.85 − AC008555.1 × 0.72 + AC040160.1 × 0.40 + AC064807.1 × 0.62 − AC126773.4 × 0.92 + AL023583.1 × 0.82 + AL512306.2 × 0.14 + EIF2AK3-DT × 0.08 + LINC00667 × 0.22 + LYPLAL1-DT × 0.26 − MIR181A2HG × 0.03. The median risk score was used to divide samples into low-risk and high-risk groups. Subsequently, the OS analysis revealed a dramatic difference between the high- and low-risk groups (Figure 6(C)) and testing datasets (Figure 6(D)). Supplementary Figure S1 shows the risk model distribution, survival status and heatmap of 11 m6A-associated prognostic lncRNAs in the training (Supplementary Figure S1(A)) and testing cohorts (Supplementary Figure S1(B)). The ROC analysis demonstrated that our risk model had a high prognostic value for THCA patients, the 3- and 5-year area under the curve (Figure 6(E–F)) in the training and testing datasets showed an excellent predictive value. **Figure 6.:** *Risk model from m6A-associated lncRNAs. (A–B) LASSO coefficient of m6A-associated lncRNAs in thyroid cancer (THCA). Survival analysis for THCA patients in the training (C) and testing cohorts (D). The receiver operating characteristic curve of the risk model in the training (E) and testing cohorts (F).* ## Risk model score as an independent prognostic factor in THCA patients We first performed univariate Cox regression and found that the risk score was correlated to OS in THCA patients (Supplementary Figure S2(A)), we then conducted a multivariate analysis, which further confirmed the results of the univariate Cox regression analysis (Supplementary Figure S2(B)). ## Association of the risk model score with age, N stage, clusters 1 and 2 and immunoscore in THCA In order to further investigate the correlation between risk scores and clinical characteristics, we analysed the differences in risk scores between subgroups stratified by clinical characteristics. Our findings revealed that the risk score was highest in THCA patients older than 65 years (Figure 7(A)). No major differences in risk scores were observed in relation to gender or T and M stage (Figure 7(B)–(E)). In terms of immune score, the risk score in the higher immune score group was lower than that in the lower immunoscore group (Figure 7(F)). Moreover, the risk model score was higher in cluster 1 than that in the other clusters (Figure 7(G)). Compared to the other consensus clusters, cluster 1 had a significantly higher risk score and poorer prognosis than clusters 2 and 3. **Figure 7.:** *Risk model score associated with clinicopathological features, including age (A); grade (B); T stage (C); M stage (D); N stage (E); clusters 1, 2 and 3 (F); and immunoscore (G). Heatmap demonstrating the clinicopathologic features between two risk groups (H).* Next, we performed subgroup analyses, and found that worse outcomes in THCA patients in the high-risk group were correlated with age (Supplementary Figure S3(A)–(B)), gender (Supplementary Figure S3(C) and (D)), M0 stage (Supplementary Figure S3 (E)), N stage (Supplementary Figure S3 (G) and (H)), T3–T4 stage (Supplementary Figure S3(J)) and pathological stages III–IV (Supplementary Figure S3(L)). The p values associated with the above subgroups, except for the M1 stage (Supplementary Figure S3(F)) and pathological stage I–II subgroups (Supplementary Figure S3(K)), were <0.05. Compared to the low-risk group, m6A-associated lncRNA, including AL023583.1, AC007365.1, AC040160.1, AC064807.1, AL512306.2, EIF2AK3-DT, LINC00667 and LYPLAL1-DT levels were higher in the high-risk group, whereas AC00855.1, AC126773.4 and MIR181A2HG were decreased (Figure 7(H) and Supplementary Figure S4(A)). The upper bar of the heatmap also identified significant differences in age, N stage, immunoscore and cluster groups between the two risk groups. ## Knockdown of LncRNA MIR181A2HG or LYPLAL1-DT overexpression affected the proliferation and migration of PTC cells in vitro In our study, 11 m6A-related lncRNAs were used to construct a prognosis model. For verification purposes, we initially selected four lncRNAs in the model with relatively low scores: MIR181A2HG, LYPLAL1-DT, EIF2AK3-DT and LINC00667. Our expectation was that if these four lncRNAs can be successfully verified, lncRNAs with higher scores should have even better chances of being correct. Analysis of TCGA data showed that MIR181A2HG was highly expressed in thyroid cancer, and LYPLAL1-DT, EIF2AK3-DT and LINC00667 were suppressed in cancer tissue (Figure 8(A–C)). We then validated the expression of these genes in our thyroid cancer tissue samples (Figure 8(D–F)). However, construction of the linc00667 expression plasmid failed, as the linc00667 fragment was too large (5489 bp). No further experiments were carried out on linc00667, thus related linc00667 qPCR data were not included in this manuscript. Since the functional experiments required to study LYPLAL1-DT and EIF2AK3-DT are the same, LYPLAL1-DT was chosen for subsequent functional testing. Additionally, we constructed plasmids to knockdown a high expression gene (MIR181A2HG) and overexpress a low expression gene (LYPLAL1-DT) for subsequent functional tests. **Figure 8.:** *Differential expression analysis of THCA patients with LYPLAL1-DT, EIF2AK3-DT and MIR181A2HG. LYPLAL1-DT(A), EIF2AK3-DT(B) and MIR181A2HG(C) expression based on TCGA-THCA dataset. qPCR analysis of LYPLAL1-DT(D), EIF2AK3-DT(E) and MIR181A2HG(F) expression in 14 pairs of THCA and adjacent normal tissues. An unpaired Student’s t test was used to determine the significance of differences. *p < 0.05; **p < 0.01; ***p < 0.001.* We further investigated the involvement of MIR181A2HG and LYPLAL1-DT in PTC in vitro. First, shCTL/shMIR181A2HG cell lines of KTC-1 and BCPAP were constructed by lentivirus transfection. qPCR results showed that the expression of MIR181A2HG was significantly reduced in the two cell lines (Figure 9(A,B)). Then, MTT (Figure 9(C,D)), EdU (Figure 9(F,G)) and colony formation assays (Figure 9(E)) were conducted to determine the role of MIR181A2HG on PTC cell proliferation. Knockdown of MIR181A2HG significantly inhibited proliferation of KTC-1 and BCBAP cells ($p \leq 0.01$). Subsequently, the wound-healing assay was used to detect the migration of PTC cells. The migration of MIR181A2HG-knockdown cells was significantly inhibited compared with the control group (Figure 9(H,I)). Similarly, to further confirm roles of LYPLAL1-DT in PTC, LYPLAL1-DT was overexpressed in KTC1 and BCBAP cells (Figure 10(A,B)). As expected, LYPLAL1-DT overexpression promoted cell proliferation and migration in PTC, indicated by MTT assays (Figure 10(C,D)), colony formation (Figure 10(E)), EdU (Figure 10(F,G)) and wound-healing assays (Figure 10(H,I)). These results collectively showed that lncRNA MIR181A2HG and LYPLAL1-DT affected the proliferation and migration of PTC cells. **Figure 9.:** *Knockdown of MIR181A2HG inhibited the proliferation and migration of PTC cells in vitro. (A–B) Relative MIR181A2HG expression in KTC1 and BCBAP cells transfected with two independent shRNAs targeting MIR181A2HG by qPCR. (C–D) KTC1 and BCBAP cell proliferation after knockdown of MIR181A2HG by MTT assay. (E–G) Representative results of the colony formation (scale bar:100 μm), and EdU assays (scale bar:100 μm) in KTC1 and BCBAP cells after MIR181A2HG-sh1 or MIR181A2HG-sh2 transfection. (H–I) MIR181A2HG knockdown suppressed migration capabilities in KTC1 and BCBAP cells. *p < 0.05; **p < 0.01; ***p < 0.001.* **Figure 10.:** *Overexpression of LYPLAL1-DT promoted the proliferation and migration of PTC and BCBAP cells in vitro. (A–B) Relative LYPLAL1-DT expression in KTC1 and BCBAP cells by qPCR. (C–D) KTC1 and BCBAP cell proliferation after overexpression of LYPLAL1-DT by MTT assay. (E–G) Representative results of the colony formation (scale bar:100 μm), and EdU assays (scale bar:100 μm) in KTC1 and BCBAP cells after overexpression of LYPLAL1-DT. (H–I) Overexpression of LYPLAL1-DT promoted migration capabilities in KTC1 and BCBAP cells. *p < 0.05; **p < 0.01; ***p < 0.001.* ## Correlation analysis between the risk model score and TME, including immune checkpoint and immune cell infiltration Blocking immune checkpoints has become a popular approach to cancer treatment. To identify the association between immune checkpoint and the risk score, we compared the expression levels of immune checkpoint genes PD-L1, CTLA-4 and PD-1 in the high- and low-risk groups (Figure 11(A–C)), and we found that the expressions of CTLA-4 ($$p \leq 0.0087$$) and PD-1 ($$p \leq 0.00027$$) were higher in the low-risk group than in the high-risk group. We used the CIBERSORT algorithm to analyse immune cell infiltration in the high- and low-risk groups. Correlation analysis showed that neutrophils (Figure 11(D)), activated NK cells (Figure 11(E)) and plasma cells (Figure 11(G)) were negatively correlated with the risk model score, and regulatory T cells (Tregs) were positively correlated with the risk model score ($p \leq 0.05$, Figure 11(F)). However, no significant correlations were observed in relation to other types of immune cells. In addition to CIBERSORT, we used a different method of immune deconvolution analysis, ssGSEA [34], to further characterize the differences in immunological function. Using the ssGSEA method, we compared the infiltration of 23 tumour immune cells between high-risk and low-risk THCA patients. As shown in Supplementary Figure S4(B), the risk score was negatively correlated with most tumour immune cell types. Furthermore, the levels of most tumour immune cell types differed between the high-risk and low-risk groups. The low-risk group had a higher level of immune cell infiltrations than that of the high-risk group, and the correlation analysis demonstrated that the risk score was negatively correlated with the levels of most immune cells, except for CD56 dim natural killer cells, eosinophilia, monocyte and type 17 T helper cells (Supplementary Figure S4(C)). Collectively, our risk score may allow the assessment of the tumour immune microenvironment to further ascertain whether immunotherapy can be generally applied in THCA patients. **Figure 11.:** *The PD-L1 (A), CTLA-4 (B) and PD-1 (C) expression levels by the risk score groups. Correlation between immune cells infiltration and risk score for (D) neutrophils, (E) activated natural killer cells, (F) regulatory T cells (Tregs) and (G) plasma cells.* ## Discussion Several studies have demonstrated that m6A modification may play a regulatory role in cancer pathogenesis; however, its role in THCA progression by regulating lncRNA is poorly understood. In our study, we identified 70 m6A-associated prognostic lncRNAs from 502 TCGA–THCA patients, subsequently, the TCGA–THCA dataset was divided into three cluster groups by consensus expression of 70 m6A-associated prognostic lncRNAs. Notably, a significant survival difference was found among the three groups, cluster 1 had worse survival and higher expression of m6A-associated lncRNAs than the other clusters. Moreover, we also found that lower immune and ESTIMATE scores were associated with poorer prognosis in cluster 1 compared with the other clusters. Regarding immune checkpoints, cluster 1, which showed worse OS, had a low level of PD-L1 expression, which indicated those patients would not respond to immune checkpoint inhibitors. These results indicate that m6A-associated lncRNAs exert vital functions in the tumour immune microenvironment and correlate with the prognosis of THCA patients. Subsequently, based on LASSO regression analysis, 11 of the m6A-associated lncRNAs were screened from the 70 m6A-associated prognostic lncRNAs to establish the risk model to accurately evaluate risk stratification in individual samples. OS analysis demonstrated that there were dramatic differences between the low- and high-risk groups. Subgroup analysis demonstrated that risk score is effective for further distinguishing different subgroups, and significant differences were observed with respect to age ($p \leq 0.05$), N stage ($p \leq 0.05$), immunoscore ($p \leq 0.001$) and cluster groups ($p \leq 0.01$) between the two risk groups. All the above results confirm that risk stratification according to the m6A-associated lncRNAs risk model would improve personalized therapy and improve outcomes of THCA patients. Using the ssGSEA method, we found that the levels of most tumour immune cell types differed between the high-risk and low-risk groups. The low-risk group exhibited a higher level of immune cell infiltration than the high-risk group, and the correlation analysis demonstrated that the risk score was negatively correlated with the levels of most immune cells. Similarly, the high-risk group was characterized by lower expression of immune checkpoint genes (CTLA-4 and PD-1), which was negatively correlated with poorer outcomes. Together, these results suggest that the immune microenvironment plays an important role in the occurrence and progression of THCA and is closely related to the prognosis of THCA patients. Interestingly, we found the highest levels of CD8T cell infiltration in cluster 1, which also had the worst prognosis. Previous studies have demonstrated that CD8+ T cells can exert antitumour effects against multiple cancer types, and high levels of CD8+ T cell infiltration are associated with better prognosis. Recent research has discovered that CD8+ T cell status is correlated with poorer OS in invasive mucinous adenocarcinoma [35] and renal cell carcinoma (RCC) [36–38]. Nakano et al. indicated that the negative impact of CD8+ T cells and CD4+ T cells on prognosis was mainly attributed to the cancer grade or the proliferative activity of RCC cells, and infiltrations of CD8+ T cells were not correlated with the efficacy of antitumour immunity [38]. Petitprez et al. [ 39] also demonstrated that a higher progression rate was observed in prostate cancer patients with high CD8+ T cell counts. Moreover, Leclerc et al. showed that CD73 suppresses immune surveillance mediated by CD8+ T cells and converts them into cancer-promoting factors [40]. Likewise, Ness et al. [ 41] also found that CD8+ T cells have immunosuppressive capabilities, which is an important mechanism that underlies cancer development. While the specific mechanisms remain poorly understood, our results suggest that THCA patients with higher levels of CD8+ T cells tend to have worse clinical outcomes. In order to further verify the reliability of our risk model, we detected the RNA expression levels of the representative genes in the model in thyroid cancer tissue samples. Consistent with TCGA database analysis, MIR181A2HG was highly expressed in thyroid cancer, while LYPLAL1-DT, EIF2AK3-DT and LINC00667 were low expressed in cancer tissues. MIR181A2HG has been reported to be associated with the prognosis of bladder cancer [42] and THCA [43,44]. Furthermore, MIR181A2HG may also impair the proliferation and migration of vascular endothelial cells through the miRNAs/AKT2 axis [45]. Similarly, Zhu et al. showed that LncRNA LYPLAL1-DT could regulate the process of autophagy through the miR-204-5p/SIRT1 axis [46]. In Zhu’s study, the overexpression of LYPLAL1-DT facilitated endothelial cell proliferation and migration, increased autophagy activity. Additionally, monocytic cells adherence to endothelial cells was also reduced by LYPLAL1-DT [46]. Interestingly, functional experiments in our study showed that knockdown of MIR181A2HG obviously inhibited the proliferation and migration of PTC cells in vitro, which was consistent with the finding of previous studies. Whereas LYPLAL1-DT overexpression promoted PTC cell proliferation and migration. The above results verified the reliability of our risk score in tissue and in vitro cell models, respectively. At present, reports on how the m6A-associated regulator lncRNAs interact with the tumour immune response have been limited. Wang et al. [ 47] constructed a risk model based on eight m6A-associated lncRNAs. Consistent with our results, this study highlighted that m6A-associated lncRNAs are closely related to immune regulation in thyroid cancer. However, unlike the study by Wang et al. we also verified the reliability of our model through functional experiments on several factors from the risk model. Moreover, we verified the reliability of our risk score in both clinical sample tissues and in vitro cell models. In our study, the risk scores were evidently associated with immune cells and immune checkpoints. Furthermore, the scores were inversely related to the level of neutrophils, activated NK and plasma cells. Recent studies have demonstrated that neutrophils play a vital role in the antitumour effect [48,49]. Similarly, NK cells are well-known antitumour factors, as reported in several studies [50–52]. The low levels of NK cells and neutrophils, and low expression of immune checkpoint genes PD-L1 and CTLA-4 seem to be markedly correlated with worse prognosis in our risk model. ## Conclusions In the present study, we sought to examine how m6A-associated lncRNAs interact with the TME and affect the prognosis of patients with THCA. Our study identified 70 m6A-associated prognostic lncRNAs. Among them 11 lincRNAs were used to construct an m6A-associated lncRNA risk model, which might be used to predict the clinical outcomes of THCA patients. Two selected lncRNAs MIR181A2HG and LYPLAL1-DT were further verified in clinical samples and THCA cell lines. The present study may provide a novel and efficient immunotherapeutic strategy for the treatment of THCA patients. ## Data availability statement Data are contained within the article or Supplementary. Further inquiries can be directed to the corresponding author. ## Patient consent Written informed consent has been obtained from the patient(s) to publish this paper. ## Author contributions Conceptualization, F.Z., Y.S. and T.H.; Data curation, Y.S., B.X. and F.Z.; Formal analysis, B.X. and T.H.; Investigation, B.X. and J.L.; Methodology, J.L. and Q.S.; Resources, Y.S.; Software, B.X. M.M. and Z.L; Validation, J.L, Q.S. and Z.L; Visualization, B.X.; Writing—original draft, Y.S. F.Z. and T.H.; Review and editing, T.H. 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--- title: 'Challenges around Child-Feeding Practices with ‘Comida Chatarra’: A Qualitative Study to Understand the Role of Sociocultural Factors in Caregiver Feeding Decisions' authors: - Florence L. Théodore - Anabelle Bonvecchio - Ana Lilia Lozada Tequeanes - Rocío Alvarado - Armando García-Guerra - María Angeles Villanueva Borbolla - Mauro Brero journal: Nutrients year: 2023 pmcid: PMC10054330 doi: 10.3390/nu15061317 license: CC BY 4.0 --- # Challenges around Child-Feeding Practices with ‘Comida Chatarra’: A Qualitative Study to Understand the Role of Sociocultural Factors in Caregiver Feeding Decisions ## Abstract A massive incorporation of ultra-processed products into young children’s diets worldwide and in Mexico has been documented. The aim of this study is to understand the role of sociocultural factors in principal caregivers’ decisions to give a type of ultra-processed food to children under age five, called ‘comida chatarra’ (‘junk food’ in English), usually includes sugar-sweetened beverages, sweet and salty snacks, and sweet breakfast cereals. We conducted a descriptive, observational qualitative study. The research was conducted in urban and rural communities in two Mexican states. Twenty-four principal caregivers were equally distributed between the two states and types of communities. They were interviewed in person. Phenomenology underpinned this study. Results highlight the preponderant role of culture in food choices and feeding practices with junk food. Local culture influences child-feeding with ultra-processed products through social norms, knowledge, or socially constructed attitudes. These social norms, built in the context of abundant ultra-processed products and omnipresent marketing, ‘justify’ children’s consumption of junk food. They acquire these products from the principal caregivers, family members, and neighbors, among others, who reward and pamper them. These actors also define what amount (small amounts) and when (after meals as snacks) children are given these products. Cultural factors must be considered in the development of effective public policies and programs that aim to change the culture around ultra-processed products among children and avoid their consumption. ## 1. Introduction For more than two decades, the massive incorporation of ultra-processed products (UPPs) into the diets of adults and young children has been widely documented worldwide and especially in Latin America [1,2]. These artificial products are unhealthy due to the way they are manufactured and their high content of added sugar, salt, and/or fat [3]. UPPs are generally directed at children and adolescents. They include sugar-sweetened beverages, sweet and salty snacks, processed meat, and sweet breakfast cereals. UPPs have been associated with a large spectrum of preventable communicable diseases [4]. The high level of UPP consumption is the result of political and economic processes related to liberalism, free trade agreements [5], and tourism development [6] that shaped the obesogenic environment [7] under which UPP intake is encouraged through powerful marketing strategies aimed at positioning these products as widely available and desirable [8]. Rural and urban landscapes in Mexico with the highest consumption of UPPs are described as ‘food swamps’ [9,10], a geographic metaphor for the inundation of unhealthy products in communities with healthy food options [11]. Food swamps predict obesity rates [12]. In Mexico, UPPs are extensively advertised in public spaces, including streets [13], grocery stores, TV [14], social media [15], and inside and around schools [16,17]. Unlike Uruguay [18], the terminology for UPPs is unknown for the Mexican population, and the closest term is ‘comida chatarra’ (‘junk food’ in English) [19]. In this article, ‘comida chatarra’ or ‘chatarra’ will refer to the participants’ own use, whereas the term “UPPs” will refer to the way in which these unhealthy products are named according to the NOVA classification [20]. Research on UPPs has focused on measuring purchases [21] or intake [22] among adults and children, as well as associated harms to health [4,23,24]. Other studies have analyzed conceptualizations of UPPs [25,26,27] and identified the drivers and facilitators of their intake [19,28]. This evidence is essential to guide the development of public policies and educational programs aimed at preventing obesity, a major public health issue in Mexico [29,30]. However, little is known about caregivers’ experiences emerging in this food swamp when providing food to children under age five, where antagonistic narratives about UPPs coexist in terms of their content and healthiness, which is important to caregivers worldwide [26,31]. The consumption of UPPs is reported from early childhood [32,33,34], a life stage considered particularly ‘vulnerable’ as malnutrition can lead to irreversible consequences for growth and development [35,36], and the food habits adopted can endure for life. Therefore, it is essential to understand which factors and processes influence principal caregivers’ (PCs) decisions to give UPPs to children under age five. It is important to study this from their perspective and from different theoretical frameworks, such as the theory of planned behavior, food choice decision framework, or the behavior change wheel, among others [37,38,39]. This article focuses on the role of sociocultural factors in PCs’ experiences and decisions to give UPPs to children under age five, analyzing the meaning of ‘chatarra’ and the different decisions made by caregivers in Mexico from rural and urban landscapes. Culture is understood as a set of traditions, lifestyles, knowledge, beliefs, and norms shared by the members of a society, which are socially acquired [40]. Food is shaped by culture [41], but culture also shapes food choices and the willingness to incorporate new foods [42,43]. We aimed to understand how PCs navigate the food swamp, as well as their experience with ‘chatarra’ and feeding practices of children under age five by analyzing their practices, beliefs and knowledge, attitudes and social norms, and the way they give meaning to their actions. This study aimed to inform the design of a mHealth strategy to prevent malnutrition among children under age five and promote behavior change towards a ‘healthy’ lifestyle by sending short message services (SMS) about nutrition and health to PCs living in vulnerable economic situations. ## 2.1. Research Design Our study was descriptive, observational, and qualitative. We conducted 24 in-depth face-to-face interviews with PCs. ## 2.2. Theoretical Framework Phenomenology underpinned this exploratory qualitative research study, which focused on lifeworld study and the subjective consciousness and experience of people built through daily life interactions and dialogue among individuals [44]. This framework guided how we explored the subjective lived experience of PCs and how we interpreted their perceptions and feeding practices related to ‘comida chatarra’, a type of UPP. ## 2.3. Setting, Participants, and Purposive Sampling We conducted our research in urban and rural communities of two states (in the south and center regions of Mexico). The first was the state of Yucatan, located in the peninsula of Yucatan, with predominant Mayan culture, which has undergone great changes from traditional to globalized diet [32]. The second was the state of Morelos, with easy access to big cities, located about eighty kilometers from Mexico City, one of the most populated cities in the world. States were selected according to the implementation feasibility of the project. In-depth face-to-face interviews with PCs were equally distributed between the two states in urban and rural communities. UPPs were one of the general health and nutrition topics explored. Our sampling was purposive [45]. Considering that experiences with infant feeding could depend on other people, on the state, the type of locality (urban and rural), and whether women were first-time mothers or not, we introduced this diversity when constructing our sample. Inclusion criteria were being a PC of children aged 24–59 months (although we explored feeding experience from birth) in charge of their daily feeding and care, having access to a functional cell phone, and being a beneficiary of the federal social protection conditional cash transfer program named Prospera [46] due to economic marginalization defined by the lack of education, housing and availability of goods. Being a PC of a child with a disease involving a particular diet was the only exclusion criterium because feeding experiences might have been different. The research team recruited participants through primary health care centers based on a list of caregivers who met the study’s inclusion criteria. ## 2.4. Data Collection Topics explored with PCs in the in-depth interviews included: family dynamics around food and UPPs consumption (including industrial sugar beverages), practices, knowledge (especially harm and benefits to health), attitudes, and social norms related to the consumption of UPPs by infants and young children. To study the concept of UPPS, we explored topics with the participants using the words ‘chatarra’ and ‘comida chatarra’. Prior to the interview, informants answered a sociodemographic questionnaire (age, level of education, number of children, among others). In each state, two teams of three junior researchers with master’s degrees in public health (5 females and 1 male) completed a three-day training and piloted the instrument. The fieldwork was conducted for two weeks in October (Yucatán) and two weeks in November 2019 (Morelos). A senior social science researcher designed the qualitative study, supervised the fieldwork, and analyzed and interpreted data. Our fieldwork was conducted before the approval of the new nutritional warning labels (NOM-051) in January 2020, which allows consumers to quickly identify healthy and unhealthy products [47]. All interviews were conducted in Spanish and lasted between 45 and 80 min. We translated the selected testimonials for this article into English. ## 2.5. Analysis In-depth interviews were audio recorded and transcribed verbatim and verified for quality. To interpret the in-depth interviews, the team followed a systematic procedure: [1] Categories and dimensions were identified using the initial in-depth interview guide based on phenomenology (gathering data on experiences) and the research question; [2] Emerging categories were included in the coding tree after a team discussion (Figure S1); [3] Encoding was performed with NVivo® software and results were interpreted from interference and contextualization of the testimonials [48]. The six junior researchers coded the interviews, and the senior researcher supervised the process and organized regular meetings to ensure a standardized process. Using grounded theory and comparative methods [49], a junior and senior researcher (one per state) interpreted the data and were in constant communication to guarantee validity. ## 3.1. PCs’ Characteristics The average age of the sample was 34.6 years for Yucatan and 32.2 years for Morelos. Women from Morelos had a slightly higher educational level and a number of children (more than three children per PC) (Table 1). Our sampling consisted only of the children’s mothers. The sociodemographic information of each of the 24 participants is presented in Table S1. Despite cultural specificities, we detected little differences between PC’s experiences with UPPs in Yucatan and Morelos. Therefore, the information is presented without distinguishing between the states. ## 3.2. UPP Availability and Child-Feeding Practices The PCs reported obtaining food from markets, supermarkets, and local stores (including greengrocers and poultry stores) and from backyards and fruit trees on a regular basis. All PCs mentioned a high availability of ‘chatarra’ in their neighborhood, thanks to an extensive network of street stalls (especially around schools) and grocery stores, where children usually hung out. In urban settings, PCs mentioned a greater diversity of UPPs. Throughout the day, PCs routinely offered children a variety of ‘chatarra’. The most mentioned type of ‘chatarra’ was cookies, added sugar yogurts, drinkable yogurts, candies, gum, chips, ‘chicharrón de harina’ (fried Mexican snacks made with flour and salt), and pizza, among others. In the urban communities of both states, PCs also mentioned offering flan (a Mexican dessert), a high number of chip brands, pastries, and powdered chocolate in drinks. Sweet breakfast cereals were mentioned in the urban and rural landscapes of both states and in the rural communities of Morelos. In this context of high availability, the PCs saw children’s consumption of ‘chatarra’ as “normal” nowadays and said that it had been normalized over the years: Finally, ‘chatarra’ was also associated with celebrations and conviviality. ## 3.3. PC’s Knowledge and Attitudes of ‘Chatarra’ PCs are immersed in a universe where conflicting information about UPPs coexists, as presented below. It is important to understand knowledge and attitudes toward ‘chatarra’ to understand the way PCs manage UPPs with children. ## 3.3.1. Definition of ‘Chatarra’ PCs mentioned a small number of products that they considered as ‘chatarra’: chips, ‘chicharron de harina’ (in Spanish), candies, store-bought cookies, and cola soda. Most ‘chatarra’ products are packaged. Urban PCs had a broader conception of ‘chatarra’, including foreign foods such as hamburgers, hotdogs, pizza, or instant food. One PC even mentioned industrial baby food jars and yogurts. However, generally, yogurts (those with added flavors and sugars) are considered healthy food by PCs. PCs noted the following features of ‘chatarra’: unnatural because it is made of chemicals and preservatives, with high content of sugar and/or fat, and no nutrients or vitamins associated with good health and growth among young children. However, we did identify inconsistencies in the PCs’ own storytelling; products that should belong to ‘chatarra’, according to the previously mentioned characteristics, are not always considered as such by PCs. For example, orange-flavored soda or industrial juice or chocolate powder because they supposedly contain ‘vitamins,’ as announced in the brand slogans: Despite being products that are high in sodium, sugar, and chemicals, a wide range of UPPs are not considered ‘chatarra’ by PCs, such as processed meats and sausages, which are widely consumed by children for being “a cheap nutritive food”. In brief, PCs’ knowledge of these product characteristics and their health effects are based on a variety of sources that are not always aligned with nutritional recommendations, and this guides their navigation in the food swamp. ## 3.3.2. Beliefs about Health Effects Knowledge about the health issues that can be caused by ‘chatarra’ consumption came from many sources (health centers, schools, own experiences, the folk culture). PCs expressed that ‘chatarra’ do not nourish children, unlike vegetables, fruits, and meat (including processed meats and sausages or tortillas, which are sources of nutrients and vitamins necessary to prevent diseases (urban landscapes) and to guarantee healthy growth (rural landscapes). PCs also associated these ‘chatarra’ with indigestion (‘empacho’, a Latin-American folk illness), grounded on the idea that children’s stomachs are not ready for certain junk food: PCs considered that not all these ‘chatarra’ had the same harmful potential, ranking them according to the degree of assessed damage. PCs perceived chips and soda as very harmful, while they considered that store-bought cookies “do not harm and do not benefit” (#4). According to PCs, in addition to the chemicals, soda has a high-sugar content responsible for diabetes. Sugar seemed to be an ingredient feared by PCs and identified by them in sweets, juices, and soda, among others, creating a kind of Saccharophobia towards sweet UPPs. Some PCs included yogurts as they contain milk, and although they also have preservatives, PCs consider that it is much better to give children yogurt than chips (#17). Finally, most PCs associated ‘chatarra’ consumption with obesity and diabetes. Although some PCs commented that they strive to avoid children’s consumption of those very harmful ‘chatarra’ (soft drinks, chips), they emphasized their lack of control because of two main factors: children’s taste preferences and the role modeling of family members (elder siblings, parents, grandparents), friends, or neighbors they see eating ‘chatarra’. Eating and drinking chatarra throughout the day has become a social norm in all age groups of rural and urban communities of these two states, normalizing snacking among adults and children. However, there was a moral judgment of ‘laziness’ towards PCs who gave these ‘chatarra’ to children instead of nutritious food, ## 3.3.3. Hedonist Domain Regardless of their knowledge about the damage of ‘chatarra’ to health, PCs assimilated them as a ‘craving’ or a ‘treat’ for children to be given in addition to food considered as nutritious. By establishing it as a ‘craving’ and a snack, a very general idea in both states, PCs differentiated it from the home food considered nutritious. From what was reported by PCs, ‘chatarras’ function is purely hedonistic but can also be problematic when children only want to eat it, ignore homemade food, or get sick. An emerging theme of this study is the tension experienced by PCs between two principles that structure their actions towards child-feeding that placed them in a difficult situation with ‘chatarra’. On the one hand, they seek to ensure children’s health and growth, and on the other hand, they attach importance to pleasing their children by satisfying their cravings and rewarding them with ‘chatarra’, which is stimulated by an obesogenic environment: In summary, according to PCs, ‘chatarra’ is considered a craving, treat, or prize that can also be harmful to children’s health. As a caregiver or a mother, the way to ‘treat’ little children is with ‘chatarra’, a social norm that promotes its consumption by children. Although economic constraints constitute a protective factor against UPP consumption, families’ poverty and lack of money to buy these products to fulfill their children’s cravings can generate frustration among PCs. ## 3.3.4. Towards Reconciliation of Health and Hedonic Principles We identified two main ideas in the PCs’ narratives that allowed them to continue giving ‘chatarra’ to children, including those considered to be the most harmful. First, PCs thought that giving them occasionally or in what they considered to be small amounts (called ‘probaditas’ in Spanish) of UPPs mitigated the potentially harmful effects. From this PC’s narrative, offering ‘probaditas’ (small portions of UPPs) allowed PCs to reconcile young children’s pleasure and health, two a priori incompatible aims. Second, offering ‘chatarra’ to children followed certain rules, such as not giving it to them before meals, avoiding displacing homemade meals, and guaranteeing necessary requirements for children’s growth and health. We identified more strategies implemented by PCs to control the amount of ‘chatarra’ consumed by children to mitigate its potential damage. PCs offered an option of ‘chatarra’ to children that they considered to be less harmful, not necessarily based on nutritional knowledge of the product, for example, the choice of orange soda instead of cola soda. Another strategy consisted of reducing the amount of ‘chatarra’ given to children by mixing it with foods and drinks considered healthy, such as mixing cola soda with water or sugary cereals with those that are not. Sharing a single package of chips among several children or giving them cookies or candies little by little were other examples given by PCs to limit children’s ‘chatarra’ consumption. Another strategy mentioned was aimed at avoiding stimulating the children’s desire to consume chips or sodas, asking siblings or the father to be discrete when eating these ‘chatarra’. ## 4. Discussion This article highlights the preponderant role of culture in food choices and feeding practices in two Mexican states. We focused on a type of UPP referred to as ‘comida chatarra’, which is broadly incorporated into children’s diets in part thanks to powerful marketing strategies. PCs and environmental factors contribute to the normalization of child-feeding with ‘comida chatarra’ through a series of practices, experiences, and meanings linked to sociability, affection, and maternity. This role of culture in food choices and feeding practices has been previously documented elsewhere [50,51] in Mexico. As far as we are aware, this is the first study that investigates meaning and mediations related to some UPPs (‘chatarra’) in the context of children’s feeding practices and behaviors through PC’s experiences. The study underlined the way local culture influences children’s feeding with UPPs through social norms, knowledge, or socially constructed attitudes. Regarding child-feeding with ‘chatarra’, we identified a series of social norms built in the context of abundant UPPs and the omnipresence of their marketing. In a way, these social norms ‘authorize’ children to eat junk food, obtaining it from PCs, family members, and neighbors, among others, with the purpose of rewarding and pampering them, as previously documented [52]. Social norms also define in what amount (small amounts) and when (after a homemade meal as a snack) to give these products. Through an approach focused on the study of daily life, we identified five findings that represent major worldwide public health concerns. First, in our research, the universe of products considered as ‘chatarra’ by PCs is varied but does not include all UPPs, leaving out some that are widely consumed by children in Mexico and considered nutritious food (e.g., processed meat, industrial baby food jar), an important public health issue if we consider the associated health harms. As also reported in Uruguay, not all UPPs were considered unhealthy and detrimental to children’s health and growth by PCs [26], which was probably due to the lack of a simple and comprehensible food labeling system in both countries at the time of the studies, as well as misconceptions caused by marketing. From a public health perspective, actions for raising the population’s awareness about the large range of UPPs that are not only limited to a few numbers of ‘chatarra’ products are urgently required. In this context, food labeling acquires relevance as an instrument to support healthy choices among the population. Second, PCs reported a wide availability of ‘chatarra’. Our data suggest that child-feeding with ‘chatarra’ is promoted by the food environment, prompted by the wide availability of UPP in close proximity, which has also been documented worldwide [53,54,55]. Moreover, advertising messages form positive perceptions of UPPs among PC. Omnipresent networks of stores constantly encourage UPP consumption among children and their provision by an immediate circle of acquaintances [56]. This routine consumption of ‘chatarra’ by children in Mexico contrasts with what was documented in Brazil, where it is conceptualized as breaking the routine that is based on home-style food [57]. We do hypothesize that commercial strategies of food corporations aimed at converting ‘chatarra’ into highly available, accessible, desirable, and hyper-palatable products have facilitated its incorporation into the population’s daily life and culture (including children). These commercial strategies are particularly effective in low- and middle-income countries, most of which share limited governance [58] that favors a significant permeation of companies in all aspects of society (legal, economic, social, and cultural) [59]. This makes it difficult to adopt policies to control corporate practices [60]. High availability of ‘chatarra’ results in its continued consumption by children. The main limitations for ‘chatarra’ consumption are economic constraints, while in other countries, junk food consumption by children has been associated with “socioeconomic adversity and family dysfunction that offspring distress” [61]. Third, PCs’ knowledge of product characteristics and health effects influences their navigation in the food swamp. They rank ‘chatarra’ according to their perceived outcomes on children’s growth and health based on a variety of sources that are not always aligned with nutritional science. The same situation was reported in Uruguay, where not all junk food was considered unhealthy and harmful [26]. Fourth, the incorporation of chatarra’ in children’s feeding practices may have been allowed by the cultural practice of ‘probaditas’ (small portions), a generalized strategy used to introduce babies to their first solid foods in Mexican culture [62,63]. ‘ Probaditas’ are aimed at preparing the stomach to get used to new foods gradually, preventing ‘empacho’ (indigestion) [31]. With UPPs, ‘probaditas’ are extended to a later age and are used to avoid ‘empachos’, and, nowadays, obesity and diabetes. The second cultural conception based on a previously documented principle in relation to school snacks is that as long as children’s nutritional requirements are met, giving them junk food does not matter [64]. Finally, just like in Uruguay [26], ‘chatarra’ is placed in the hedonic domain. According to the traditional Mexican motherhood model, in Mexico, PCs have to satisfy a craving, where the child’s food preference is an important driver of infant feeding choices [31]. In countries where child-feeding with junk food is a public health issue, it would be important to identify the cultural anchors that may have fostered its consumption among children. Fifth, children and the Mexican population, in general, have incorporated ‘chatarra’ in their day-to-day routine as documented [21,65] and have created positive meanings because its consumption is associated with affection, celebration, and conviviality, as documented in other countries [18,66]. The incorporation of junk food in family diets undoubtedly shapes children’s preferences and intake patterns [67]. In short, ‘chatarra,’ a type of UPP in Mexico and possibly in other countries, has penetrated daily life and culture since childhood through different processes. It is important to understand this cultural background to inform the design of public policy aimed at discouraging child-feeding with junk food. Nevertheless, the challenge is not only to avoid diseases associated with UPP consumption among children but to delay their initiation, considering their hyper-palatability and the subsequent conditioning to this type of flavors and food. This study demonstrates the presence of various social norms that drive child-feeding with UPPs, which have evolved in the context of massive supply and marketing. Finally, we identified spaces (e.g., groceries) that stimulate the consumption of products aimed at children (sweets, candies), probably because they are in full view. Changes in social norms towards UPPs are urgently needed to reverse their favorable image, as was performed with tobacco over many years. Finally, it seems to us that there is a need for greater control of the presentation of food and beverages aimed at children within the points of sale, which should not be visible to children. The main limitation of this research is that UPPs were not the only topic explored in this study, which made it impossible to go deeper into the topic. In addition, the study predates the implementation of the new nutritional warning labels, and it would be interesting to explore its possible effects on child-feeding with UPPs. However, the information generated is rich and can inform possible strategies to minimize UPPs in children’s feeding, such as awareness campaigns and regulation of marketing aimed at children in stores, among others. ## 5. Conclusions The influence of local knowledge, values, habits, and social norms is very relevant in shaping the decision of PCs about child-feeding and must be considered for the development of effective public policies and programs to prevent the consumption of UPPs among children. It is important to promote the replacement of UPPs with ‘real food’ with health protective effects [68] and separate them from the notion that they are a way of expressing affection and other good feelings. This effort should be global and a call for attention directed not only to parents, grandparents, and siblings but to all members of society, including teachers, health professionals, and decision-makers. In short, culture is not static and is constantly being built into interaction with others, with corporate commercial strategies, and/or with government efforts to promote health. For these reasons, countries should reinforce public policies that regulate the food environment in order to protect children and control UPP availability and access. 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--- title: 'White Matter Hyperintensities in Young Patients from a Neurological Outpatient Clinic: Prevalence, Risk Factors, and Correlation with Enlarged Perivascular Spaces' authors: - Qiaoqiao Zou - Mingliang Wang - Danni Zhang - Xiaoer Wei - Wenbin Li journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10054337 doi: 10.3390/jpm13030525 license: CC BY 4.0 --- # White Matter Hyperintensities in Young Patients from a Neurological Outpatient Clinic: Prevalence, Risk Factors, and Correlation with Enlarged Perivascular Spaces ## Abstract [1] Background: to investigate the prevalence of white matter hyperintensities (WMH), risk factors, and correlation with enlarged perivascular spaces (ePVS) among young patients (age, 16–45 years) in a neurological outpatient clinic. [ 2] Methods: a total of 887 young patients who underwent a head magnetic resonance imaging (MRI)examination between 1 June 2021, and 30 November 2021, were included in this study. Paraventricular WMH (PWMH), deep WMH (DWMH), ePVS in the centrum semiovale (CSO-ePVS), and basal ganglia (BG-ePVS) were rated. Logistic regression analysis was used to identify the best predictors for the presence of WMH and, for the association of the severity of ePVS with the presence of WMH. Goodman–*Kruskal gamma* test was used to assess the correlation between the severity of ePVS and WMH. [ 3] Results: the prevalence of WMH was $37.0\%$, with low severity. Age, hypertension ($p \leq 0.001$), headache ($$p \leq 0.031$$), syncope ($$p \leq 0.012$$), and sleep disturbance ($$p \leq 0.003$$) were associated with the presence of DWMH. Age, sex ($$p \leq 0.032$$), hypertension ($$p \leq 0.004$$) and sleep disturbance ($p \leq 0.001$) were associated with the presence of PWMH. The severity of CSO-ePVS was associated with the presence and the severities of DWMH. The severity of BG-ePVS was associated with the presence and severities of DWMH and PWMH. [ 4] Conclusions: the prevalence of WMH was $37\%$ and mild in young patients without specific causes. Older age, female, hypertension, headache, syncope, and sleep disturbance were associated with WMH. The severity of ePVS had an impact on the presence and severity of WMH in the corresponding brain regions. ## 1. Introduction White matter hyperintensities (WMH) are one of the manifestations of cerebral small vessel disease (CSVD), detected by magnetic resonance imaging (MRI) [1]. WMH were named after the high intensity observed on T2-weighted and T2 fluid-attenuated inversion recovery sequences (FLAIR) [2]. Several studies have reported that WMH are associated with stroke, dementia, and Alzheimer’s disease [3]. Therefore, understanding WMH prevalence, risk factors, and correlation with other CSVD is imperative. Previous studies have shown that, WMH are associated with increasing age and hypertension [4]. However, no correlation was established between sex, diabetes, hyperlipidemia, and enlarged perivascular spaces (ePVS). Some studies have reported a correlation between WMH and ePVS in middle-aged and elderly populations [2,5]. Studies of WMH in young clinical populations (≤45-years-old) are rare. Additionally, the literature on the symptomology of WMH, especially in the young without specific diseases is limited. Therefore, determining the correlation between neurological symptoms and WMH is significant. Thus, this retrospective study aimed to investigate WMH prevalence, risk factors, and correlation with ePVS in young patients without specific diseases from a neurological outpatient clinic for an in-depth understanding of WMH. ## 2.1. Study Population This retrospective study included a total of 887 outpatients (age range: 16–45 years; 389 male patients, 498 female patients) who underwent head MRI examinations between 1 June 2021, and 30 November 2021. This study did not include children (<16-years-old), as it might have shown a congenital rise in WMH [6]. The indications of MRI were determined by the neurologists and defined as follows: [1] an increase in the frequency and intensity of symptoms, such as dizziness, indicating secondary pathology; [2] any abnormal neurological finding, such as asymmetric or unilateral hearing or vision loss; [3] no neurological symptoms with brain examinations as part of the physical examination. The current study included patients with no history of a specific disease and a diagnosis of no specific disease based on head MRI results. Patients were excluded from this study if they had [1] specific causes of WMH and ePVS; [2] a history of traumatic brain injury, radiotherapy, presence of neoplasms, demyelinating diseases, or neurological diseases, or [3] suboptimal MRI because of artifacts (Figure 1). Most of the patients ($94.0\%$, $\frac{834}{887}$) had neurological symptoms, including 109 patients with unspecified symptoms, whose MRI requisition forms mentioned “suspected cerebrovascular disease”. The patients with no neurological symptoms ($6.0\%$, $\frac{53}{887}$) underwent head MRI examinations as a part of disease screening. Due to the retrospective nature of the study, the local institutional review board waived the informed consent requirement. ## 2.2. Data Collection The demographic and clinical data, including age, sex, symptoms, and history of hypertension, diabetes, and hyperlipidemia, were collected from all patients. Symptoms were determined according to the patient’s primary complaint. Symptoms found to be difficult to identify were defined as follows. Dizziness: a feeling of sway and instability while moving or seeing, most often done while standing, sitting, or lying down. Vertigo: a feeling (motion hallucination) characterized by episodes of the subjective illusion that one’s own body and/or outside objects are rotating or rolling in a certain direction despite being factually untrue. Light-headedness: a continuous feeling of light-headedness or mental disorientation. Somatic symptoms: any part of the body or organ could be affected by recurrent and changing somatic symptoms without any organic lesions being discovered by various medical examinations. Sleep disturbance: interfering with social functioning is the subjective feeling of insufficient daytime sleep quantity and/or quality. This may involve one or more of the following: [1] prolonged sleep latency (sleep onset requiring > 30 min); [2] sleep maintenance disorder (two or more nighttime awakenings or early morning awakenings); [3] decreased sleep quality (light sleep, excessive dreaming); [4] a shortening of the total amount of time spent sleeping (usually < 6 h), or [5] residual daytime effects (dizziness, mental fatigue, drowsiness, and fatigue, on the next morning). ## 2.3. Brain MRI All patients were scanned using the uniform 3T MRI scanning protocol (Magnetom Verio, Siemens Healthcare, Germany) that included axial T1-weighted, axial T2-weighted, axial FLAIR, axial DWI, and sagittal T1-weighted sequences. WMH were distinguished by isointensity on T1-weighted images and high signal intensity on T2-weighted and FLAIR images [7]. According to previous experience, WMH were assessed using the Fazekas rating scale [8]. DWMH and PWMH were selected for analysis based on previous experience. PWMH were graded as follows: 0 = absent; 1 = cap; 2 = smooth halo; 3 = irregular and extending into the subcortical white matter. DWMH were graded as follows: 0 = absent; 1 = punctate foci; 2 = early-confluent, or 3 = confluent. ePVS were defined as round, ovoid, or linear lesions with a CSF-like signal (hypointense on T1-weighted/FLAIR images and hyperintense on T2-weighted images) located along the penetrating arteries [7]. According to previous experience, ePVS were identified and graded at the level of centrum semiovale (CSO) and basal ganglia (BG). The level with the highest number of CSO-ePVS was selected and graded as follows: 0: no ePVS; 1: ≤10 ePVS; 2: 11–20 ePVS; 3: 21–40 ePVS; or 4: > 40 ePVS, or an uncountable number [9]. The level with the highest number of BG-ePVS was selected and graded as follows: [1] 1: <5 ePVS; [2] 2: 5–10 ePVS; and [3] 3: 10–20 ePVS; [4] 4: > 20 ePVS [9]. The numbers refer to ePVS on one side of the brain; for analysis, the side with the higher ePVS number was used when the numbers were not bilaterally consistent (Figure 2). Based on the median value, the CSO-ePVS degree was dichotomized into low (score: 0–1) and high (score: 2–4) levels. Additionally, based on the median value, the BG-ePVS degree was dichotomized into low (score: 1) and high (score: 2–4) levels. Neuroradiologist blinded to the clinical data evaluated the MRI results. With a 4-week gap between the first and second image assessments, a random sample of 100 subjects was used to analyze the interrater reliability of WMH and ePVS using *Cohen kappa* statistics. ## 2.4. Statistical Analysis All statistical tests were performed using SPSS version 26.0 for Microsoft Windows software. Numbers and percentages were used to represent categorical variables. Univariate analysis was performed using the chi-square test, and the variables with $p \leq 0.2$ were included in the logistic regression analysis. Logistic regression analysis was used to determine the best predictors for the presence of WMH and to analyze the association between the severity of ePVS and the presence of WMH. The correlation between the severities of ePVS and WMH was analyzed using Goodman–*Kruskal gamma* test after logistic regression showed that the severity of ePVS was significantly correlated with the presence of WMH. $p \leq 0.05$ was considered significant. ## 3.1. Demographic Characteristics of the Study Participants Table 1 summarizes the demographic and clinical findings of this study. A total of 887 patients, including 389 ($43.8\%$) males and 498 ($56.1\%$) females, were enrolled in this study. The median age of the group was 36 years (range, 16–45 years). The cohort comprised 24 ($2.7\%$) patients with diabetes, 72 ($8.1\%$) with hypertension and 25 ($2.8\%$) with hyperlipidemia. Most of the patients had symptoms ($94.0\%$), including 227 ($25.6\%$) with headache, 177 ($20.0\%$) with dizziness, 35 ($3.9\%$) with vertigo, 17 ($1.9\%$) with syncope, 27 ($3.0\%$) with light-headedness, 70 ($7.9\%$) with somatic symptoms, 31 ($3.5\%$) with hearing disturbance, 21 ($2.4\%$) with visual disturbance, 46 ($5.2\%$) with convulsions, 21 ($2.4\%$) with tremors, 53 ($6.0\%$) with sleep disturbance, and 109 ($12.3\%$) with unspecified symptoms. ## 3.2. Distribution and Severity of WMH The prevalence of WMH among the study participants was $37.0\%$. Of the individuals with WMH, $96.3\%$ ($\frac{316}{328}$) had DWMH and $20.0\%$ ($\frac{64}{328}$) had PWMH. Most of the patients in the DWMH group had a score of 1 ($79.0\%$, $\frac{259}{328}$), followed by 2 ($16.2\%$, $\frac{53}{328}$) and 3 ($1.2\%$, $\frac{4}{328}$). Similarly, most of the patients in the PWMH group had a score of 1 ($62.5\%$, $\frac{40}{64}$), followed by 2 ($25.0\%$, $\frac{16}{64}$) and 3 ($12.5\%$, $\frac{8}{64}$) (Table 2). ## 3.3. Risk Factors of WMH As shown in Table 3, chi-square testing indicated that age ($p \leq 0.001$), hypertension ($$p \leq 0.001$$), syncope ($$p \leq 0.044$$), and sleep disturbance ($$p \leq 0.003$$) were associated with DWMH. Also, age ($p \leq 0.001$), sex ($$p \leq 0.004$$), hypertension ($p \leq 0.001$), and sleep disturbance ($p \leq 0.001$) were associated with PWMH. Table 4 presents the results of logistic regression analysis for the predictors of DWMH and PWMH. Age, hypertension [odds ratio (OR) = 1.915, $95\%$ confidence interval (CI): 1.201–3.053], headache (OR = 1.450, $95\%$ CI: 1.035–2.030), syncope (OR = 3.647, $95\%$ CI: 1.329–10.004) and sleep disturbance (OR = 2.404, $95\%$ CI: 1.344–4.299) were associated with the presence of DWMH. Age, sex (OR = 0.555, $95\%$ CI: 0.324–0.950), hypertension (OR = 2.645, $95\%$ CI: 1.370–5.107) and sleep disturbance (OR = 3.860, $95\%$ CI: 1.855–8.032) were associated with the presence of PWMH. ## 3.4. Correlation between WMH and ePVS As shown in Table 5, binary logistic regression analysis revealed a significant association between the severity of CSO-ePVS and the presence of DWMH (Model 1: OR = 1.828, $95\%$ CI: 1.120–2.983, $$p \leq 0.016$$). This association was evident after controlling for confounding factors, including age, sex, vascular risk factors, and symptoms, as indicated by Model 2 (OR = 1.766, $95\%$ CI: 1.079–2.892, $$p \leq 0.024$$) and Model 3 (OR = 1.828, $95\%$ CI: 1.098–3.045, $$p \leq 0.020$$). The severity of BG-ePVS was associated with DWMH (Model 1: OR = 1.667, $95\%$ CI: 1.163–2.391, $$p \leq 0.005$$). After controlling for confounding factors, this association was evident as indicated by Model 2 (OR = 1.570, $95\%$ CI: 1.088–2.267, $$p \leq 0.016$$) and Model 3 (OR = 1.540, $95\%$ CI: 1.059–2.239, $$p \leq 0.024$$). As shown in Table 6, no significant association was found between the severity of CSO-ePVS and the presence of PWMH in either of the three models. The severity of BG-ePVS was associated with the presence of PWMH (Model 1: OR = 3.465, $95\%$ CI: 1.861–6.452, $p \leq 0.001$). This association was still evident after controlling for confounding factors, as indicated by Model 2 (OR = 3.007, $95\%$ CI: 1.616–5.595, $$p \leq 0.001$$) and Model 3 (OR = 3.427, $95\%$ CI: 1.802–6.520, $p \leq 0.001$). The Goodman–*Kruskal gamma* test was used to analyze the correlation between the severities of ePVS and WMH. The severities of CSO-ePVS were positively correlated with those of DWMH (gamma = 0.263, $p \leq 0.001$) (Table 7). The severities of BG-ePVS were positively correlated with the severities of DWMH (gamma = 0.289, $p \leq 0.001$) and PWMH (gamma = 0.579, $p \leq 0.001$). ## 4. Discussion In this retrospective study, we investigated WMH prevalence, risk factors, and correlation with ePVS in young clinical patients. The prevalence of WMH in our cohort was $37.0\%$, mostly mild. Age, hypertension, headache, syncope, and sleep disturbance were associated with the presence of DWMH while age, sex, hypertension, and sleep disturbance were associated with the presence of PWMH. The severities of CSO-ePVS were associated with the presence and severity of DWMH. The severity of BG-ePVS affected the presence and severity of DWMH and PWMH. ## 4.1. Effects of Demographic Factors on WMH The prevalence of WMH differs between populations, wherein WMH frequently observed in older populations. Seixas et al. demonstrated that the prevalence of WMH was $95.8\%$ among healthy individuals (age: 65.1 ± 8.2 years) [10]. Another study reported that the prevalence of WMH was $56\%$ in healthy individuals (age: 16–78 years) [11]. The overall prevalence of WMH in the current study was $37.0\%$. Nonetheless, we observed a low prevalence because the median age of the current study population was 36 years. Furthermore, the 26- to 35-year-old and 36- to 45-year-old age groups experienced high degrees of DWMH and PWMH compared to the 16- to 25-year-old group. In line with previous reports, the degree of WMH increased in an age-dependent manner. Therefore, in clinical practice, WMH should be under intensive focus in older patients. The majority of studies have concluded that sex was not correlated with WMH; while in a few studies, women presented WMH. In a cross-sectional study of middle-aged subjects, the female sex was significantly associated with DWMH [1]. The reason for the sex difference is yet to be clarified. In the Elderly at Risk (PROSPER) study, females had a high burden of WMH (both in DWMH and PWMH) [12]. This phenomenon could be attributed to decreased estrogen after menopause, allowing the brain to be more prone to hypoxia [13]. In the current study, we observed that young women had a high prevalence of PWMH indicating the correlation of female with PWMH is not related to menopause; nonetheless, a large sample size is required to confirm this finding. Furthermore, we demonstrated that hypertension has a significant impact on the presence of DWMH and PWMH which was consistent with previous findings that hypertension is a predictor of WMH [14]. A cross-sectional cohort study indicated that structural alternations of cerebral vessels induced by high blood pressure were correlated with WMH. Decreased cerebral vessel density, decreased tortuosity and increased radius of vessels may lead to hypoperfusion which is the pathogenesis of WMH [15]. In clinical work, when WMH is incidentally detected, the radiologists and neurologists should focus on the patient’s history of hypertension. ## 4.2. Influence of Clinical Symptoms on WMH In clinical practice, radiologists often analyze the head MRI of symptomatic patients without specific causes. Hence, we considered the effects of symptoms on WMH in this study and found that patients with, rather than without, headaches were more likely to have DWMH. Previous studies indicated that any history of severe headaches was associated with an increased risk of high volumes of total WMH, DWMH, and PWMH [16]. Thus, we hypothesized that our results are discordant due to younger age and lower severity, which might have caused headaches leading to DWMH, but not progressed to PWMH. Our study also showed that patients with syncope were likely to have DWMH. Thus, we speculated that syncope represents the poor tolerance of the brain to any changes in blood pressure indicating that vascular endothelial dysfunction leads to DWMH emergence. Therefore, in clinical practice, radiologists should be concerned about WMH when patients present headaches or dizziness. Accumulating evidence suggests that sleep is associated with the presence of WMH. Shanshan et al. demonstrated that sleeping disorders are associated with a high burden of WMH among patients with chronic insomnia (median age = 50 years) [17]. Kristine et al. found that short sleep duration is associated with WMH in middle-aged adults [18]. Recent studies have shown that the neurotoxic metabolites are cleared during sleep, and shortened sleep duration could influence this process [19]. Consequently, accumulated neurotoxic metabolites (for example, tau protein) might form WMH [20]. The current study showed that sleep disturbance is associated with DWMH and PWMH. Therefore, sleep disorders not only affected WMH presence in the middle-aged and older people but also in the young individuals. ## 4.3. Correlation between WMH and ePVS Almost all studies have reported that ePVS is associated with WMH. Herein, we found that the severity of BG-ePVS was associated with the presence of DWMH and PWMH in contrast with CSO-ePVS only related to the presence of DWMH. The severity of CSO-ePVS was associated with that of DWMH, while the severity of BG-ePVS was associated with those of both DWMH and PWMH. However, the underlying mechanism for the difference in the regional association between WMH and ePVS is yet unclear. Some studies suggested that BG-ePVS was caused mainly by hypertensive arteriopathy, with pathogenesis similar to WMH, while CSO-ePVS was due to cerebral amyloid angiopathy [5]. However, this phenomenon did not explicate our results. Huang et al. proposed the topological connections between DWMH and CSO-ePVS [2]. Most punctuate (<3 mm) DWMH was connected with one ePVS tube, and a large (>5 mm) DWMH could have several thick ePVS connections. This association is apparent in patients with mild WMH. In our study, this correlation was manifested due to the fact that the study population was young, and the vast majority of patients presented a mild feature. Nevertheless, the current study has several limitations. First, we used visual rating scales to judge the severities of WMH and ePVS. Due to very little ePVS, coexisting extensive WMH, or the presence of lacunes, the reliability of this evaluation method is reduced [21]. Some special rating scales or three-dimensional automated grading scales can be used to improve the detection of CSVD [21,22]. Second, the risk factors, such as hypertension, diabetes, and hyperlipidemia, were included, while some confounding variables, such as smoking and obesity, were not included in the analysis model. 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--- title: Beneficial Effects of Hordenine on a Model of Ulcerative Colitis authors: - Zhengguang Xu - Qilian Zhang - Ce Ding - Feifei Wen - Fang Sun - Yanzhan Liu - Chunxue Tao - Jing Yao journal: Molecules year: 2023 pmcid: PMC10054341 doi: 10.3390/molecules28062834 license: CC BY 4.0 --- # Beneficial Effects of Hordenine on a Model of Ulcerative Colitis ## Abstract Hordenine, a phenethylamine alkaloid, is found in a variety of plants and exhibits a broad array of biological activities and pharmacological properties, including anti-inflammatory and anti-fibrotic effects. However, the efficacy and underlying mechanisms of hordenine in treating ulcerative colitis (UC) remain unclear. To address this, we examined the therapeutic effects of hordenine on dextran sodium sulphate (DSS)-induced UC by comparing disease activity index (DAI), colon length, secretion of inflammatory factors, and degree of colonic histological lesions across diseased mice that were and were not treated with hordenine. We found that hordenine significantly reduced DAI and levels of pro-inflammatory factors, including interleukin (IL)-6, IL-1β, and tumor necrosis factor alpha (TNF-α), and also alleviated colon tissue oedema, colonic lesions, inflammatory cells infiltration and decreased the number of goblet cells. Moreover, in vitro experiments showed that hordenine protected intestinal epithelial barrier function by increasing the expression of tight junction proteins including ZO-1 and occludin, while also promoting the healing of intestinal mucosa. Using immunohistochemistry and western blotting, we demonstrated that hordenine reduced the expression of sphingosine kinase 1 (SPHK1), sphingosine-1-phosphate receptor 1 (S1PR1), and ras-related C3 botulinum toxin substrate 1 (Rac1), and it inhibited the expression of phosphorylated signal transducer and activator of transcription 3 (p-STAT3) in colon tissues. Thus, hordenine appears to be effective in UC treatment owing to pharmacological mechanisms that favor mucosal healing and the inhibition of SPHK-1/S1PR1/STAT3 signaling. ## 1. Introduction Ulcerative colitis (UC) is a multifactorial chronic inflammatory bowel disease (IBD), which mainly affects the colon and rectum. Clinical manifestations in patients include abdominal pain, diarrhea, and bloody stool [1,2]. However, the etiology and pathogenesis of UC remain somewhat unclear and may be related to genetic factors, environmental factors, infections, dysbiosis, and immune factors [2,3,4,5,6,7]. At present, drug treatments for UC include 5-aminosalicylic acid (5-ASA), glucocorticoids, immunosuppressants, and biological agents. Unfortunately, the effects of most of these drugs are limited in terms of therapeutic efficacy and safety, resulting in various adverse reactions [3,8,9]. Therefore, safer and more effective drugs for UC treatment are urgently required. The sphingolipid pathway is a key component of many signal transduction pathways and regulates biological activities such as cell proliferation, cell migration, and inflammation [10,11]. Sphingomiglide kinase-1 (SPHK1) is an intracellular lipase that acts as a signaling molecule in the sphingolipid signaling pathway, converting sphingosine into Sphingosine-1-phosphate (S1P) [12,13,14]. S1P is a pleiotropic bioactive sphingolipid metabolite that regulates various cellular processes by binding to its own receptors [15,16,17]. Studies have shown that S1P is closely related to the occurrence and development of UC [17,18]. Sphingosine-1-phosphate receptor (S1PR1), also known as endothelial differentiation gene 1 (EDG1), is a G-protein-coupled receptor that mediates the bioactivity of S1P to promote cell proliferation and survival [19]. The activation of the SphK1-S1P-S1PR1 axis is crucial for various cellular signaling cascades and several pathological processes [20]. Signal transducer and activator of transcription 3 (STAT3) mediates cytokine and growth factor signals in a range of tissues and translocates to the nucleus after phosphorylation, where it participates in the regulation of cell proliferation, migration, differentiation, and transcription of inflammatory target genes [21,22]. Numerous studies have demonstrated that epithelial STAT3 is essential for maintaining gut barrier integrity [23,24], whereas S1P promotes the activation of STAT3, thus contributing to the development of colitis-related cancers [17]. Hordenine, chemically known as 4-(2-Dimethylaminoethyl) phenol, is an alkaloid extracted from a wide range of plants, including cacti and the seedlings of cereals (such as barley, proso millet, and sorghum), as well as some algae and fungi. It exhibits antioxidant, anti-inflammatory, antibacterial, and anti-tumor activities [25,26,27,28,29,30]. The chemical formula for hordenine is given in Figure 1A. Studies indicate that hordenine can inhibit neuro-inflammation and reduce nerve pain [27], exert anti-inflammatory effects in diabetic nephropathy [30], and prevent lipopolysaccharide-induced acute lung injury [25,27]. In addition, hordenine displays antibacterial properties, as well as antiviral properties against herpes virus and SARS-CoV-2, and prevents inflammation caused by both viruses at the site of infection [31,32]. However, the potential alleviating effects of hordenine on experimentally-induced UC and the underlying mechanisms driving these effects remain unclear. Here, we addressed this gap using a dextran sodium sulphate (DSS)-induced UC model and in vitro experiments to provide a theoretical basis for the use of hordenine in the treatment of UC. ## 2.1. Ethics Statement All animal experiments were approved by the Institutional Animal Care and Use Committee of Jining Medical University (2021-DW-ZR-019). ## 2.2. Chemicals and Reagents Hordenine (high-performance liquid chromatography-grade ≥$95\%$) and 5-ASA (purity > $99\%$) were purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). DSS (molecular weight 36~50 kDa) was purchased from MP Biomedicals (Irvine, CA, USA). Fecal occult blood qualitative detection kit purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Mouse interleukin (IL)-6, IL-1β, and tumor necrosis factor-alpha (TNF-α) enzyme-linked immunosorbent assay (ELISA) kits were purchased from Biolegend (San Diego, CA, USA). Hematoxylin and eosin (H&E) were purchased from Solarbio Science & Technology Co., Ltd. (Beijing, China). Periodic acid-Schiff (PAS) staining solution was purchased from Wuhan Servicebio technology Co., Ltd. (Wuhan, China). Universal SP Kit was purchased from ZSGB-BIO Co., Ltd. (Beijing, China). Primary antibodies against SPHK1, S1PR1/EDG1, ras-related C3 botulinum toxin substrate 1 (Rac1), and p-STAT3 (phospho-S727) were purchased from Abcam (Cambridge, MA, USA). Antibodies against IL-6, IL-1β, and TNF-α were purchased from Bioworld Technology (St. Louis Park, MN, USA). Antibodies against β-actin and zonula occludens 1 (ZO-1) were purchased from Affinity Biosciences (Cincinnati, OH, USA). Antibodies against occludin was purchased from Proteintech Group (Wuhan, China). Anti-mouse and anti-rabbit secondary antibodies were obtained from eBioscience (San Diego, CA, USA). Enhanced chemiluminescent (ECL) substrate was purchased from Beijing Labgic Technology Co., Ltd. (Beijing, China). Transwell inserts (pore size of 0.4 µm) were purchased from Corning Inc. (Kennebunk, ME, USA). ## 2.3. Cell Culture Mouse colonic epithelial cells (MCECs) were cultured in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with $10\%$ fetal bovine serum (FBS), 100 U/mL penicillin, and 100 μg/mL streptomycin in an incubator with $5\%$ CO2. ## 2.4. Cell Counting Kit-8 (CCK-8) Experiment MCEC cells at the logarithmic growth stage were evenly distributed in 96-well plates at a growth density of $30\%$, and after 24 h of incubation, a blank group (no cells were inoculated), a control group, and various concentrations of hordenine administration groups (500, 250, 125, 62.5, 31,25, and 15.625 μM) were set up, with six replicate wells in each group. Each well was given the medication for 24 h before the addition of 10 μL CCK-8 reagent and an additional hour of incubation. The aforementioned test was carried out three times [33]. It was found that 500, 250, 125, 62.5, 31.25, and 15.625 μM of hordenine had no significant effect on the survival rate of MCEC cells for 24 h. Therefore, 500 μM was chosen as the hordenine administration condition. ## 2.5. DSS-Induced Models and Hordenine Treatment Female BALB/c mice (35~40 days, weighing 18~22 g) were obtained from Jinan Pengyue Experimental Animal Breeding Co., Ltd. (Jinan, China). Animals had access to food and water ad libitum and were maintained on a 12 h/12 h light/dark cycle at 21 ± 2 °C with a relative humidity of 45 ± $10\%$. All mice were then randomly divided into six groups ($$n = 10$$/group): untreated control, DSS model, DSS+5-ASA 40 mg/kg, and DSS+hordenine 50 mg/kg, DSS+hordenine 25 mg/kg, DSS+hordenine 12.5 mg/kg (Figure 1B). Except for the control group, mice were given $4\%$ (w/v) DSS solution for 7 days before being given regular water for the next 5 days [33]. From day 1 to day 12, mice in the treatment groups were administered 5-ASA or hordenine daily by gavage, while mice in control and DSS model groups were administered normal saline. All mice were sacrificed on day 13. ## 2.6. Assessment of Disease Activity Index (DAI) Score From the first day of the experiment, mice were observed daily for their mental status and hair condition. Their body weight, fecal characteristics and fecal occult blood were recorded and DAI scores were calculated [17]. Specific standards of DAI score are shown in Table 1. ## 2.7. Collection of the Main Organs and Colon Tissues and Preparation of Serum Samples The mice were sacrificed on 13th day, and the main organs including heart, liver, spleen, lung and kidney, were collected and weighed, and the colon and rectum were separated from the small intestine at the proximal ileocecal end, and from the anus at the distal end. This section of colorectal was extracted and straightened (without stretching) and its length was measured with a ruler, and follow-up tests were performed [34]. The colons were dissected longitudinally and washed with saline, and fixed with $10\%$ neutral formalin for H&E staining, PAS staining and immunohistochemical (IHC) staining. The remaining colon tissue was stored at −80 °C for Western blot analysis. ## 2.8. H&E Stain Paraffin-embedded colonic tissue blocks were cut into 4 μm-thick sections for H&E staining [35]. The histological change scoring criteria are shown in Table 2. ## 2.9. PAS Stain PAS staining is used to display glycogen and polysaccharide substances, mostly used for goblet cell staining. The paraffin tissue section was dewaxed and hydrated, and then stained with PAS staining solution B, A and C according to the instructions, and finally dehydrated and sealed, and the image was collected and analyzed under the microscope. The experimental method is consistent with the literature report [36]. ## 2.10. Measurement of Cytokines The levels of IL-6, IL-1β, and TNF-α in the supernatant of colon tissue homogenate were determined by ELISA according the instruction of test kits [37]. ## 2.11. IHC Colon segments were taken and fixed in $4\%$ paraformaldehyde. Then, 4 μm-thick paraffin-embedded colon sections were prepared and incubated in $0.3\%$ hydrogen peroxide methanol for 20 min at room temperature to inhibit endogenous peroxidase activity. For antigen extraction, sections were treated with citrate buffer (pH 6.0) and heated three times in a microwave oven for 5 min each. Sections were then closed with $5\%$ bovine serum albumin (BSA) for 30 min at room temperature, followed by overnight incubation at 4 °C with the IL-6, TNF-α, SPHK1, S1PR1, Rac1 and p-STAT3 primary antibody. The next day, the sections were incubated with their respective pairs with secondary antibodies at room temperature, and the remaining manipulations were completed according to the Universal SP kit, and finally observed and photographed under a microscope [38,39]. ## 2.12. Western Blot Assay The BCA assay reagent was used to measure the protein concentration after removing the whole protein from the colon tissue of the mice in each group. After electrophoresizing the samples from each group in polyacrylamide gels of $8\%$, $10\%$, and $15\%$, the protein was then transferred to a polyvinylidene fluoride membrane. The membrane was blocked with $5\%$ skim milk powder for 2 h at room temperature and then incubated with primary antibody overnight at 4 °C. After that, the membranes were exposed to secondary antibodies for 1 h at room temperature. As directed by the ECL western blotting experiment, membrane imaging was carried out. The protein expression of IL-6, TNF-α, IL-1β, SPHK1, S1PR1, Rac1 and p-STAT3 in colon tissues, and ZO-1 and occludin in MCECs were examined using the previously described method [38,39]. ## 2.13. Co-Culture and Scratch Assay Colitis model mice were induced with $4\%$ DSS solution for 5 days and sacrificed on the 6th day. Peritoneal macrophages (Mφs) were collected and cultured in DMEM. MCECs were plated in 6-well culture plates and incubated at 37 °C in a $5\%$ CO2 incubator. Mφs were added to the upper chamber of a Transwell insert (pore size of 0.4 μm) on the cavity, co-cultured with MCECs in 6-well culture plate, and treated with hordenine (500 μM). Following the above treatments, monolayers of the MCECs were scratched and observed at 0 and 24 h. The percentage of coverage was calculated. ## 2.14. Statistical Analysis Statistical analysis was performed using Prism 5 software (GraphPad Software, La Jolla, CA, USA). All data were presented as the mean ± SD. The significant difference between groups were analyzed by Student’s t-test (for normal distribution), p values of less than 0.05 were considered significant for all data. ## 3.1. Hordenine Ameliorates DSS-Induced UC in Mice Mice in the DSS group displayed a significant decrease in body weight compared to those in the control group, but this DSS-induced weight loss was alleviated by treatment with hordenine (Figure 1C). Average DAI scores were higher among mice in the DSS group compared to those in the control group (Figure 1D). The drugs did not affect the weight of the heart, spleen, lungs, kidneys, and liver weight. The colon lengths of mice in the model group were significantly shorter than those of mice in the control group, and were significantly longer among mice in the drug administration group (Figure 1E,F). Our examination of colon injury and inflammatory cell infiltration using HE staining. These results revealed colonic necrosis and ulceration, disappearance of mucosa and glands, hyperplasia of connective tissue, granulocyte infiltration, and infiltration of a large number of inflammatory cells in mice in the DSS group, all of which were substantially improved by treatment with hordenine (Figure 1G,H). In addition, PAS staining revealed that compared with the normal group mice, the goblet cells of the model group mice were irregular in arrangement, incomplete in shape, significantly reduced in number and uneven in size, some cells were vacuolate, and the contents of glycogen and other mucus substances were significantly reduced. Compared with the model group, the goblet cells in the hordenine group were more regular in arrangement, more complete in shape, and significantly increased in number, and contained more mucus substances such as glycogen, and showed a certain dose dependence (Figure 1I,J). ## 3.2. Hordenine Inhibited the Secretion and the Expression of Inflammatory Factors Induced by DSS As shown in Figure 2A–C, hordenine inhibited DSS-induced production of interleukin (IL)-6, IL-1β, and tumor necrosis factor alpha (TNF-α) in the supernatant of colon tissue homogenate. The results of immunohistochemistry (IHC) and western blotting showed that hordenine inhibited the expression of IL-6, IL-1β, and TNF-α proteins in colonic tissues relative to those in DSS-treated mice that did not receive hordenine (Figure 2D–H). ## 3.3. Hordenine Inhibits S1P/S1PR1/STAT3 Signaling Pathway and Expression of Ras-Related C3 Botulinum Toxin Substrate 1 (Rac1) in Colon Tissues As shown in Figure 3A–E, hordenine inhibited DSS-induced increases in the expression of SPHK1 and S1PR1 and the phosphorylation of STAT3 in colon tissues. IHC and western blotting results showed that trends in the expression of Rac1 were consistent with those of SPHK1, S1PR1, and STAT3 (Figure 3A,B,F). ## 3.4. Hordenine Contributes to Mucosal Healing To mimic the inflammatory microenvironment of colon epithelial cells, we established a co-culture of peritoneal macrophages (Mφs) and mouse colonic epithelial cells (MCECs) (Figure 4A). The effects of hordenine on cell migration and wound healing were evaluated using a cell scratch assay. The results indicated that the migration capacity of MCECs decreased in the presence of Mφs from DSS-treated mice, while hordenine-treated Mφs promoted MCECs migration (Figure 4B,C). Western blotting showed that hordenine treatment also significantly increased occludin and ZO-1 expression (Figure 4D–F). ## 4. Discussion Alkaloid is one of the effective active ingredients in natural Chinese herbal medicine, and is a highly diversified heterocyclic compound [40]. Plant alkaloid is a molecule with anti-inflammatory activity of traditional Chinese medicine, which can inhibit the expression of cytokines, lipid mediators, histamine, enzymes involved in inflammatory reaction and various pro-inflammatory factors [41]. Based on this, alkaloids are important material repositories for drug research and development. As an alkaloid, hordenine is also a promising candidate for the treatment of inflammatory diseases [42]. The DSS-induced UC model has the advantages of being very similar to human clinical symptoms, with a simple operation and high repeatability, and has been commonly used in colitis research [43]. In the present study, we used a DSS-induced UC model to explore the therapeutic effects and mechanisms of hordenine in the treatment of UC. Mice treated with $4\%$ DSS displayed a number of clinical symptoms, including weight loss, diarrhea, and blood in the stool; hordenine treatment substantially improved these symptoms. Histopathological analysis revealed that hordenine markedly improved DSS-induced mucosal necrosis and inflammatory cell infiltration. In addition, the typical tissue changes in the UC mouse model constructed by DSS also include the reduction of goblet cell damage [43]. Our results show that hordenine can significantly inhibit the growth of goblet cells. Inflammatory cytokines play an important role in the occurrence and development of UC [44], and our results showed that hordenine reversed the DSS-induced increase in the levels of IL-6, IL-1β, and TNF-α, suggesting that hordenine inhibited the typical inflammatory response associated with UC. Mφs are antigen-presenting cells that connect the innate and adaptive immune systems and have high plasticity [45]. The M1 phenotype of macrophages can up-regulate inflammatory factors and chemokines, promote the production of reactive oxygen species and reactive nitrogen, while the M2 phenotype can inhibit inflammatory reactions and promote wound healing [46]. Inhibiting the polarization of M1 macrophages contributes to reducing DSS-induced colitis damage [47]. In addition, Mφs can drive the immune function of intestinal microenvironment [48]. Changes in the inflammatory microenvironment of the colon epithelium may affect the integrity of the intestinal barrier [44]. To investigate the effects of hordenine on ulcer healing ability in UC mice, Mφs were isolated from UC mice and co-cultured with MCECs in vitro to simulate the inflammatory environment of intestinal epithelial cells. The DSS+Mφs+hordenine group was treated with hordenine (500 µM) on the basis of the DSS+Mφs group, and a blank control group of MCECs was not co-cultured with Mφs. The results of the scratch experiments showed that Mφs isolated from UC mice inhibited the migration of MCEC, whereas hordenine promoted it. Therefore, we infer that hordenine may inhibit the polarization of M1 macrophages or promote the polarization of M2 macrophages to reduce the inflammatory mediators in mice induced by DSS and promote mucosal healing. The intestinal barrier is a physical barrier formed by various intestinal epithelial cells and cell tight junction complexes, among which are important transmembrane proteins involved in tight junction formation, including occludin and ZO-1 [49]. Studies have shown that the up-regulation of the expression of occludin and ZO-1 can reduce the inflammatory response, improve the tight junctions of the intestinal epithelium, and repair and maintain the intestinal epithelial barrier function [50]. Treatment with hordenine upregulated the expression of occludin and ZO-1, indicating that hordenine can promote colon healing in UC mice. In conclusion, these experiments suggest that hordenine exerts therapeutic effects in UC colon tissue by improving the intestinal barrier via regulation of the expression of tight junction proteins. SPHK1 expression is typically low in normal colon tissue. When inflammation occurs, SPHK1 is activated, and its expression is up-regulated to produce inflammation, which also increases in the colon of UC mice [51,52]. S1P plays a key role in inflammatory diseases, especially IBD [53]. STAT3 affects various cytokines and growth factors including IL-6, interferon, epidermal growth factor through phosphorylation [22,54]. Increased expression of p-STAT3 is directly linked to inflammation and the formation of histological lesions. In addition, phosphorylated STAT3 can activate the S1P-SPHK1-S1PR1 signaling axis, which in turn maintains the activated state of STAT3 [55,56]. This process plays an important role in the development of intestinal inflammation [57,58]. Rac1, a member of the Rho family of small GTPases, which are ubiquitously expressed signaling sensors [59,60]. All three receptors of S1P, S1PR1, S1PR2 and S1PR3 can influence the expression of Rac1 [11]. Rac1 activation is necessary for proliferation, migration, and other processes in S1P-mediated cells [50,51,59,60]. Studies have confirmed that Rac1 induces STAT3 activation through the expression and activity of IL-6 to promote inflammation [61]. Our results showed that the expression levels of S1PR1, SPHK1, and their downstream protein p-STAT3 were notably elevated in DSS-treated mice, but were markedly reduced after the administration of hordenine. The expression of Rac1 exhibited a similar trend, suggesting that Rac1 may play a key role in this pathway. As such, we suggest that hordenine exerts therapeutic effects in UC colon tissue through inhibition of the S1P/S1PR1/STAT3 pathway, with its mechanism of action detailed in Figure 5. However, the role of Rac1 in the S1P/S1PR1/STAT3 pathway is not yet comprehensively understood. Future studies should use siRNA and Rac1 overexpression plasmids to explore whether Rac1 plays a bridging role in this pathway. The question of whether hordenine exerts its therapeutic effect on UC by altering the subtype of macrophages also warrants further investigation. ## 5. Conclusions Our results showed that the administration of hordenine alleviated lesions in DSS-induced UC mice by reducing the expression of pro-inflammatory cytokines and regulating the S1P/S1PR1/STAT3 signaling pathway. Hordenine also promoted the healing of colonic ulcers by regulating the expression of tight junction proteins, including ZO-1 and occludin. The results of this study suggest that hordenine is a promising drug for the treatment of UC. ## References 1. 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--- title: Association of Glycosylation-Related Genes with Different Patterns of Immune Profiles and Prognosis in Cervical Cancer authors: - Wanling Jing - Runjie Zhang - Xinyi Chen - Xuemei Zhang - Jin Qiu journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10054345 doi: 10.3390/jpm13030529 license: CC BY 4.0 --- # Association of Glycosylation-Related Genes with Different Patterns of Immune Profiles and Prognosis in Cervical Cancer ## Abstract [1] Background: Although the application of modern diagnostic tests and vaccination against human papillomavirus has markedly reduced the incidence and mortality of early cervical cancer, advanced cervical cancer still has a high death rate worldwide. Glycosylation is closely associated with tumor invasion, metabolism, and the immune response. This study explored the relationship among glycosylation-related genes, the immune microenvironment, and the prognosis of cervical cancer. [ 2] Methods and results: Clinical information and glycosylation-related genes of cervical cancer patients were downloaded from the TCGA database and the Molecular Signatures Database. Patients in the training cohort were split into two subgroups using consensus clustering. A better prognosis was observed to be associated with a high immune score, level, and status using ESTIMATE, CIBERSORT, and ssGSEA analyses. The differentially expressed genes were revealed to be enriched in proteoglycans in cancer and the cytokine–cytokine receptor interaction, as well as in the PI3K/AKT and the Hippo signaling pathways according to functional analyses, including GO, KEGG, and PPI. The prognostic risk model generated using the univariate Cox regression analysis, LASSO algorithm and multivariate Cox regression analyses, and prognostic nomogram successfully predicted the survival and prognosis of cervical cancer patients. [ 3] Conclusions: Glycosylation-related genes are correlated with the immune microenvironment of cervical cancer and show promising clinical prediction value. ## 1. Introduction Globally, cervical cancer (CC) is one of the most frequent cancers amongst women [1]. Although advancements in screening techniques and treatment measures have greatly reduced the CC incidence and mortality in developed nations, CC remains a severe problem in developing countries [2]. With the continuous improvement in therapeutic measures, early CC is halted by surgery, achieving satisfactory results. However, metastatic CC is difficult to cure and often displays a poor prognosis owing to individual variability among patients. Recurrence and metastasis are pivotal hurdles in determining the survival and prognosis of CC, and there is no effective molecular marker to predict the prognosis. Thus, it is crucial to identify new biomarkers for the diagnosis and prognosis of CC. The tumor immune microenvironment (TIME), including tumor cells, immune cells, and cytokines [3], is now recognized as a key factor in the development of cancer and chemo-resistance and has a significant impact on the expression of genes in cancer tissues [4]. Tumor and immune cells interact in the TIME as an essential process, shaping the progression of various cancer types, including CC [5]. For the precise therapeutic improvement of CC, it is vitally necessary to have a thorough understanding of the connection between the TIME and prognosis and to investigate innovative treatment approaches. Studies have reported that some miRNAs and lncRNAs play a role in predicting CC. One previous study constructed a two-miRNA risk score model with predictive potential, providing new clues for the evaluation and treatment of CC [6]. In CC tissues and cell lines, miR-99a-5p expression was reported to be downregulated [7]. A study innovatively identified and validated four immune-related lncRNA signatures as predictors of CC [8]. In contrast to normal tissues, CC had significantly higher levels of EphA7 promoter methylation. EphA7 hypermethylation is therefore a promising signature to detect and screen CC [9]. Although these biomarkers can predict the survival and prognosis of patients with CC to some extent, they do not completely solve the problem. Glycosylation is an important aspect among various post-translational modifications of proteins [10]. Glycosyltransferases and glycosidases regulate the majority of protein glycosylation in eukaryotes through the secretory pathway. A glycosidic link is created when the carbohydrates are transported to the protein’s amino acid residue [11]. Changes in glycosylation have been implicated to be intimately correlated with tumor cell invasion, metabolism, and immunity. A recent study reported that shortened O-Glycans could increase proliferation, impede differentiation, and cause invasive behavior by impairing cell–cell adhesion in adenocarcinomas [12]. Imbalanced glycosylation can influence the immune system in recognizing tumor cells and can modify glycan-binding receptors to induce an immunosuppressive response [13]. One of the primary characteristics of tumor cells is the glycosylation of the glycoproteins and glycolipids found on the cell surface. Tumor cells express glycosylation differently from the way in which normal cells do. As a result of the large number of different types of glycosylation-dependent lectin receptors expressed by immune cells, these cells are able to detect changes in glycosylation in the environment, which may induce immunosuppression [13]. Tumor cells can also camouflage themselves by expressing host-derived glycosylation and affect the expression of antigen-presenting cells, M2 macrophages, T cells, and NK cells, thereby promoting immune escape [14]. Carbohydrate Lewis antigens can attach to carcinoembryonic antigens expressed in colon cancer cells and combine with C-type lectin expressed in macrophages and immature dendritic cells to induce innate immune suppression [15,16]. The aggregation of Treg cells, the minimal infiltration of effector T cells, and the activity of NK cells are all strongly correlated with the sialylated structure of melanoma cells and the progression of the tumor in vivo [17]. The glycosylation of tumor cells usually occurs in the early stage of tumor development. In the prophase lesions of different types of tumors, some tumor-related glycosylation expression has been observed [18]. Therefore, the importance of glycosylation in cancer warrants further investigations to unmask the novel aspects of this hallmark. In CC, the use of virus-induced glycosylated peptides for vaccines was originally reported more than four decades ago [19]. Recent research has discovered how glycosylation contributes to the development of CC and underscores the prospects of viable methods in distinguishing individual differences [20]. O-linked GlcNAcylation is used to influence major metabolic pathways [21]. Interestingly, elevated O-GlcNAcylation in CC was linked to increased cell proliferation and decreased cellular aging. Therefore, reducing O-GlcNAcylation could prevent the phenotypic transformation of HPV-18-transformed HeLa CC cells after treatment with appropriate inhibitors [22]. Glycans play key roles in the pathological processes of tumorigenesis and advancement. There is reduced expression of fucosylation in CC cytoplasmic proteins compared to normal tissues [23]. During carcinogenesis, dysregulated glycosyltransferases synthesize aberrant glycosylation structures, supporting tumor progression. Previous studies have demonstrated that differentially expressed genes (DEGs) of glycosyltransferase can predict the overall survival (OS) of pancreatic ductal adenocarcinoma patients and can be identified as prognostic markers [24]. Other studies have revealed that the expression of genes involved in glycosylation is very different in breast cancer compared to normal breast tissue [25]. Glycosylation-related genes have exhibited large expression variations between breast cancer subtypes, which may be associated with patient prognosis. However, the role of glycosylation-related DEGs in CC has remained poorly understood. In this study, to investigate whether glycosylation-related genes are associated with differences in the TIME and prognosis of patients with CC, we thoroughly analyzed glycosylation-related DEGs in CC. A signature was developed to assess the prognostic value of glycosylation-related genes in CC. Our work is anticipated to offer new insights into the targeted therapeutic approach for CC. ## 2.1. Datasets and Samples Glycosylation-related genes and CC samples were acquired from the Gene Set Enrichment Analysis (GSEA) Molecular Signatures Database and TCGA-GDC database. The following were the inclusion requirements: (a) samples with a CC diagnosis; (b) samples with a gene expression matrix and mapped clinical data; and (c) samples with all relevant clinical data, including age, FIGO stage, risk, and histopathological grade (Table 1). Samples without follow-up information were disqualified. Patients obtained from the TCGA-GDC database were randomly classified into training and testing cohorts for identification and validation. ## 2.2. Identification of Molecular Subgroups According to the expression matrix of glycosylation-related genes, consensus clustering was carried out using the R program “Consensus Cluster Plus” to divide patients into two clusters [26]. Survival analysis between the two subgroups was also performed to assess the correlations among their survival rates. ## 2.3. Immune Analyses Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis illustrates major signaling pathways [27]. The Estimation of STromal and Immune cells in MAlignant Tumor tissues using *Expression data* (ESTIMATE) algorithm was used to determine the stromal score, immune score, and estimation score [28]. To quantify the relative proportions of different types of immune cells in the tumor sample, CIBERSORT was applied for analysis [29]. The enrichment of immune-infiltrating cells and the expression of immune-related functions were analyzed via single-sample gene set enrichment analysis (ssGSEA) [30]. Statistical significance was defined as a p value and/or FDR ≤ 0.05. ## 2.4. Functional Analyses DEGs were screened using the package of R language (|log2FC| > 0.585 and adj. p Val < 0.05). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to analyze the enriched pathways [31]. GO analysis determined biological processes, cellular components, and molecular function. Protein–Protein Interaction (PPI) network analysis was subsequently utilized to implement hub gene analysis according to the number of nodes [32]. ## 2.5. Establishment and Validation of the Risk Model The size of prognostic genes previously filtrated was narrowed down using univariate Cox regression analysis [33] and least absolute shrinkage and selection operator (LASSO) analysis [34]. The minimum lambda was regarded as the optimal value. Multivariate Cox regression [35] analysis determined several significant genes in establishing a risk model. The risk score was calculated using the following formula: Risk score = ΣExpn × βn, where Expn represents the expression value of each gene and βn represents the coefficient of the gene. Next, groups with high and low risk were separated. Survival analysis was performed using the Kaplan–Meier approach, and the predictive validity of the risk model was assessed using the receiver operating characteristic (ROC) [34]. A nomogram was constructed according to the status, age, FIGO stage, risk, and histopathological grade of CC patients. ## 3.1. Identification of the Two Subtypes with Different OS In total, 246 glycosylation-related genes were acquired. A total of 146 and 145 clinical samples were randomly classified into the training and testing cohorts, respectively. The Consensus Cluster Plus R package was used to cluster the CC patients in the training cohort. At $K = 2$, the optimal cluster stability was determined (Figure 1A–C). In total, clusters 1 and 2 each contained 180 patients and 126 patients, respectively. Cluster 1 showed better OS ($$p \leq 0.0003234$$; Figure 1D). These results indicated that CC patients could be classified into two subtypes with different OS. ## 3.2. Glycosylation of Proteins Can Affect Immune Function in the Two Molecular Subtypes KEGG enrichment analysis showed that more pathways related to the glycosylation process were found in cluster 2 compared to cluster 1; accordingly, more immune-related pathways were found in subgroup 1 (Figure 2A). Thus, genes involved in glycosylation modification also act in the immune system. To investigate the association of glycosylation with the immune status, immune analyses were performed to explore differences in immunity between the two subgroups. According to the results of the ESTIMATE algorithm, CC patients in cluster 1 had significantly higher immune and ESTIMATE scores, and no appreciable differences were found in the stromal scores of patients in the two clusters (Figure 2B). In addition, the numbers of CD8 T cells, activated memory CD4 T cells, monocytes, M1 macrophages, resting dendritic cells, and resting mast cells were significantly higher in cluster 1 than in cluster 2, which was reversed as resting memory CD4 T cells, M0 macrophages, and activated mast cells showed no statistical significance for other immune-filtrating cells (Figure 2C). Moreover, ssGSEA analysis illustrated that immune levels differed prominently between the two clusters, with cluster 1 having a comparatively high immune status, except for T helper 2 cells, while others were significantly higher in cluster 1 (Figure 2D). Moreover, cluster 1 showed significantly higher scores of immune activation and immunosuppression than cluster 2, except for the type II IFN response (Figure 2E). Cluster 1 had a higher immune status. ## 3.3. DEGs and Functional Analyses In order to better investigate the underlying signaling pathways, functional analyses were performed, and 1195 DEGs were discovered in total. The result of GO analysis showed that the DEGs were more enriched in glycosylation, CC development, and biological processes related to the immune system, including the regulation of peptidase and endopeptidase activity, epidermal cell and keratinocyte differentiation, and the humoral immune response (Figure 3A,B). Meanwhile, some related cellular components and molecular functions were also enriched (Figure 3A). Moreover, several signaling pathways, including proteoglycans in cancer, cytokine–cytokine receptor interaction, the PI3K/AKT signaling pathway, the Hippo signaling pathway, and HPV infection were identified to be associated with glycosylation, the immune response, and CC (Figure 3C). PPI analysis of DEGs indicated that, compared with cluster 1, 565 genes were upregulated and 630 genes in cluster 2 were downregulated (Figure 3E). We selected the top 30 DEGs based on the number of nodes, including ITFB1 and SDC1, which were closely associated with the proliferation, migration, and prognosis of CC [36,37] (Figure 3D,F). ## 3.4. Risk Model Was Established in the Training Cohort To establish the predictive model based on glycosylation-related genes in CC, we conducted univariate Cox regression analysis. *Potential* genes were screened using LASSO analysis, and 11 genes were selected with the optimal λ value (Figure 4A,B). Multivariate *Cox analysis* identified nine genes based on the genes generated through LASSO analysis to establish the risk model. The risk score = (0.0500580626412369 × MGAT4B) + (0.125800669064781 × FUT11) + (0.0302396698484961 × GALNT2) + (0.266509552440604 × DPY19L4) + (−0.152265202480328 × PMM1) + (0.0625200342212958 × GALNT10) + (−0.329088155870026 × MAN1C1) + (0.130257296074648 × COG3) + (−0.41914468450172 × DERL3). The risk model effectively classified CC patients into high- and low-risk groups (Figure 4C,D). In the high-risk group, the heatmap revealed that six candidate genes had a more general expression, except for PMM1, MAN1C1, and DERL3, and had a worse OS (Figure 4E,G). As for the model diagnosis for the risk model, for 1, 3, and 5 years, the area under the curve (AUC) of the ROC curve was 0.872, 0.865, and 0.841, respectively. The risk model had accurate 1-year predictive capability (Figure 4F). Finally, the TIME in both groups was assessed and the low-risk group had considerably higher stromal sores, immune scores, and ESTIMATE scores (Figure 4H).] ## 3.5. Risk Model Was Validated in the Testing and Total Cohorts The testing cohort was separated into the high- and low-risk groups, and we validated the model in the two groups (Figure 5A,B). The expression of nine candidate genes was displayed on a heatmap with the same outcomes as the training cohort (Figure 5C). For 1, 3, and 5 years, the area under the curve (AUC) of the ROC curve was 0.558, 0.705, and 0.819, respectively (Figure 5D). The model demonstrated accurate 5-year predictive capability. According to the survival analysis, the high-risk group had considerably worse OS in the testing cohort ($$p \leq 0.011$$; Figure 5E). Similar to the training cohort, the low-risk group had significantly higher immune scores and ESTIMATE scores (Figure 5F). In addition, all 291 samples in the total cohort were analyzed to validate the constructed risk model (Figure 6). The results were similar to those for the testing cohort. The risk model and clinical data including the age, FIGO stage, risk, and histopathological grade of CC patients were incorporated into a nomogram to more accurately predict the prognosis of CC patients (Figure 7A). The risk score and clinical risk factors were endowed with a certain score according to their impact on the prognosis in CC. The C-index of the nomogram reached 0.736 (se = 0.04). We then validated the nomogram in all samples. As for the diagnosis of the nomogram, the calibration curve showed consistency between the expected and observed OS (Figure 7B). ## 4. Discussion Protein glycosylation refers to the enzymatic attachment of a glycosyl donor to the side groups of amino acids [38]. It is one of the most abundant post-translational modifications in eukaryotic cells, which is also a critical process involved in numerous gynecological malignancies, including CC [39]. Glycosylation influences extensive aspects of the CC biology, including cell–cell adhesion, cell surface expression, and cancer signaling. CC cells can combine different O-glycosylation modifications and alter the expression levels of proteins to govern their malignant phenotypes [40]. The Tn antigen refers to GalNAc-Ser/Thr during the biosynthesis of mucin-type O-glycosylation. Mutations in the Tn antigen exert a significant impact on tumor cell adhesion, immune evasion, and migration [41]. The abnormal glycosylation profile and Tn-antigen-induced cell identification both contribute to the pathogenesis of CC [42]. Glycosyltransferases are involved in most glycans’ biosynthesis. The altered expression of glycosyltransferases in CC leads to more aggressive characteristics and drug resistance [43]. Under normal conditions, cellular immunity is regulated by activation signals (co-stimulatory molecules) and inhibition signals (immune checkpoints) [44] to maintain homeostasis. An immunosuppressive tumor microenvironment is produced as CC cells continue to evade immune surveillance. It includes the upregulation of regulatory T cells (Tregs) while downregulating anti-cancer activity by effector T cells, the loss of major histocompatibility complex antigen presentation, and the upregulation of immune checkpoints [45]. The programmed cell death receptor (PD-1) on the external effector immune cells binds the programmed cell death receptor ligand (PD-L1) produced by cancer cells. The PD-1/PD-L1 axis is a major immune checkpoint mechanism [46]. According to a study, cisplatin-based treatment can increase PD-L1 in CC, and utilizing a checkpoint blocker may help with tumor cell regression [47]. Pembrolizumab, a PD-1 inhibitory antibody, has been authorized for persistent, recurrent, or metastatic CC treatment [48]. In addition, glycosylation also plays an important role in this pathway. Four glycosylation sites on PD-L1 in the extracellular domain serve as the primary sites of N-glycan modification [49]. Via EGFR signaling and EMT, 1,3-N-acetylglucosamine transferase 3 catalyzes the increase in interaction with PD-1 in triple-negative breast cancer [50,51]. Many cancer types, including melanoma, cervical cancer, and non-small-cell lung cancer, have been discovered to exhibit PD-L1 glycosylation, which is a typical characteristic of cancer [52]. Moreover, the extracellular domain of PD-1 also has four N-glycosylation sites, and glycosylation is necessary to preserve the stability of the PD-1 protein and the location of the cell surface [53]. In T cells, PD-1 is extensively N-glycosylated, and its particular type varies when the TCR is activated [54]. According to a previous study, camdelizumab, a PD-1 antibody, can specifically bind N58 glycosylated PD-1 and block the PD-1/PD-L1 pathway [55]. Although checkpoint inhibitors have achieved extraordinary progress in cancer [56,57], they have attracted researchers’ attention to the exploration of predictive biomarkers for CC owing to their limited efficacy. In our study, two molecular subgroups were identified through consensus clustering according to the glycosylation-related gene expression matrix of CC patients. Immune analysis showed that cluster 1 had a higher immune status, and poor prognosis among CC patients in the high-risk group was found to be related to the immunosuppressive tumor microenvironment. Then, the results of the function assay confirmed that the expression of DEGs was associated with immune dysregulation and glycosylation. We carried out univariate and multivariate Cox regression and LASSO analyses to investigate the clinical value of these genes in CC further, and nine prognostic genes (MGAT4B, FUT11, GALNT2, DPY19L4, PMM1, GALNT10, MAN1C1, COG3, and DERL3) were finally identified to establish the risk model. High- and low-risk groups of CC patients were identified according to the model. To check the efficacy of the constructed model, we further validated these nine genes and our prognostic model in the testing and the total cohorts. The AUC values of ROC for 5 years were 0.841, 0.819, and 0.815, respectively, in the training, testing, and total cohorts, indicating that the constructed model was accurate in predicting the prognosis. Survival analysis revealed that regardless of the cohort, the constructed risk model demonstrated a robust predictive level for the survival of CC patients. Significant decreases in the ESTIMATE score and immune score were always accompanied by poor survival. Therefore, the constructed risk model was proven to be significantly connected with the TIME and possessed strong potential to forecast the prognosis of CC patients in the training, testing, and total cohorts. Finally, a nomogram combining clinical features and the risk score was also created and calibrated, which demonstrated excellent potential in forecasting CC survival. The above results confirmed that the developed risk model could accurately predict the prognosis in CC; TIME disorders, including lower immune and ESTIMATE scores, were prevalent in individuals with poor prognosis. Fucosyltransferase 11 (FUT11) has been reported as a new biomarker for CC prognosis [58]. Mucin O-glycosylating enzyme (GALNT2) has been reported to exhibit the capacity to serve as a novel biomarker for endometrial hyperplasia [59]. GALNT10 was found to be highly predictive of the OS of ovarian cancer [60]. Increased GALNT10 expression also promotes tumor growth by creating an immunosuppressive microenvironment and is associated with poor clinical outcomes in those with high-grade ovarian serous carcinoma [61]. Integrinβ1 (ITGB1) is markedly overexpressed in various malignancies and has been reported as a prospective marker in predicting the effects of immunotherapy in gastric cancer [62]. A previous study indicated that Syndecan 1 (SDC1) might be a novel immune-related prognostic biomarker for pancreatic adenocarcinoma [63]. However, our study is the first to illustrate that these glycosylation-related genes may have a functional involvement in CC and are related to immune infiltration. Furthermore, KEGG analysis revealed that the DEGs were prominent in the PI3K/AKT signaling pathway, cytokine–cytokine receptor interaction, and Hippo signaling pathway. By influencing cell survival, proliferation, and migration, the aberrant triggering of the PI3K/AKT/mTOR signaling pathway can result in a malignant phenotype of cancer cells and chemotherapy resistance [64]. It is crucial for the crosstalk between the virus and the host cells in HPV-positive cancer cells. E6 and E7 have been found to have an activating effect on AKT and mTOR [65,66]. Normally, cytokines are secreted glycoproteins that promote cellular proliferation, differentiation, and apoptosis [67]. However, immuno-suppressive cells are recruited when cytokines bind to their cognate receptors, resulting in tumor invasion and metastasis [68]. The nuclear accumulation of downstream effector factor YAP of the Hippo pathway stimulates the expression of EGF-like ligands (such as TGF-α), which activates EGFR, thereby promoting the growth and invasion of CC. The proteasome-dependent YAP protein can be prevented from degradation and maintained at high levels in CC cells by HPV E6/E7 oncoproteins [69]. The Hippo pathway is significant to cell–cell junctions, as well as [70] extracellular matrix attachment [71] and the TIME [72]. Our predictions were based on analyses of online databases, which is one limitation of our study. As a result, additional experimental validation is required. ## 5. Conclusions In this study, we discovered that the expression of glycosylation-related genes was highly correlated with the TIME and enriched in several significant pathways in CC. Our research might offer a new target for the prognosis of CC. Additional research on these genes and associated signaling networks may reveal new perspectives on CC immunotherapy and lead to better prognoses. ## References 1. 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--- title: 'Nephrotic Syndrome and Statin Therapy: An Outcome Analysis' authors: - Ruxandra Busuioc - Gabriel Ștefan - Simona Stancu - Adrian Zugravu - Gabriel Mircescu journal: Medicina year: 2023 pmcid: PMC10054350 doi: 10.3390/medicina59030512 license: CC BY 4.0 --- # Nephrotic Syndrome and Statin Therapy: An Outcome Analysis ## Abstract Background and Objectives: Hypercholesterolemia in patients with nephrotic syndrome (NS) may predispose to cardiovascular events and alter kidney function. We aimed to evaluate statins efficiency in NS patients under immunosuppression using four endpoints: remission rate (RR), end-stage kidney disease (ESKD), major cardiovascular events (MACE), and thrombotic complications (VTE). Materials and Methods: We retrospectively examined the outcome at 24 months after diagnosis of 154 NS patients (age 53 (39–64) years, $64\%$ male, estimated glomerular filtration rate (eGFR) 61.9 (45.2–81.0) mL/min). During the follow-up, the lipid profile was evaluated at 6 months and at 1 and 2 years. Results: The median cholesterol level was 319 mg/dL, and $83\%$ of the patients received statins. Patients without statins ($17\%$) had similar age, body mass index, comorbidities, blood lipids levels, NS severity, and kidney function. The most used statin was simvastatin ($41\%$), followed by rosuvastatin ($32\%$) and atorvastatin ($27\%$). Overall, $79\%$ of the patients reached a form of remission, $5\%$ reached ESKD, $8\%$ suffered MACE, and $11\%$ had VTE. The mean time to VTE was longer in the statin group (22.6 ($95\%$CI 21.7, 23.6) versus 20.0 ($95\%$CI 16.5, 23.5) months, p 0.02). In multivariate analysis, statin therapy was not associated with better RR, kidney survival, or fewer MACE; however, the rate of VTE was lower in patients on statins (HR 2.83 ($95\%$CI 1.02, 7.84)). Conclusions: Statins did not improve the remission rate and did not reduce the risk of MACE or ESKD in non-diabetic nephrotic patients. However, statins seemed to reduce the risk of VTE. Further randomized controlled studies are needed to establish statins’ role in NS management. ## 1. Introduction Abnormal lipid metabolism is common in patients with nephrotic syndrome, where hypercholesterolemia and hypertriglyceridemia are seen in 90 and $78\%$ of cases, respectively [1,2]. The underlying mechanisms of hyperlipidemia in nephrotic syndrome are only partially understood and involve both enhanced synthesis and decreased metabolism of lipoproteins. Thus, apoB lipoproteins (low-density lipoproteins, LDL) are primarily increased, and their content is higher in cholesterol, triglycerides, and phospholipids than in the general population, whereas high-density lipoproteins (HDL), although usually normal or variable, are dysfunctional [2,3,4]. Persistent hypercholesterolemia, low blood volume, and hypercoagulability in the setting of nephrotic syndrome predispose patients to cardiovascular events and may alter kidney outcomes [5,6]. Besides the specific immunosuppressive therapy for the glomerular disease, the management of hyperlipidemia in patients with nephrotic syndrome follows the guidelines recommended for the general population and use the same lipid-lowering agents. Statins are well-tolerated and effective in correcting, at least partially, the abnormal lipid profile in patients with nephrotic syndrome [7]. However, evidence for the presumed cardiovascular event reduction or kidney disease improvement due to statin therapy is lacking in patients with nephrotic syndrome [7,8,9]. Therefore, we aimed to evaluate statins efficiency in patients with nephrotic syndrome under immunosuppressive therapy using four hard endpoints: remission rate, end-stage kidney disease, major cardiovascular events, and thrombotic complications. ## 2.1. Patients and Study Design This retrospective unicentric study included consecutive non-diabetic adult patients newly diagnosed with nephrotic syndrome (24 h proteinuria >3.5 g and hypoalbuminemia <3.5 g/dl) between 1 January 2010 and 31 December 2015 at “Dr. Carol Davila” Teaching Hospital of Nephrology. The patients were followed from the time of kidney biopsy to the following four distinct outcomes or until 24 months after diagnosis:kidney replacement therapy initiation (dialysis initiation or kidney transplantation).major cardiovascular event (MACE) defined as cardiovascular death, myocardial infarction, or ischemic stroke.thrombotic complications including deep vein thrombosis, renal vein thrombosis, and pulmonary embolism.complete remission defined as proteinuria under 0.5 g per 24 h, serum albumin of at least 3.5 g per deciliter, and stable eGFR (eGFR remaining unchanged or declining by <$15\%$ during follow-up). During the follow-up, the lipid profile was evaluated at 6 months and a year and 2 years after the kidney biopsy. Patients were excluded when they were younger than 18 years at the time of the kidney biopsy, if they had diabetes mellitus or cancer, if they were untreated with immunosuppressants, or if the follow-up was less than 24 months. ## 2.2. Covariates (Measurements) and Treatment Electronic medical records were reviewed for demographics, presentation characteristics, thrombotic complications, outcome data, and laboratory parameters (i.e., serum creatinine, proteinuria, serum albumin, blood lipids, and inflammation). The Charlson comorbidity score (available at: https://www.mdcalc.com/calc/3917/charlson-comorbidity-index-cci; URL accessed on 10 June 2021) was used to assess the burden of comorbidities in the studied patients. It is based on a weighted sum of the presence and severity of 17 various conditions. The averages of the serum albumin and urinary protein values in 6 month periods are presented as the time-averaged serum albumin and proteinuria. Only patients receiving immunosuppressive therapy were included in the analyses. The choice of the immunosuppressive treatment was at the discretion of the nephrologist in charge. ## 2.3. Statistical Analysis Descriptive statistics were summarized as mean ± SD or median (quartile 1, quartile 4) for continuous variables, and frequency distribution is presented as percentages for categorical variables. Group comparisons were performed with Student’s t-test, χ2 test, and Mann–Whitney U test, as appropriate. Survival analyses were conducted with the Kaplan–Meier method, and the log rank test was used for comparisons. Multivariate Cox proportional hazard analyses were performed to identify independent predictors of the studied endpoints. The results were expressed as hazard ratio (HR) and $95\%$ confidence interval (CI). All statistical tests were two-sided, and a $p \leq 0.05$ was considered significant. Statistical analyses were performed using the SPSS program (SPSS version 26, Chicago, IL, USA). ## 2.4. Ethics Approval The study was conducted with the provisions of the Declaration of Helsinki, and the protocol was approved by the local ethics committee (“Dr. Carol Davila” Teaching Hospital of Nephrology, Bucharest, Romania, approval number 2021-012, 3 March 2021). Since all data were anonymized, informed consent was not obtained from individual patients. ## 3. Results We found 213 patients with nephrotic syndrome in our databases during the study period. Based on the exclusion criteria, 59 cases were excluded; the main reasons were: incomplete follow-up [30], childhood onset of the nephrotic syndrome, [5] and missing data on statin therapy [24]. The final cohort comprised 154 patients, with a median age of 53 years at the time of the kidney biopsy and with a male sex predominance ($64\%$). The most frequent cause of nephrotic syndrome was membranous nephropathy ($55\%$), followed by minimal change disease ($31\%$), focal and segmental glomerulosclerosis ($11\%$), and membranoproliferative glomerulonephritis ($3\%$). All patients received an immunosuppression therapy based on corticotherapy, i.e., $26\%$ received corticotherapy only, $58\%$ corticotherapy plus cyclophosphamide, and $16\%$ corticotherapy plus cyclosporine. There were no differences between the two studied groups in regard to the type of immunosuppressive drugs (Table 1). The baseline characteristics of the included patients are presented in Table 1. The median eGFR was 70 mL/min at diagnosis, and all included patients had full-blown nephrotic syndrome (i.e., median proteinuria, 6.4 g/g and hypoalbuminemia, 2.9 g/dL) at presentation. Almost half of the patients had arterial hypertension, but the comorbidity burden evaluated with the Charlson index was rather mild with a median score of one. The median cholesterol level was 319 mg/dL, and $83\%$ of the patients received statin therapy. However, the patients without statin therapy had similar age, body mass index, comorbidities, blood lipids levels (cholesterol, triglycerides, and total lipids), nephrotic syndrome severity, and kidney function (Table 1). The most frequent prescribed statin was simvastatin ($41\%$), followed by rosuvastatin ($32\%$) and atorvastatin ($27\%$). The median dose of the prescribed statins was 20 mg; there were no differences in dosing between the statin categories. During the follow-up period, we found no differences in the cholesterol levels, neither depending on the used statins nor between statin-treated and untreated patients, at baseline, 6 months, and 1 and 2 years (Figure 1). Overall, $79\%$ of the studied patients reached a form of remission (Table 1). Complete remission rates were $43\%$ after 6 months, $55\%$ after 12 months, and $65\%$ after 24 months. The mean time to cumulative remission was 13.7 ($95\%$CI 12.2, 15.2) months. There was no relationship between statin therapy and time to remission (statin, 13.9 ($95\%$CI 12.4, 15.6), no statin, 12.6 ($95\%$CI 8.8, 16.3) months, p 0.4) (Figure 2A). Eight patients ($5\%$) started kidney replacement therapy (Table 1). The primary renal diseases were focal and segmental glomerulosclerosis ($$n = 3$$, $37.5\%$), membranous nephropathy ($$n = 3$$, $37.5\%$), and minimal change disease ($$n = 2$$, $25\%$). Kidney survival at 6, 12, and 24 months was 97, 96, and $93\%$, respectively. The mean kidney survival time was similar between the two studied groups (statin, 23.4 ($95\%$CI 22.8, 24.0), no statin, 22.4 ($95\%$CI 20.3, 24.0) months, p 0.5) (Figure 2B). Moreover, there were no differences in kidney survival depending on the type of statin used (Kaplan–Meier analysis, log rank test, p 0.1). Twelve ($8\%$) patients suffered from a major adverse cardiovascular event; however, no death was registered during the follow-up period (Table 1). The mean time to MACE was 23.2 ($95\%$CI 22.7, 23.8) months. We report no relationship between treatment with statin and time to MACE (statin, 23.1 ($95\%$CI 22.4, 23.8), no statin, 24.0 ($95\%$CI 24.0, 24.0) months, p 0.6) (Figure 2C). Thrombotic complications were present only in $11\%$ of the patients and included pulmonary embolism, renal vein thrombosis, and deep vein thrombosis. Interestingly, the patients who were not on statin therapy had a significantly higher percent of thrombotic complications during the follow-up period (23 vs. $9\%$, p 0.03) (Table 1). Furthermore, the mean time to a thrombotic event was significantly shorter in these patients (no statin, 20.0 ($95\%$CI 16.5, 23.5), statin, 22.6 ($95\%$CI 21.7, 23.6) months, p 0.02) (Figure 2D). In multivariate analysis, statin therapy was not associated with better remission rate, kidney survival, or fewer MACE; however, the rate of thrombotic complications was significantly lower in patients who received statins (Table 2). In addition, the protective effect of statins (HR 3.16 ($95\%$CI 1.13, 8.83)) for thrombotic complications remained after adjusting for time-averaged albumin (HR 0.85 ($95\%$CI 0.34, 2.12)) and proteinuria (HR 1.05 ($95\%$CI 0.92, 1.21)). Serious side effects were not reported in the studied patients. Only two patients had a more than three times upper the normal limit elevation in alanine aminotransferase levels, and one patient complained of myalgias; in all these cases, statin therapy was stopped. ## 4. Discussion In this retrospective study involving nephrotic patients treated with immunosuppressives, statin therapy did not improve the cholesterol levels. Moreover, there were no differences in nephrotic syndrome remission rates, in the proportion of patients who initiated kidney replacement therapy, and in the rate of major cardiovascular events during the two-year follow-up. However, patients on statins had fewer thrombotic complications. The particularity of our research is that we studied—for the first time to our knowledge—the relationship between statins and these four hard endpoints in non-diabetic patients with nephrotic syndrome who received immunosuppressive therapy. Currently, statins are the norm in the management of hyperlipidemia of nephrotic syndrome, despite the paucity of data to prove their efficiency in this setting [7,8,9,10,11]. Statins seem to be well tolerated and effective in correcting, at least partially, the abnormal lipid profile in patients with nephrotic syndrome [9,10]. However, the benefits and ability of statins to slow the progression of chronic kidney disease remain unproven and largely controversial [12]. Thomas et al. performed a randomized controlled trial on thirty adult patients with nephrotic syndrome or significant proteinuria (>1 g/day) who were randomized to simvastatin or placebo therapy and found no significant differences between the groups in proteinuria levels, rise in serum creatinine, or decline in plasma inulin clearance [8]. In line with this, we report no relationship between statin therapy and remission rate or kidney replacement therapy initiation in our cohort. These results might challenge the dogma that statins are efficient in hyperlipidemia management in patients with nephrotic syndrome treated with immunosuppressive drugs. Statin effect on the cholesterol level and on MACE could be confounded by the immunosuppressive treatment which leads to the remission of the nephrotic syndrome. Immunosuppressant-mediated hypercholesterolemia has also been reported, especially for cyclosporine [13]. However, the mechanisms behind immunosuppressant-mediated hypercholesterolemia are not completely understood. In the case of cyclosporine, it appears that many steps of lipid metabolism can be disturbed: lipoprotein synthesis, lipolysis, uptake, and clearance [13]. In our population, all patients received immunosuppressive treatment, and only $16\%$ of them were on a cyclosporine regimen. Moreover, there were no differences between the two studied groups concerning the immunosuppression agents. Therefore, the confounding risk of immunosuppressant-mediated hypercholesterolemia in our study was reduced. There are numerous epidemiologic studies and randomized clinical trials that have established hypercholesterolemia as a major risk factor in the pathogenesis of atherosclerotic cardiovascular disease. Nevertheless, there are few studies to confirm these findings in patients with nephrotic syndrome. Ordonez et al. compared 142 non-diabetic adult patients with nephrotic syndrome with matched controls, and those with nephrotic syndrome had a higher risk of myocardial infarction (relative risk [RR], 5.5, $95\%$CI 1.6–18.3) but a non-significantly higher risk of coronary death (RR, 2.8, $95\%$CI 0.7–11.3) [5]. In addition, Dogra et al. showed that statin therapy improved brachial artery endothelial function measured by flow-mediated dilatation in patients with nephrotic syndrome [14]. Nevertheless, persistent nephrotic syndrome and hyperlipidemia seem to be risk factors for atherosclerotic cardiovascular disease, especially if other cardiovascular risk factors are present [15]. However, the low incidence of MACE in our cohort could be explained by the rather mild Charlson score and the relatively short follow-up time for a population with a median age of 53 years. Thrombotic events are relatively frequent in patients with nephrotic syndrome, being eight times more frequent than in the general population [16]. The hypercoagulable state due to nephrotic syndrome is not well understood and is probably multifactorial [17]. The most frequent reported abnormalities include reduced levels of natural anticoagulants such as antithrombin III, plasminogen, and protein C and S (due to urinary losses), increased platelet activation, hyperfibrinogenemia, inhibition of plasminogen activation, and the presence of high-molecular-weight fibrinogen in the serum (due to increased liver synthesis) [17,18,19,20]. Moreover, hypovolemia, diuretic therapy, and corticosteroid treatment can additionally increase the thrombotic risk. Comparable to nephrotic syndrome, other hyperlipidemic disorders such as familial hypercholesterolemia are associated with a high incidence of thrombotic episodes [21]. In this case, the level of oxidized low-density lipoproteins (oxLDLs) is increased, and oxLDLs seem to interact with monocytes and macrophages, leading to the expression of tissue factor, a procoagulant molecule [22]. Statins are known to have pleiotropic effects on coagulation and inflammation: improvement in endothelial function, inhibition of platelet activation and of thrombosis [23]. Moreover, studies in non-renal patients reported antithrombotic properties of statins due to their influence on the coagulation cascade [24,25]. In line with this, Zou et al. reported that statin therapy was associated with a lower risk of venous thromboembolism in patients with primary membranous nephropathy, a benefit independent of the statin potency [26]. Similarly, in our cohort of nephrotic patients—more than half with primary membranous nephropathy—statins were associated with a lower risk of thrombotic events. We acknowledge several limitations of our study. The data were retrospectively collected and were, therefore, dependent on the accuracy and completeness of the electronic databases (for example, smoking status was not available for all the patients, and therefore was not included as a variable in the analysis). In addition, the follow-up time of 24 months was a compromise between the time with data completeness and the clinically relevant time for the investigated outcomes. Importantly, LDL cholesterol, HDL cholesterol, and lipoprotein (a) were not routinely measured and were not included in the analysis. Moreover, asymptomatic thrombotic events may have been missed because the participants were not regularly screened, which could have led to an underestimation of the incidence. Our cohort may not be representative of all adult patients with nephrotic syndrome due to the referral-based nature of our cohort. ## 5. 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--- title: Palmitic Acid Inhibits Myogenic Activity and Expression of Myosin Heavy Chain MHC IIb in Muscle Cells through Phosphorylation-Dependent MyoD Inactivation authors: - Izumi Matsuba - Rikako Fujita - Kaoruko Iida journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054354 doi: 10.3390/ijms24065847 license: CC BY 4.0 --- # Palmitic Acid Inhibits Myogenic Activity and Expression of Myosin Heavy Chain MHC IIb in Muscle Cells through Phosphorylation-Dependent MyoD Inactivation ## Abstract Sarcopenia associated with aging and obesity is characterized by the atrophy of fast-twitch muscle fibers and an increase in intramuscular fat deposits. However, the mechanism of fast-twitch fiber-specific atrophy remains unclear. In this study, we aimed to assess the effect of palmitic acid (PA), the most common fatty acid component of human fat, on muscle fiber type, focusing on the expression of fiber-type-specific myosin heavy chain (MHC). Myotubes differentiated from C2C12 myoblasts were treated with PA. The PA treatment inhibited myotube formation and hypertrophy while reducing the gene expression of MHC IIb and IIx, specific isoforms of fast-twitch fibers. Consistent with this, a significant suppression of MHC IIb protein expression in PA-treated cells was observed. A reporter assay using plasmids containing the MHC IIb gene promoter revealed that the PA-induced reduction in MHC IIb gene expression was caused by the suppression of MyoD transcriptional activity through its phosphorylation. Treatment with a specific protein kinase C (PKC) inhibitor recovered the reduction in MHC IIb gene expression levels in PA-treated cells, suggesting the involvement of the PA-induced activation of PKC. Thus, PA selectively suppresses the mRNA and protein expression of fast-twitch MHC by modulating MyoD activity. This finding provides a potential pathogenic mechanism for age-related sarcopenia. ## 1. Introduction Sarcopenia is an age-related, progressive, and generalized skeletal muscle disorder characterized by low muscle strength and mass and reduced functional performance [1,2]. It becomes a major cause of frailty, which dramatically affects health status and quality of life in the elderly [3,4]. Sarcopenia is caused by a variety of factors, including not only aging but also poor nutrition, reduced physical activity, and chronic diseases [1,2]. Obesity, especially age-associated obesity, is closely involved in the development of sarcopenia [5]. A reduced muscle mass correlates with a lower resting metabolic rate, which perpetuates the development of obesity. Indeed, in adult males, muscle mass contributes to 30–$42\%$ of the total body weight in younger individuals, declining with age to 18–$27\%$, while the body fat mass increases from $20\%$ to $30\%$ [6,7]. Thus, lipid deposition occurs in various organs, including skeletal muscles, leading to the metabolic disturbance known as lipotoxicity [8,9]. In the elderly, lipotoxicity acts synergistically with sarcopenia to cause various chronic diseases, such as cardiovascular diseases [10,11]. Saturated fatty acids, including palmitic acid (PA), are thought to play a causal role in lipotoxicity [12]. PA, the most common and predominant saturated fatty acid in the human body [13], is generally stored as a component of triglycerides in lipid droplets in adipose tissue. However, when lipid accumulation in adipose tissue or lipid intake from diet is excessive, the PA in the blood also increases, acting in a paracrine or endocrine manner in various tissues, with adverse effects that lead to disease development [14,15]. In many in vitro and in vivo experimental settings, PA treatment has been shown to induce inflammatory reactions, mitochondrial dysfunction, and the generation of reactive oxygen species, leading to cellular damage and cell and tissue death [13,15,16]. Several in vitro studies evaluating the effects of PA on myocytes have reported that PA exposure negatively affects myocyte maintenance by suppressing protein synthesis [17] and upregulating proteolytic signaling [18]. Furthermore, PA has been shown to induce endoplasmic reticulum (ER) stress, which in turn triggers programmed cell death via apoptosis [19,20]. PA also regulates the expression of several microRNAs, thereby inhibiting myoblast differentiation and maturation into myofibers [21,22]. Skeletal muscles are comprised of two types of fibers with distinct metabolic profiles: glycolytic (type II) fibers that mainly use glucose as a substrate, and the more oxidative (type I) fibers that use lipids as a substrate. Reductions in muscle mass associated with aging are known to occur mainly in type II fibers [23,24]. This raises the question of whether intramuscular lipid accumulation, particularly excess PA, plays a causal role in the selective reduction of type II fibers in the elderly. Carter et al. [ 25] hypothesized that type II fibers are more vulnerable to lipotoxic stress based on findings that type II fibers have less cellular machinery to deal with the fatty acid spillover than type I fibers [26]. This is supported by animal studies that demonstrated a greater adaptive response of type I fibers to intracellular lipid accumulation [27]. Muscle fiber types are determined by the expression of different myosin heavy chain (MHC) isoforms, MHC I, IIa, IIx, and IIb, with type I fibers primarily expressing MHC I and type II fibers primarily expressing MHC IIx and IIb (although MHC IIb is rarely detected in human muscle) [28]. MHC gene expression is dynamic and changes with specific conditions such as training, immobility, or disease. A significant reduction in the mRNA levels of MHC IIx, a predominant isoform in human type II fibers, with no change in MHC I, has been reported in aging [29,30]. We therefore further hypothesized that increased PA due to intramuscular lipid accumulation is directly responsible for reduced MHC II mRNA expression. Therefore, in the present study, we investigated whether PA differentially affects the MHC mRNA expression of each MHC isoform, using muscle cells derived from the C2C12 mouse myoblast cell line. ## 2.1. PA Inhibits the Terminal Differentiation of Myoblasts into Myotubes We initially examined the effect of PA on morphological changes and MHC production in differentiated C2C12 cells. In cells treated with 400 μM PA on day 5 for 24 h (Figure 1a), the ratio of differentiated myotubes expressing MHC, a marker of terminal differentiation, was lower than in the untreated control cells (Figure 1b). The calculated fusion index and the average amount of MHC in the cultures treated with PA were significantly lower than in the untreated control at the same time point (Figure 1c). ## 2.2. PA Primarily Inhibits the Expression of MHC IIb in Differentiated Cells The effect of PA on the expression of each MHC gene was examined. Mouse muscles contain four MHC isoforms (MHC I, IIa, IId/x, and IIb) [28], and the transcripts of all these isoforms are well expressed in C2C12 cells after day 4 of differentiation [31]. Hence, the effect of PA on the expression of genes encoding each MHC isoform was examined on days 4 and 6 (Figure 2a). Treatment with 400 μM PA for 24 h significantly suppressed the expression of Myh4 (encoding MHC-IIb) on days 4 and 6 (Figure 2b) and that of Myh1 (encoding MHC-IId/x) on day 6 (Figure 2b). In contrast, the expression levels of Myh2 (encoding MHC-IIa) and Myh7 (encoding MHC-I) were not altered by PA treatment on either day. These effects of PA on Myh4 expression were observed from the early to late stages of differentiation (from day 1 to day 6) (Figure 2c). As the expression of MHC genes is strictly controlled by several myogenic regulatory factors (MRFs), the levels of Myod and Myog (encoding MyoD and myogenin, respectively) were determined on days 4 and 6. The results showed that Myod expression was significantly suppressed by PA treatment on both days, whereas Myog expression was suppressed only on day 6 (Figure 2d). The inhibition of MHC protein expression by PA was further confirmed by Western blotting. Consistent with the gene expression results, C2C12 myotubes treated with 400 μM PA on day 6 contained considerably less MHC IIb protein than untreated controls (Figure 3). The MHC I protein expression was also reduced by PA, inconsistent with the results of the gene expression analysis (Figure 3). ## 2.3. The Inhibitory Effect of PA on MHC Expression in Myotubes Is Not Mediated via TLR-4 PA is known to act as a ligand for toll-like receptors (TLR), especially TLR4, which promotes inflammatory responses [32]. To investigate whether the activation of this receptor is involved in the PA-induced inhibition of myotube differentiation and Myh4 expression, we assessed the effect of a TLR4-specific inhibitor, TAK-244. TAK-244 had no influence on the inhibitory effects of PA on cellular MHC production, based on fluorescence intensity (Figure 4a) and Myh1 and Myh4 expression in C2C12 myotubes (Figure 4b). ## 2.4. PA Suppresses MyoD-Induced Activation of Myh4 Promoter in C2C12 Cells Using a luciferase reporter assay, we further examined whether PA reduced MHC gene expression by directly suppressing promoter activity, focusing specifically on the *Myh4* gene. The transfection of C2C12 myoblasts with the luciferase reporter gene under the control of the mouse Myh4 promoter resulted in increased reporter gene transcription during cell differentiation (Figure 5a). Treatment with 400 μM PA for 24 h significantly reduced reporter gene transcription relative to the vehicle control on each day of differentiation (Figure 5a). The Myh4 promoter is preferentially activated by MyoD [33]. Therefore, we examined whether MyoD transcriptional activity was suppressed by PA treatment. Promoter activity of the pGL-MHCIIb reporter construct was substantially elevated in undifferentiated myoblasts under the forced expression of MyoD with pcDNA–MyoD relative to that in cells transfected with the empty pcDNA3 vector (Figure 5b). After PA treatment for 24 h, promoter activity was also upregulated through the forced expression of MyoD, albeit moderately compared to the activity in the untreated cells (Figure 5b). ## 2.5. The Inhibitory Effect of PA on Myh4 Promoter Activation by MyoD Requires Ser Residues That Are Targets for Phosphorylation The MyoD protein contains several phosphorylation sites, and the phosphorylation of specific sites, such as Thr115 [34] or Ser200 [35,36], regulates its myogenic function. Therefore, we examined whether the phosphorylation of MyoD is involved in the mechanism by which PA suppresses the MyoD-induced increase in Myh4 promoter activity. The mutant forms of MyoD expressed by each expression plasmid are shown in Figure 6a. In undifferentiated myoblasts expressing MyoD-T/A with a single mutation at Thr115, the PA-induced inhibition of Myh4 promoter activity was statistically recovered. However, the promoter activity was significantly suppressed in cells expressing this mutant compared with native MyoD-expressing controls (Figure 6b). Conversely, in myoblasts expressing MyoD-S/A with a single mutation on Ser200, promoter activity was significantly suppressed by PA treatment to a similar extent as in control cells expressing native MyoD (Figure 6c). When the mutant MyoD-S/A-2, with mutations at Ser5 and Ser262 in addition to Ser200 (all known phosphorylation targets [37,38]), was expressed in cells, Myh4 promoter activity was elevated relative to the activity in the control cells (Figure 6d). The PA-induced reduction in Myh4 promoter activity was still observed in MyoD-S/A-2-expressing cells; however, this decrease was significantly recovered compared to the control cells expressing native MyoD (Figure 6d). ## 2.6. Inhibition of PKC Partially Recovers PA-Induced Inhibition of MHC IIb Gene Expression in C2C12 Myotubes The phosphorylation of MyoD is likely to be involved in the inhibition of Myh4 transcription by PA. Therefore, we tested whether kinase inhibition attenuated the suppressive effect of PA on the expression of Myh4. For validation, we used the following three inhibitors: (a) Ro 31-8220, a potent PKC inhibitor of PKCα/β/γ and PKCε; (b) myriocin, an SPT inhibitor that inhibits the conversion of PA to ceramide, an activator of PKCζ; (c) roscovitine, a selective CDK inhibitor of CDK1 and CDK2. We observed that 0.5 μM Ro 31-8220 partially diminished the suppression of Myh4 expression by PA treatment (Figure 7a). In contrast, myriocin (Figure 7b) and roscovitine (Figure 7c) at up to 5 μM did not affect the PA-induced suppression of Myh4 expression. Finally, Figure 8 summarizes the putative mechanism by which PA selectively suppresses the expression of fast-twitch MHC, MHC IIb. ## 3. Discussion In this study, we found that PA suppressed the mRNA and protein expression of MHC, specifically MHC IIb, a predominant form of fast-twitch fiber, in C2C12 myotubes by inhibiting the transcriptional activity of MyoD. We suggest that the mechanism by which PA inhibits MyoD transcriptional activity is the phosphorylation of MyoD, and that a specific type of PKC participates in this mechanism. Several studies have examined the direct effects of PA on cultured myoblasts and myocytes. Similar to the findings of the present study, treatment of myoblasts with PA has been shown to inhibit myogenic cell differentiation and myotube maturation [21,22,39,40] and reduce type II myosin protein expression [41]. We further clarified the detailed mechanism by which PA treatment selectively inhibits the expression of specific MHC isoforms at a transcription level during myoblast differentiation. TLR4 is a major receptor that recognizes pathogen-associated molecular patterns, leading to the induction of sterile inflammation. PA cross-reacts with this receptor and causes the derangement of intracellular signaling pathways in muscle cells and tissues [32,42,43]. Several previous studies have suggested that the pro-inflammatory effects of PA and the associated inhibition of PI3K/Akt signaling are involved in the mechanism by which PA reduces the differentiation potential of myogenic cells [39,40]. However, in the present study, the TLR4-specific inhibitor TAK-242 did not affect the PA-induced inhibition of Myh4 expression, suggesting that the signaling pathway involving TLR4 is independent of the mechanism. The process of myogenic differentiation is strictly regulated by several transcription factors, including Myf5, MyoD, and myogenin. Of these, MyoD and Myf5 are required for commitment to the myogenic lineage in the early stage of differentiation. In contrast, myogenin is believed to play a critical role in the expression of the terminal muscle phenotype pre-established by MyoD late in the differentiation process [44]. MyoD transcriptionally activates myogenin expression and autoactivates its own expression through a positive feedback loop. Moreover, several studies have confirmed that MyoD plays a crucial role in MHC IIb expression in mature muscles [33,45,46]. In the denervated soleus muscles of rats and mice, the overexpression of normal MyoD, or a mutant form resistant to inactivation, increased the number of fast-type MHC fibers [47]. In the present study, PA treatment specifically suppressed the expression of MHC IIb, a fast-type MHC isoform. This suppressive effect was observed during the early stage of myoblast differentiation (on day 1). In addition, Myod and *Myog* gene expression was suppressed by PA treatment. Based on these observations, we focused on MyoD as a key molecule in the mechanism by which PA regulates gene expression in MRFs and MHCs. As expected, the results of the reporter assay suggest that Myh4 expression is repressed at the transcriptional level by PA during differentiation and that, as a mechanism, PA administration suppresses the MyoD-dependent transcription of Myh4. The MyoD protein contains several phosphorylation sites targeted by specific protein kinases, such as PKC and CDK, and its activity is thought to be regulated by post-transcriptional modification. For instance, phosphorylation of serine residues at positions 5, 200, and 262 by CDK1 and/or CDK2 results in the degradation of the MyoD protein [35,36,37,38]. Another study reported that two putative PKC phosphorylation sites, Ser200 and Thr115, are required for MyoD inactivation [34]. Here, MyoD, with amino acid substitutions of serine residues that disrupt phosphorylation by CDK and PKC, significantly recovered the PA-induced inhibition of Myh4 promoter activity. The amino acid substitution at Thr115 also recovered PA-induced reduction in Myh4 promoter activity. However, this mutant severely suppressed Myh4 promoter activity itself, which is inconsistent with previous results that demonstrated that the expression of mutant (Thr115 to Ala) MyoD leads to an increase in MHC protein expression in mouse fibroblasts [34]. The cause of this discrepancy between studies is unknown; however, a reduction in promoter activity by this mutant may be due to the importance of Thr115 in the binding capacity of MyoD [48]. Finally, the experimental results using a specific inhibitor showed that PKC, but not CDK, is likely to be involved in the mechanism of the PA-induced inhibition of Myh4 transcription. PKCs form a large family of serine–threonine kinases that can be classified into three subfamilies, depending on the specific lipids required for their activation. Conventional PKCs (cPKCs, including PKCα/β/γ) and novel PKCs (nPKCs, including PKCε) require a lipid second messenger, diacylglycerol (DAG), for activation; the former require Ca2+ and the latter are Ca2+-independent, whereas atypical PKCs (aPKCs, such as PKCζ) are not activated by DAG but by another lipid mediator, sphingolipid ceramide [49,50,51]. Both DAG and ceramide are synthesized from PA; however, Ro 31-8220, not myriocin, restored PA-induced reductions in Myh4 expression, suggesting the involvement of DAG-activated PKC in the mechanism. Levels of DAG were significantly higher in myogenic cells treated with PA and in the muscles of genetically obese mice than in controls [52,53]. Such an elevation in DAG levels would lead to the suppression of MyoD activity through phosphorylation by PKC. On the other hand, we could not determine whether Ro 31-8220 could completely eliminate the PA-induced inhibition of Myh4 expression because MCH gene expression was severely suppressed when this inhibitor was used at high concentrations (Supplementary Figure S1). Ro 31-8220 inhibits the activity of PKCε, which has been reported to play important roles in myoblast differentiation [54,55]. Therefore, treatment with this inhibitor may lead to the suppression of MHC expression. In addition, a previous study suggested the involvement of PKCθ, a member of nPKCs, in the biological effects of PA on C2C12 myocytes [56]. Further studies are needed to ascertain which PKCs are more critical for the action mechanism of PA. In recent years, sarcopenia has become a major health problem in an aging society. The histological changes in age-related loss of muscle tissue are characterized by the atrophy of fast-twitch muscle fibers and an increase in intramuscular fat deposition [57]. The present study reveals that PA, a predominant component of body fat, selectively suppresses the mRNA and protein expression of fast-twitch MHC by modulating the transcriptional activity of MyoD, suggesting a pathogenic mechanism of sarcopenia. ## 4.1. Materials PA was purchased from Nacalai Tesque (Kyoto, Japan). Fatty-acid-free bovine serum albumin (BSA) was purchased from FUJIFILM Wako Chemicals (Osaka, Japan). TAK-242, an inhibitor of toll-like receptor 4 (TLR4), and myriocin, an inhibitor of serine palmitoyl-transferase (SPT), a key enzyme for ceramide de novo synthesis, were purchased from Cayman Chemical (Ann Arbor, MI, USA). Ro 31-8220, a potent inhibitor of protein kinase C (PKC), was obtained from Santa Cruz Biotechnology (Dallas, TX, USA). Roscovitine, a selective cyclin-dependent kinase (CDK) inhibitor of CDK1 and CDK2, was purchased from FUJIFILM Wako Chemicals. The inhibitors were reconstituted in dimethyl sulfoxide. ## 4.2. Palmitic Acid Complex Preparation PA was complexed with BSA in phosphate-buffered saline (PBS). PA was first added to a 100 mM NaOH solution at a concentration of 100 mM and dissolved on a heat block at 75 °C for 30 min. The prepared PA solution was then added to $10\%$ (w/v) fatty-acid-free BSA in PBS at a ratio of 1:9 (v/v) to obtain a PA–BSA solution with a PA concentration of 10 mM. This solution was added to the medium at a final concentration of 400 μM PA. The chosen concentration of PA is within the physiological range of the plasma PA concentration of healthy adults [58]. For the vehicle control, a mixture of 100 mM NaOH and $10\%$ BSA/PBS (1:9) was used. Each prepared solution was warmed to 55 °C before being added to the cells. ## 4.3. Cell Culture and Treatment C2C12 myoblasts (RIKEN, Tsukuba, Japan) were cultured in Dulbecco’s modified Eagle’s medium (DMEM) containing $10\%$ fetal bovine serum at 37 °C in a humidified atmosphere with $5\%$ CO2. Myoblasts were seeded on the type-I-collagen-coated plate (Iwaki, Shizuoka, Japan) at a density of 3.0 × 104 cells/cm2. The following day (day 0), differentiation into myotubes was initiated by replacing the medium with a differentiation medium (DMEM containing $2\%$ horse serum). The medium was changed daily until the cells were collected for analysis. In the treated set, the C2C12 myotubes were incubated with 400 μM PA from the indicated day of differentiation (day 0 to day 5) for 24 h. In some of the experiments, the inhibitors (1 μM TAK-242, 0.5 μM Ro 31-8220, 5 μM myriocin, or 5 μM roscovitine) were added separately with the PA. We confirmed that inhibitor treatment did not affect cell viability at the indicated concentrations (data not shown). ## 4.4. Gene Expression Analysis Using Real-Time PCR The total RNA was isolated from cells using Sepasol-RNA I reagent (Nacalai Tesque). First-strand cDNA was synthesized using ReverTra Ace qPCR RT Master Mix (TOYOBO, Osaka, Japan), following the manufacturer’s instructions. Next, the quantitative real-time PCR was carried out using a SYBR premix Ex Taq II (TAKARA BIO, Shiga, Japan) with 10 µL reactions on a Thermal Cycler Dice Real Time System (TAKARA BIO) for amplification. The PCR cycling conditions were one cycle of 30 s at 95 °C, followed by 40 cycles of 5 s at 95 °C and 30 s at 60 °C. Gene mRNA expression was normalized to that of a standard housekeeping gene (Gapdh) using the ΔΔCT method. Experiments were performed in duplicate and repeated three times independently. The primer sequences are shown in Supplementary Table S1. ## 4.5. Western Blotting The cells were washed with PBS, dissolved in lysis buffer ($1\%$ Triton X-100, $0.45\%$ sodium pyrophosphate, 100 mM NaF, 2 mM Na3VO4, 50 mM HEPES (pH 8.0), 147 mM NaCl, 1 mM EDTA, and protease inhibitor mixture (cOmplete; Sigma-Aldrich, Tokyo, Japan), and centrifuged at 12,000× g for 15 min at 4 °C. The supernatant was used as the cell lysate. Referring to a previous report [59], cell lysate proteins (50 μg per lane) were resolved on $8\%$ SDS-PAGE gel containing $30\%$ glycerol, and electrophoresed at 100 V for 24 h at 4 °C (this electrophoretic condition allows for the separation of MHC isoforms on the same gel). The protein bands were then transferred to a PVDF membrane (Hybond-P; GE Healthcare Life Science, Tokyo, Japan). The membrane was blocked with Blocking One P (Nacalai Tesque) for 30 min at room temperature (20–25 °C) and incubated overnight at 4 °C with an antibody against MHC (1:1000; MF-20; Hybridoma Bank, Iowa, IA, USA), which recognizes all MHC isoforms, or with β-actin (1:1000; sc-47778; Santa Cruz Biotechnology). Next, the membranes were incubated with a secondary anti-mouse IgG antibody (1:5000; #7076; Cell Signaling Technology, Danvers, MA, USA) in Tris-buffered saline containing $0.1\%$ Tween 20 for 1 h at room temperature. The bands were developed using an ECL Prime Western Blotting Detection Reagent (GE Healthcare Life Science), and images were captured using an ImageQuant LAS-4000 (GE Healthcare Life Science) image analyzer. The optical density of each band was analyzed using ImageJ software (National Institutes of Health, Bethesda, MD, USA). Experiments were repeated twice independently. ## 4.6. Immunofluorescence and Calculation of the Myogenic Index The differentiated C2C12 cells were fixed and permeabilized using $1\%$ Triton-X containing $4\%$ paraformaldehyde in PBS for 10 min at room temperature. The cells were then incubated with an MF-20 anti-MHC antibody (1:100) for 90 min at room temperature, washed with PBS containing $0.1\%$ Tween 20 (PBS-T), and incubated for 1 h with anti-mouse IgG conjugated with fluorescein isothiocyanate (FITC) (1:500; #115-095-062; Jackson ImmunoResearch, West Grove, PA, USA). After washing the samples with PBS-T, the nuclei were stained with 4,6-diamidino-2-phenylindole (DAPI). For each condition, 15 images of the cells ($$n = 3$$, five images per sample) were randomly taken using the 40× objective lens on a fluorescence microscope (BZ-X700; Keyence, Osaka, Japan). The number of nuclei in each sample was counted from the photographs, and the MHC-positive polynucleic cells stained with green fluorescence were defined as myotubes. The fusion index (%) was calculated using the following formula: (number of nuclei within myotubes/total number of nuclei) × 100. The average myocellular MHC content was estimated by dividing the total green fluorescence intensity (in pixels) by the total number of nuclei. The measurement methods are summarized in Supplementary Figure S2. ## 4.7. Reporter Assays The luciferase reporter plasmid, under the control of the Myh4 promoter, and the MyoD expression plasmid were previously constructed [60]. Briefly, mouse promoter sequences (−1347 to +33) of Myh4 (encoding MHC IIb protein) were amplified from mouse genomic DNA using specific primers with suitable restriction sites. These were cloned into the pGL3 basic vector (Promega, Tokyo, Japan) and named pGL-MHCIIb. Full-length mouse MyoD cDNA was amplified by PCR, using specific primers with suitable restriction sites, and cloned into a pcDNA3 mammalian expression vector named pcDNA-MyoD. Using the pcDNA-MyoD and KOD-Plus-Mutagenesis Kit (Toyobo, Osaka, Japan), three additional mutant MyoD expression plasmids were constructed: those expressing a MyoD protein that substituted alanine (Ala) at each of the following positions: threonine (Thr) residue Th115 (pcDNA-MyoD-T/A), serine (Ser) residue S5 (pcDNA-MyoD-S/A), and multiple serine residues S5, S200, and S262 (pcDNA-MyoD-S/A-2). One day before transfection, C2C12 cells (3 × 104 cells/well) were seeded into 24-well plates (non-coated for undifferentiated cells, or collagen-coated for differentiated cells), and the indicated plasmid and control plasmid (pRL-SV40) (Promega), containing early SV40 enhancer/promoter region upstream of the Renilla luciferase gene, were co-transfected into cells using X-tremeGENE HP DNA Transfection Reagent (Sigma-Aldrich), in accordance with the manufacturer’s protocol. For differentiated samples, the growth medium was changed to the differentiation medium the next day. The transfected cells were then incubated with or without PA for 24 h until the cells were harvested, and the luciferase activity was measured using the Dual-Luciferase Reporter Assay System (Promega). The values were expressed as a fold induction and were corrected for transfection efficiency using Renilla luciferase activity. The experiments were performed in duplicate and were repeated three times independently. ## 4.8. Statistical Analysis The data are expressed as the mean ± standard error of the mean (SEM). All statistical analyses were performed using SPSS Statistics for Windows (version 24; SPSS Inc., Chicago, IL, USA). An unpaired Student’s t-test was used to identify significant differences between the two groups. A one-way ANOVA, followed by Tukey’s post-hoc test, was performed to determine differences among three or more groups. A two-way ANOVA was used to determine interactions between two independent variables. 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--- title: Glycoursodeoxycholic acid regulates bile acids level and alters gut microbiota and glycolipid metabolism to attenuate diabetes authors: - Bingting Chen - Yu Bai - Fenglian Tong - Junlin Yan - Rui Zhang - Yewei Zhong - Huiwen Tan - Xiaoli Ma journal: Gut Microbes year: 2023 pmcid: PMC10054359 doi: 10.1080/19490976.2023.2192155 license: CC BY 4.0 --- # Glycoursodeoxycholic acid regulates bile acids level and alters gut microbiota and glycolipid metabolism to attenuate diabetes ## ABSTRACT Accumulating evidence suggests that the bile acid regulates type 2 diabetes mellitus (T2DM) through gut microbiota-host interactions. However, the mechanisms underlying such interactions have been unclear. Here, we found that glycoursodeoxycholic acid (GUDCA) positively regulates gut microbiota by altering bile acid metabolism. GUDCA in mice resulted in higher taurolithocholic acid (TLCA) level and *Bacteroides vulgatus* abundance. Together, these changes resulted in the activation of the adipose G-protein-coupled bile acid receptor, GPBAR1 (TGR5) and upregulated expression of uncoupling protein UCP-1, resulting in elevation of white adipose tissue thermogenesis. The anti-T2DM effects of GUDCA are linked with the regulation of the bile acid and gut microbiota composition. This study suggests that altering bile acid metabolism, modifying the gut microbiota may be of value for the treatment of T2DM. ## Introduction Type 2 diabetes mellitus (T2DM) is a complex polygenic disease associated with insulin resistance and pancreatic β-cell dysfunction1. In spite of the uncertainty surrounding the pathogenesis of T2DM, more and more studies have found that bile acids (BAs) and gut microbiota may be involved. In recent years, the gut microbiota is shown to play an important part in the biotransformation and reabsorption of BAs, and acts on host glycolipid and energy metabolism through co-metabolism of BAs2. Sun et al3 showed that intestinal flora and bile acid metabolic pathways are the key mechanisms mediating the hypoglycemic effects of metformin. Therefore, the modulation of host lipid metabolism disorders by BAs-gut microbiota co-metabolism has become a new model for early intervention in type 2 diabetes. Co-metabolic networks between BAs-gut microbiota and the host is considered therapeutic targets for various metabolic diseases. It has been found4 that dysbiosis of the intestinal flora leads to a decrease in secondary bile acid production and thus a decrease in activation of bile acid receptors, which further leads to dysregulated glucose metabolism and T2DM disease. Many bacteria, especially some Clostridium perfringens, have been shown to be active in the conversion of primary bile acids to secondary bile acids5. Bile acids and microbiota interact in a bidirectional manner. Through their ability to promote the development of bacteria associated with bile acid metabolism as well as curb the growth of bile-sensitive germs, bile acids reshape the microbial community in the intestine. When the flow of bile is blocked, bacteria overgrow and overtake the small intestine in biliary obstruction, and the administration of bile acid can reverse the phenotype6. These studies suggest a dynamic interaction between host bile acids and microbial populations in the gut. Therefore, monitoring the composition of bile acids and gut microbiota in human can provide potential help for early diagnosis and treatment of T2DM. After transplantation of intestinal flora from patients with polycystic ovary syndrome into mice using fecal transplantation technique, it was found that the mice showed some degree of disruption of ovarian function and disturbance in the metabolic conversion of bile acids in vivo, Treatment with glycine deoxycholic acid (GDCA) could alter bile acid metabolism and intestinal flora to improve the disease7. Therefore, targeting bile acids to modulate bile acid-gut microbiota could be a potential treatment for metabolic diseases. The efficacy of glycoursodeoxycholic acid (GUDCA) therapy to delay disease progression has been demonstrated8,9, and oral supplementation of GUDCA may have potential translational value in the clinical management of T2DM3, but whether GUDCA can improve glucolipid metabolism in diabetes through modulation of bile acid-gut microbiota metabolism has not been reported. In the present study, we investigated the differences of bile acids and intestinal microflora in type 2 diabetic patients with normal controls by metabonomics-high-throughput sequencing. Then, the effects of GUDCA on glucose and lipid metabolism in db/db mice were further studied and the underlying mechanisms were elucidated. Results showed that GUDCA is effective at intervening T2DM by modulating bile acids-gut microbiota, which providing insights into the mechanism of its action as well as guiding future studies about its prospective applications in the therapy of metabolic disorders. ## Bile acids and gut microbiota alterations between T2DM patients and healthy controls To investigate how bile acids and intestinal flora are altered in the organism of T2DM patients, we collected serum from 30 patients and stool from 15 patients. In two independent cohorts (Figure 1(a); Table S1), 29 bile acids were detected. Orthogonal projections to latent structures- discriminant analysis (OPLS-DA) showed that there was a trend to differentiate the bile acid metabolic profile between the T2DM and normal groups (Figure 1(b)). Qualitative and quantitative analysis of bile acid species indicated that deoxycholic acid (DCA), lithocholic acid (LCA) and glycodeoxycholic acid (GDCA) were considerably elevated in the T2DM group compared with the control group in the serum. Notably, we observed that glycoursodeoxycholic acid (GUDCA) was significantly decreased in T2DM group (Figure 1(c)). In addition, we performed a receiver-operating characteristic (ROC) analysis and observed that the proportion of GUDCA had good performance in predicting T2DM subjects (AUC = 0.63, $95\%$CI:0.50–0.77, p<0.05) (Figure 1(d)). ACE, Chao1, and Shannon indices revealed no notable differences between the two groups in terms of α diversity (Figure S1(a)). Notably, the β-diversity of microbial communities in the T2DM group was significantly lower compared to the normal group, indicating that the T2DM individual communities were more homogeneous ($p \leq 0.05$; Figure S1(b)). Analysis with the linear discriminant analysis (LDA) suggested that *Akkermansia muciniphila* was keystone species in the normal group while *Klebsiella pneumoniae* was considered as the potential biomarker for the T2DM (Figures 1(e)). Detection of abundances at the species level further supported the above observation, in other words, less abundance of B. vulgates and A. muciniphila but more of K. pneumoniae was showed in T2DM group (Figure 1(f)). Figure 1.Profile of the bile acids and gut microbiota in individuals with T2DM. a Sex proportions and FBG distribution in T2DM and Control. b OPLS-DA plot of bile acids levels in T2DM (blue) and Control (orange). c Determination of serum bile acids in T2DM and Control group. P values were analyzed by two-tailed Mann–Whitney U-test and data were presented as medians. d ROC of GUDCA in predicting T2DM. AUC: area under curve. e Analysis with the linear discriminant analysis (LDA). Green indicates enriched taxa in the T2DM group. Red indicates enriched taxa in the Control group. f Different species abundance of T2DM and Control based on metagenomics data. $$n = 15$$ individuals/groups. * p<0.05,**p<0.01. ## GUDCA regulates blood glucose and lipid levels To explore the impact of GUDCA on metabolic diseases, db/db mice were gavaged with GUDCA for 8 weeks and their glucose and lipid levels were observed. We found that there was no alteration in food intake, water intake and body weight gain (Figures S2(a-b)). After GUDCA supplementation, db/db+GUDCA mice showed a significant decrease in blood glucose at weeks 2 and 8 (Figure 2(a)). At the same time, glucose tolerance test (GTT) and insulin tolerance test (ITT) results, insulin levels, and HOMA-IR indices in db/db+GUDCA mice were decreased compared with db/db+Veh group (Figures 2(b-d), S2(c)). Research also indicated that lipid levels (TC, TG) in serum had significantly decreased in db/db+GUDCA mice compared with db/db mice. ( Figure 2(e)). Furthermore, we found that GUDCA was able to reduce the level of serum GLP-1 compared with db/db+Veh group. ( Figure 2(f)). Figure 2.GUDCA supplementation had therapeutic effects in improving glucose tolerance. a Fasting blood glucose. b, c OGTT, ITT and AUC. Vehicle or GUDCA-treated (100 mg/kg/d) mice on db/db mice for 8 weeks. $$n = 10$$ mice in m/m group, $$n = 9$$ mice in db/db+veh and db/db+gudca groups. All P values were analyzed by two-tailed Student’s t-test, **$p \leq 0.01$ versus m/m; #$p \leq 0.05$, ##$p \leq 0.01$ versus db/db+veh. All data are presented as the mean ± sd. d HOMA-IR. E TC and TG in the serum. f Serum active GLP1 levels. $$n = 8$$ mice/group. All P values were analyzed by two-tailed Student’s t-test, *$p \leq 0.05$, **$p \leq 0.01.$ *All data* are presented as the mean ± sd. ## Liver lipid profiles, oxidative stress and histopathology The levels of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were decreased after GUDCA supplementation, indicating that liver function impairment was improved in db/db mice to some extent (Figure S2(d)). TC and TG levels in the livers of mice fed with GUDCA were decreased significantly compared with the db/db+Veh group (Figure S2(e)). Diabetes, for instance, is a result of oxidative stress, which plays an integral role in the development of a wide range of diseases. We found that the SOD levels were significantly decreased and MDA levels were significantly increased in db/db mice compared with m/m mice, indicating that a certain degree of oxidative damage existed in the liver tissues of db/db mice. At the same time, GUDCA administration was able to improve the oxidative stress damage to some extend by elevating GSH and decreasing MDA levels (Figure 3(a)). However, there is no significantly increased in SOD and CAT in liver after GUDCA administration. GUDCA-treated mice displayed improved morphology in their livers. A histological examination of liver specimens found cellular swelling and lipid vacuoles in the db/db group as compared to the m/m group. Hepatocytes in the GUDCA group were more normal in structure, with intact cell morphology and significantly fewer vacuoles, tending to be normal hepatocytes (Figure 3(b)). The above observations indicate that GUDCA could reduce oxidative stress injury to a certain extent and have a protective effect on liver tissue. Figure 3.The physiological changes in m/m, db/db+veh and db/db+gudca. a Oxidative stress in liver. All p values were determined by two-tailed Student’s t-test, *$p \leq 0.05$, **$p \leq 0.01.$ *All data* are presented as the mean ± sd. $$n = 6$$ mice/group. b Representative images of H&E staining of Liver, scale bars, 25μm c Representative images of H&E staining of WAT, scale bars, 50μm. d Electron microscope of Ileum, Scale bars,50000x. ## Dynamic change of BAs profile in serum Ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was utilized to assess serum BAs profiles in the mice. As can be seen from the results of the OPLS-DA model, a clear separation between the m/m mice and db/db+Veh mice were observed. Similarly, a separation trend between the db/db+Veh group and db/db+GUDCA group was also discovered (Figure 4(a)). As a result of the serum BA profiles of the OPLS-DA, there was a significant difference between groups db/db+Veh and db/db+GUDCA because TLCA ranked higher in the VIP scores (Figure 4(b)). A summary of serum BA concentrations is shown in Table S2. Results showed that TCA、GCA、TCDCA、TDCA were significantly increased in db/db+Veh group. Compared with the m/m group, the ratios of PBAs to SBAs (PBA/SBA ratio) were elevated in db/db mice. Further, the levels of secondary BAs, conjugated BAs and taurine BAs increased, whereas PBA/SBA ratio decreased after GUDCA treatment (Figure 4(c-d)).In addition, we found that UDCA、LCA、TCDCA、TUDCA、GUDCA、TLCA, isoLCA, T-α-MCA were significantly increased in the db/db+GUDCA group and furthermore, all these differential BAs belonged to the category of non-12α-OH BAs (Figure 4(e)). 10 of the 29 bile acids detected in db/db+Veh group were upregulated and 19 were downregulated, and an increase in 18 bile acids could be observed after GUDCA administration, with significant differences in metabolite levels among three groups (Figure S3). Then, Spearman correlation analysis were executed to illuminate the coefficients between serum BAs and serum indicators for the three groups. *In* general, a majority of the BAs were significantly negatively correlated with GLP-1. Moreover, PBA/SBA had a positive correlation with blood biochemical parameters, including TC、TG、LDL、HDL、GLU、INS (Figure 4(f)). Figure 4.Dysregulated BA profiles in m/m, db/db+veh and db/db+gudca. a Orthogonal partial least squared-discriminant analysis (OPLS-DA) scores plot of serum BA profiles showing the group of m/m (blue) group, db/db+veh (red) and db/db+gudca (green). b the variable importance in projection (VIP) scores from OPLS-DA model based on the serum BA profiles between the db/db+veh and db/db+gudca group. c, d, e Profiles of BAs in the db/db+veh group. * $p \leq 0.05$, **$p \leq 0.01.$ *All data* are presented as the mean ± sd. f Heatmap of spearman correlation association between serum BAs and blood indicators from three groups. * $p \leq 0.05.$ ## Changes in intestinal mucosal barrier The levels of diamine oxidase (DAO) and D-lactic acid (D-LA) in the serum of mice in db/db+Veh group were increased significantly ($p \leq 0.01$) compared with the m/m group. The DAO and D-LA levels in the db/db+GUDCA group were $20.8\%$ and $24.3\%$ lower than in the db/db+Veh group ($p \leq 0.01$), respectively (Figure S4(a)). Transmission electron microscopy was applied to inspect the function of ileum in mice. The results revealed that the microvilli in the m/m group were intact and tightly arranged, whereas the microvilli were disorganized and incomplete in the db/db group, with coupled microvilli that were dislodged into the intestinal lumen. Surprisingly, the mice treated with GUDCA had lower injury in ileum, which indicated GUDCA could improve the abnormal intestinal mucosal barrier and protect the imbalance of intestinal homeostasis (Figure 3(d)). ## The structure of the gut microbiota The Venn diagram showed that 7971 OTUs were shared across the three groups (Figure S4(b)). There was significant difference between db/db+Veh and db/db+GUDCA group in α diversity, as indicated by the decrease of chao-1 indices and observed_species (Figure 5(a)). The β-diversity indicated that the composition and abundance of microbiota after GUDCA administration tended to the m/m mice, which was significantly different from the db/db+Veh group ($p \leq 0.05$; Figure 5(b)). Linear discriminant analysis (LDA) displayed that the db/db+Veh group was characterized by *Pseudomonas corrugata* and Arthrobacter citreus, then *Bacteroides vulgatus* was considered as the key species in the db/db+GUDCA group (Figure 5(c)). Meanwhile, in the analysis of species abundance in each group, we found that the abundance of *Pseudomonas corrugata* decreased and *Bacteroides vulgatus* increased in db/db+GUDCA group compared with the model group (Figure 5(e)). In addition, we analyzed the levels of short-chain fatty acids in the feces by using gas chromatography. The results revealed that the levels of acetic acid and propionic acid decreased in the db/db+Veh group, and GUDCA administration was able to reverse the trend of decreasing acetic acid and propionic acid (Figure S4(c)). The Firmicutes and Bacteroidota are the dominant phylum in the intestine that produce SCFAs, and in this study, the relative abundance of the Firmicutes and Bacteroidota was found to be elevated in the GUDCA group compared to the model group (Figure 5(d)). Figure 5.GUDCA modulates the composition of gut commensal bacteria. a α-diversity of the gut microbiota, as indicated by the Shannon, Chao1 indices and observed species. b Principle coordinate analysis (PCOA) plot generated using OTU metrics based on the Binary-Jaccard similarity for m/m, db/db+veh and db/db+gudca groups. c Taxonomic cladogram generated from LEfSe of metagenomic sequencing data. Blue indicates enriched taxa in the m/m group. Red indicates enriched taxa in the db/db+veh group. Green indicates enriched taxa in the db/db+gudca group. d the relative abundance of phylum level in the db/db+veh group. e Dysregulated gut microbiota in the db/db+veh group. * $p \leq 0.05$, **$p \leq 0.01.$ P values were determined by two-tailed Mann–Whitney U-test and data are presented as the mean ± sd. f Heatmap of spearman correlation coefficients between serum BAs and blood biochemical parameters from all samples in the three groups. * $p \leq 0.05$(spearman’s correlation with the post hoc correction using the Holm method). g Kyoto Encyclopedia of Genes and Genomes annotation of key altered metabolic pathways in three groups. Spearman correlation analysis of intestinal flora and bile acids (Figure 5(f)) showed that Faecalibacterium_prausnitzii correlated with multiple bile acids. Bacteroides vulgatus had positively correlated with the levels of TLCA, non 12α-OH BAs, and *Pseudomonas corrugata* had a positive correlation with elevated relative abundance of 12α-OH/non 12α-OH BAs, PBA/SBA in db/db+Veh group mice. KEGG analysis revealed that lipid metabolism and carbohydrate metabolism were the key metabolic pathways influenced by the gut microbiota changes found in the mice. ## GUDCA ameliorated metabolism by promoting fat thermogenesis In order to investigate whether GUDCA can improve obesity in db/db mice by affecting adipose function, white adipose from mice was taken for study. The white adipocytes in the db/db group were swollen and ruptured with increased lipid droplets, surprisingly, the cell morphology was intact and the adipocytes were not ruptured after GUDCA administration (Figure 3(c)). UCP1 was significantly higher in the db/db+GUDCA group compared with the db/db+Veh group ($p \leq 0.01$). Also, we found that PGC-1α in the white adipose tissue of db/db+Veh mice was decreased compared with the m/m group ($p \leq 0.05$), and GUDCA had a tendency to elevate PGC-1α but no significant difference ($p \leq 0.05$; Figure 6(a)). In addition, we also found elevated expression of white adipose TGR5 on mRNA (Figure 6(b)). Figure 6.GUDCA ameliorated metabolism by promoting fat thermogenesis. A: Western blot analysis of UCP1 and PGC-1 in white adipose tissues. B: Relative mRNA expression of TGR5. * $p \leq 0.05$, **$p \leq 0.01.$ *All data* are presented as the mean ± sd. ## Discussion The close association between bile acid metabolism and gut microbiota plays an important role in the regulation of immune function, maintenance of host nutrient metabolism and energy balance, and health of the organism10. Currently, the research of gut microbiota and bile acid metabolism for the treatment and prevention of metabolic diseases, including obesity, diabetes, inflammation and NAFLD11,12, has become a research direction. In this study, we investigated the differences between bile acids and gut microbiota in type 2 diabetes mellitus and normal subjects by means of metabolomics-high-throughput sequencing, and then further investigated the effects of GUDCA on glucolipid metabolism in db/db mice and elucidated the potential mechanisms. It has been demonstrated that the characteristics of BA show significant changes in patients with type 2 diabetes13,14. In present study, we used multivariate statistical analysis of serum bile acids in type 2 diabetes and found a significant decrease in GUDCA in the serum of diabetic patients compared to normal subjects, which can be used as a potential marker for clinical diagnosis and treatment. We also found that there was a dynamic interaction between bile acids and microbial populations in the intestine. Using metformin to treat patients with T2DM, Sun et al3found that levels of GUDCA increased in the gut, which was in line with our research. They also indicated that metformin was able to reduce *Bacteroides fragilis* in the gut, however, we found that a corresponding decrease in *Bacteroides vulgatus* occurred in the intestine of type 2 diabetic patients. The use of bile acids as targeted agents for the treatment of hepatobiliary diseases has become a hot research topic in recent years after UDCA was approved by the U.S. Food and Drug Administration (FDA) for the treatment of primary cholangitis15. Feeding cholic acids (CA) to rats was able to significantly alter the microbiota at the phylum level, leading to an increase in Firmicutes and a corresponding decrease in Bacteroidota 16. A short-term study of UDCA revealed that it was able to increase hepatic triglyceride (TG) levels17 and tauroursodeoxycholic acid (TUDCA) has been shown to be effective in preventing inflammation and improving insulin sensitivity18,19. Supplementation with glycoursodeoxycholic acid (GUDCA) can come to inhibit the intestinal FXR axis, which can reduce blood ceramide levels and thus reduce atherosclerosis in ApoE-/- model mice on a high cholesterol diet20. In this study, GUDCA treatment was found to be therapeutically effective in the metabolic disorders of db/db mice. GUDCA decreased blood glucose and reduced serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels in db/db mice, indicating that GUDCA has a hepatoprotective effect. GUDCA was associated with glucose control21, which was also indicated in our study. We also found that GUDCA significantly reduced the serum and liver levels of TC and TG in db/db mice after continuous administration. Insulin resistance is a key pathogenic factor in the development of diabetes mellitus, so, improving insulin resistance plays an important role in the treatment of diabetes mellitus22. The findings indicated that serum insulin levels were elevated in db/db mice, GUDCA decreased serum insulin levels and HOMA-IR in db/db mice. High levels of insulin concentrations could be attributed to increased insulin secretion or decreased insulin clearance23, oxidative stress is considered to be one of the most critical mechanisms of insulin resistance24. Elevated levels of oxidative stress may be a major deleterious factor contributing to insulin resistance, β-cell dysfunction, impaired glucose tolerance, and dyslipidemia25–27. In this study, SOD activity decreased and MDA content increased in the liver of db/db mice compared with the normal group was found, and then GUDCA could increase GSH and decrease MDA content, effectively improving oxidative stress damage and reducing insulin resistance in the organism. Changes in the composition of the BA pool are associated with metabolic disorders28. In our experiments, serum bile acids in db/db mice underwent significant changes, mainly in the upregulation of UDCA with its taurine and glycine conjugates (TUDCA, GUDCA) and LCA with its conjugates (isoLCA, TLCA) after eight weeks of GUDCA intervention. TLCA, an agonist of TGR5, made the largest contribution in the db/db+Veh group and db/db+GUDCA group. TGR5 is a receptor that positively regulates energy metabolism, and studies have shown that secondary bile acids have a higher affinity for TGR5 than primary bile acids. By activating TGR5 are able to induce GLP-1 secretion in the intestine and thermogenic energy expenditure in brown fat and skeletal muscle, thereby improving glucose and energy homeostasis29. Thus, we hypothesized that after administration of GUDCA, GUDCA is changed to UDCA in vivo by choline hydrolase (BSH), UDCA is rapidly metabolized to LCA by bacterial hydroxysteroid dehydrogenase. Exogenous supplementation of GUDCA to regulate glucolipid metabolism may be associated with increased TLCA. The gut microbiota plays an irreplaceable role in human physiology and pathology30. Microbial dysbiosis includes imbalance in the distribution of bacterial populations and impaired bacterial metabolic activity, which can increase intestinal permeability and thus lead to multiple disorders31,32. In a correlation analysis between bile acids and gut microbiota, the abundance of B. vulgatus was found to be positively correlated with TLCA. BSH is present in B. vulgatus, and BSH catalyzes the hydrolysis of conjugated bile salts to form amino acids and free bile acids, thus serving to maintain the balance of bile acid metabolism33. White fat is a type of adipose tissue in the human body, and the accumulation of large amounts of white fat leads to obesity. Virtue34 showed that indole-3-carboxylic acid (I3CA) and indole, tryptophan metabolites of gut microbiota, can significantly inhibit miR-181 expression thereby regulating white fat for weight loss. A study by Wu found that intestinal HIF-2α-specific knockdown could promote white fat thermogenesis and improve obesity by modulating the intestinal lactate-B. vulgatus-bile acid-adipose TGR5 signaling pathway35. Several researches have suggested that GUDCA can ameliorates diseases by regulating FXR3,20,36. Nevertheless, in present research, we found that GUDCA could activate TGR5 expression on mRNA in white adipose tissue and promote white adipose thermogenesis. Further, we hypothesized that GUDCA may provide a new target and intervention strategy for the prevention and treatment of obesity and related metabolic diseases by regulating the TLCA-B.vulgatus-adipose TGR5 signaling pathway to promote adipose thermogenesis and improve glucolipid metabolism. However, we still need to do a lot of experiments to test our hypothesis. There are several limitations in our study. First, all subjects in the study were recruited in a single region. Different dietary can have an impact on the composition of the gut microbiota. Moreover, the number of feces samples was small, which make the data are not representative enough. Second, it remains unclear whether altered GUDCA level directly mediates changes in gut microbiota on diabetes prevention. To understand how gut microbiota protects against diabetes as a result of GUDCA-related bacteria, future studies in germ-free mouse fecal microbiota transplantation need to be conducted. Third, there is a disparity in gut microbiota composition between mice and humans37,38, which makes it difficult to clarify how GUDCA influences gut microbiota in humans. In addition, GUDCA’s safety and effectiveness, however, remain to be determined in the future due to the lack of clinical evidence. In conclusion, GUDCA supplementation modulates the abundance of gut microbiota, upregulate beneficial bacteria, and alter the bile acid metabolic profile to some extent. Additionally, GUDCA can also activate white fat TGR5 and increase lipid thermogenesis. GUDCA signaling is expected to be a prospective target for the therapy of human metabolic diseases. ## Human subjects Human serum samples were collected from 30 people with T2DM and 50 healthy subjects. For serum extraction, all blood samples were centrifuged for 20 minutes at 3500 rpm after 30 minutes at room temperature.15 individuals with T2DM and 15 controls were recruited to collect feces. Feces samples were collected with a sterile spoon and stored at − 80°C until analysis. All of the subjects enrolled satisfied the diagnostic criteria by American Diabetes Association (ADA) in 2021: FPG≥7.0 mmol/L or 2-h PG ≥11.1 mmol/L or A1C ≥ $6.5\%$. The exclusion criteria were: type 1 diabetes; gestational diabetes; pregnancy; no antibiotic and probiotics use within 3 months; gastrointestinal diseases; mental illness; and alcoholism. Clinical parameters were determined at The Fourth Affiliated Hospital of Xinjiang Medical University. The demographic characteristics, lipid analysis and insulin relative indicators of cohort involved in the research are listed in Supplementary Table 1. The study protocol was approved by the Ethics Committees of Xinjiang Medical University (Permission number:20140304–133). All participants provided written informed consent. ## Mice Male C57BL/Ksj-db/db mice (35–45 g, 6–8 weeks old) and C57BL/Ksj-m/m mice (20-23 g, 6–8 weeks old) were purchased from Changzhou Cavens Model Animal Co.,Ltd with the permission number SCXK 2016–0010. After two weeks of adaptive feeding under a 12 h light/dark cycle at 21 ± 2°C with enough food and water, the mice were randomly divided into 3 groups. The study protocol followed international ethical guidelines and was approved by the Animal Care and Use Committee of Xinjiang Medical University. The m/m mice ($$n = 10$$) and db/db mice ($$n = 10$$) were fed a standard chow diet and drinking water with vehicle for 8 weeks. At the same time, ten db/db mice were fed a standard chow diet and given 100 mg/kg/d GUDCA (Sigma-Aldrich, Cat# 06863) by gavage for 8 weeks. Weekly measurements of body weight, food and drink intake, and blood glucose were taken during experiments. Stool samples were collected during the last week and stored at−80°C until the analysis. All mice were fasted and water was available for 16 hours before death. The blood samples were collected and centrifuged at 3500rpm for 15 min at 4°C to obtain the serum. Liver, ileum, and white adipose were immediately collected after excision. The tissues were stored at−80°C until further analysis or in $4\%$ paraformaldehyde and $2.5\%$ glutaraldehyde for histological and transmission electron microscopy studies. ## Bile acid analysis Bile acids were quantified with a UPLC/MS-MS system (Agilent, Thermo Fisher Scientific, USA) with an ESI source 39. Taurochenodeoxycholic acid (TCDCA-d4) was used as internal standards. An Acquity BEH C18 column (100 mm × 2.1 mm i.d., 1.7 μm, Waters Corp.) was used at the temperature of 45°C, and the flow rate of 0.4 ml/min for liquid chromatography separation. The solvent of the mobile phase was a mixture of $0.1\%$ acetic acid in water and acetonitrile. The gradient elution was applied and MS detection proceeded in negative mode. A Q Exactive Focus mass spectrometer (Thermo Fisher Scientific) was applied for assay development in Parallel Reaction Monitoring (PRM) mode40. ## Multivariate analysis Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) was used to determine taxonomic changes, and VIP (variable importance) scores were adopted to rank the ability of different taxa to discriminate between different groups41. The results of the differential metabolite screening were visualized as a volcano plot. Then, the Euclidean distance matrix was calculated, and the differential metabolites were clustered by the complete chain method and presented as a heat map. Receiver operating characteristic (ROC) curve were plotted and calculated its area under the curve to obtain potential biomarkers (performed using the vegan package in R 3.4.0). ## DNA extraction and preparation Genomic DNA from human and mouse stool samples was extracted using Magnetic Soil and Stool DNA Kit (Tiangen biotech Co. Ltd., Beijing, China). Degradation and contamination of DNA were monitored on $1\%$ agarose gels. DNA concentrations were measured using a NanoDrop system (Thermo Fisher Scientific), and the DNA molecular size was estimated by agarose gel electrophoresis. ## Metagenomics sequencing Metagenomics sequencing was measured as previously described42. In brief, the V3-V4 region of the bacterial rRNA gene was amplified by polymerase chain reaction (PCR; 98°C for 1 min, followed by 30 cycles of 98°C for 10 s, 50°C for 30 s and 72°C for 30 s and a final extension at 72°C for 5 min) using the primers 515F (5’-GTGCCAGCMCCGCGGTAA-3’) and 806 R(5’-GGACTACHVGGGTWTCTAAT-3’). Mixture PCR products was purified with GeneJET Gel Extraction Kit (Thermo Scientific). Sequences with a primary band size between 400-450bp was selected and then cut the gum to recover the target bands. Sequencing libraries were constructed using Illumina TruSeq DNA PCR-Free Library Preparation Kit (Illumina, USA). The library quality was tested on the Qubit@ 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2100 system. At last, the library was sequenced on an Illumina NovaSeq platform and 250 bp paired-end reads were generated. ## Metagenomics analysis Paired-end reads from the original DNA fragments are merged by using FLASH (https://www.flash.cn/). Paired-end reads was assigned to each sample according to the unique barcodes. Sequences were analyzed using QIIME (http://qiime.org/) software package, and in-house Perl scripts were used to analyze alpha- (within samples) and beta- (among samples) diversity. Sequences with≥$97\%$ similarity were assigned to the same OTUs. We pick a representative sequence for each OTU and use the RDP classifier to annotate taxonomic information for each representative sequence. Alpha diversity analyses (ACE and Shannon) were calculated using Mothurb.1.30.1 (http://.mothur.org/). The relative abundance was evaluated using the vegan package of R software. A heatmap based on the relative OTU abundance was generated using the gplot package of R software and the color of the heatmap is displayed as logarithmic values. Analyses of principal coordinate analysis (PCoA) by Bray-Curtis dissimilarity was performed using Mothurb.1.30.1 (http://.mothur.org/)43–45. KEGG pathway was performed using in KEGG Pathway Database (http://www.kegg.jp/kegg/pathway.html)46.Spearman correlation analysis was performed, and only correlations with $p \leq 0.05$ and r > 0.5 are displayed. ## Metabolic assays Glucose tolerance tests were performed after 16–18 h fasting. Blood glucose concentrations were measured with a glucometer, and blood samples were taken from the tail tip at 0, 15, 45, 90 and 120 min after oral glucose (2 g/kg body weight). For the insulin tolerance test, insulin (0.75 U/kg body weight) was administered via intraperitoneal injection after 4 h fasting and tail sampling was performed at 0, 40, 90 and 120 min. All of the ITT and GTT tests were performed at indicated times. ## Biochemical analyses The total triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), alanine transaminase (ALT) and aspartate transaminase (AST) levels in the plasma and the hepatic TC and TG levels were measured with commercially available kits (Jiancheng Institute of Biotechnology, Nanjing, China). The levels of Diamine oxidase (DAO) and D-lactic acid (D-LA) in the serum were assayed using commercially available kits (Sino Best Biological Technology Co., Ltd., Shanghai, China). Insulin (mlbio Co, Ltd., Shanghai, China) was determined by enzyme-linked immunosorbent assay kits for mice. The levels of superoxide Dismutase (SOD), glutathione (GSH), malondialdehyde (MDA) and catalase (CAT) in the liver were assayed to evaluate the oxidative stress using commercially available kits (Solarbio Co, Ltd., Beijing, China). ## Serum active GLP-1 detection Vehicle- or GUDCA- (100 mg/kg/d) treated mice for 3 weeks received sitagliptin (25 mg/kg, DPP4 inhibitor) by gavage 1 h before serum collection and oral glucose (2 g/kg) challenge 15 min before serum collection3. Serum active GLP1 levels were measured by GLP-1 ELISA assay kit (Shanghai Enzyme-linked Biotechnology Co., Ltd). ## Histological analysis Liver and adipose tissues were fixed in $4\%$ paraformaldehyde, and paraffin sections were cut, 3 mm thick were stained with hematoxylin-eosin (HE) and Sirius red. The stained samples were observed with an optical microscope at 200× magnification. Ileum was fixed in $2.5\%$ glutaraldehyde for transmission electron microscopy. ## Fecal SCFA quantification Vortex 1 mL of acetic acid, propionic acid and butyric acid, dilute them with ultrapure water, and add the appropriate amount to a centrifuge tube containing 2-ethylbutyric acid and mix. 600 μL ethyl acetate and 120 μL IS (500 μg/mL 2-ethylbutyric acid) was added to 20 mg of feces, and the sample was homogenized for 10 min, and then centrifuged at 12000rpm at 4°C for 10 min. An appropriate amount of fecal supernatant was transferred to a 1.5 mL EP tube and passed through a 0.22 μm filter membrane, which was subsequently used to top up the sample. The fecal SCFA analysis was performed by gas chromatography (GC) analysis (Shimadzu, 2010plus). Chromatographic separation was achieved on RTS-WAX column (30 m × 250 μm × 0.25 μm; GL science) coupled to a flame ionization detector (FID). The initial temperature was 100°C, and the temperature was increased to 250°C at 20°C/min and maintained for 1 min. The FID temperature and inlet temperature were set at 230°C and 250°C, respectively. An autosampler (AOC-20i) was employed with an injection volume of 10 μL. ## Real-time PCR analysis Real-time qPCR analysis was performed using the SYBR Green PCR master mix (Invitrogen) using the ABI 7500 real-time PCR system (Applied Biosystems). A standard phenol-chloroform extraction was performed to isolate total RNA from frozen tissues with Trizol reagent. cDNA was synthesized from 2 μg of total RNA with a PrimeScriptTM RT reagent Kit (Takara bio, Beijing, China)47. The sequences of the forward and reverse primer for β-actin were 5’-GGCTGTATTCCCCTCCATCG-3’ and 5’-CCAGTTGGTAACAATGCCATGT-3’. The sequences of the forward and reverse primer for TGR5 were 5’-TGCTTCCTAAGCCTACTACT-3’ and 5’-CTGATGGTTCCGGCTCCATAG −3’ respectively. The amplification thermal cycling conditions were as follows: 95°C for 30 s, 40 cycles at 95°C for 5 s and 60°C for 34 s. ## Western blot analysis UPC1 (1:5,000, Ab209483) and PGC-1α (1:1,000, Ab188102) were purchased from Abcam Co. Ltd., CA, USA. The primary antibody against b-actin (1:10000, bs-0061 R) and secondary antibodies against rabbit (1:50000, bs-0295 G-HRP) were purchased from Bioss Co. Ltd., Beijing, China. Adipose tissues were homogenized in RIPA buffer with protease and phosphatase inhibitors; the protein extracts were separated by SDSPAGE electrophoresis and transferred to a PVDF membrane. Membranes were blocked with $5\%$ nonfat milk for 2 h at room temperature in TBST buffer (10 mM Tris, 150 mM NaCl, pH 7.6, and $0.1\%$ Tween 20) and probed with primary antibodies overnight at 4°C. Membranes were then incubated with horseradish peroxidase-conjugated secondary antibodies. The protein bands were developed using an ECL kit (Biosharp Co. Ltd., Anhui, China). The densitometry analysis of the bands was performed using a gel documentation system (Gel Analyzer, ShineTech, Beijing, China). ## Statistical analysis Statistical analyses were performed using SPSS 22.0, and results are presented as means ± standard errors or means ± standard deviation. Two-tailed unpaired Student’s t-test and one-way ANOVA with Tukey’s correction were used for all comparisons of mice-related experiments, and a Wilcoxon matched-pairs signed rank test was used for clinical indicators in individuals with T2DM. P values<0.05 were considered significant. Correlation analysis of bile acid and gut microbiota were investigated using nonparametric Spearman’s test. ## Disclosure statement No potential conflict of interest was reported by the authors. ## Author contributions M-X.L. conceived and designed the research. C-B.T. and B.Y. performed the experiments and the statistical analyses. T-F.L. and Y-J.L. helped with the animal experiments and analyzed the data. 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--- title: Behavior-Based Video Summarization System for Dog Health and Welfare Monitoring authors: - Othmane Atif - Jonguk Lee - Daihee Park - Yongwha Chung journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10054391 doi: 10.3390/s23062892 license: CC BY 4.0 --- # Behavior-Based Video Summarization System for Dog Health and Welfare Monitoring ## Abstract The popularity of dogs has been increasing owing to factors such as the physical and mental health benefits associated with raising them. While owners care about their dogs’ health and welfare, it is difficult for them to assess these, and frequent veterinary checkups represent a growing financial burden. In this study, we propose a behavior-based video summarization and visualization system for monitoring a dog’s behavioral patterns to help assess its health and welfare. The system proceeds in four modules: [1] a video data collection and preprocessing module; [2] an object detection-based module for retrieving image sequences where the dog is alone and cropping them to reduce background noise; [3] a dog behavior recognition module using two-stream EfficientNetV2 to extract appearance and motion features from the cropped images and their respective optical flow, followed by a long short-term memory (LSTM) model to recognize the dog’s behaviors; and [4] a summarization and visualization module to provide effective visual summaries of the dog’s location and behavior information to help assess and understand its health and welfare. The experimental results show that the system achieved an average F1 score of 0.955 for behavior recognition, with an execution time allowing real-time processing, while the summarization and visualization results demonstrate how the system can help owners assess and understand their dog’s health and welfare. ## 1. Introduction At the beginning of the 20th century, structural changes in South Korea’s society, such as the spread of individualism, the rise in divorce rates, and the decline in fertility rates, contributed to the aging of the population and a significant increase in single-person households [1]. For people living alone, to cope with loneliness, many opted for raising pets to serve as an alternative to family members and help them with stress [2,3]. This led to an increase in the number of households with pets from 3.59 million in 2012 to 6.04 million in 2020, which represents $30\%$ of the country’s households [4,5]. Among the pets commonly owned, dogs are a popular choice because of the benefits associated with raising them. They motivate to engage in activities, such as walking and exercising together, helping owners sustain their physical [6,7,8] and mental health [9,10,11]. In fact, dogs are currently leading the pet market in South Korea, with a total of approximately 5.2 million raised in 2021 and a presence in $80\%$ of households with pets [4,12]. However, while the number of dogs raised remained relatively stable between 2019 and 2020 [13], data from the Korea Data Exchange (DEX) showed a $60\%$ increase in veterinary hospital visits during the same period [14]. While this shows that owners care for their dogs’ health and are spending money and time to maintain it [4], the increasing veterinary costs have reached an average of $72 per visit, which represents a burden for more than $82\%$ of owners [15]. This financial burden increases when owners take their dogs for random checkups in the hope of discovering and treating health issues. For these reasons, owners need to better understand the health (physical and mental) and welfare of their dogs so as to limit veterinary visits to the necessary ones, rather than performing frequent checkups. Although medical conditions of some dogs require tests and expert opinions for diagnosis, research has shown that there exists a strong bond between a dog’s welfare and health and its behavior [16,17,18,19]. In fact, not only can monitoring a dog’s behavior help the owner understand their pet’s health state and improve the accuracy of the expert’s diagnosis, but in some cases, behavior is the only clinical sign that experts can rely on [20,21,22]. Thus, monitoring dogs’ behavioral information is necessary because—when accurately collected—such data can help the owner discover abnormalities and provide useful insight to the expert in making an accurate diagnosis. Consequently, this would help the expert start the treatment early, improving the chances of a quick recovery and reducing veterinary visits, which would relieve some of their financial burden. Although owners generally tend to take notice of their dogs’ behaviors, it is difficult for them to do so constantly, especially since it is common for dogs to be left unattended. For example, in South Korea, dogs spend an average of five to seven hours alone at home [4], a time during which owners cannot directly observe their behaviors [23]. Hence, owners are likely to miss key behavioral signs and pattern changes that can help assess their dogs’ states, especially because some signs are displayed mainly when the dog perceives its owner’s absence [23,24,25]. In fact, dogs with physical and separation-related health issues when left alone tend to display restlessness, increased activity, pacing, and some undesirable behaviors, such as excessive vocalization, unlike healthy dogs, which are likely to mainly show long periods of passive behavior and locomotion [26]. Owing to that, and since the owner’s presence can cause the dog to synchronize its behavior with theirs [27], keep it attentive to the owner and trigger interactions, such as playing, which can affect the dog’s behavior [28], it is important to observe the dog’s behavior when alone and keep track of them [29]. This can provide more consistent information about its behavioral changes. Therefore, in this paper, we propose a method to monitor a dog in an illuminated indoor environment, recognize its behavior, and provide an effective way to visualize it to help owners and experts better understand their health and welfare. After reviewing previous studies on dog behavior recognition, we identified related studies [30,31,32,33,34,35,36,37], which are summarized in Table 1. Different methods have been introduced to recognize dog behavior. In this context, dog behavior refers to static (e.g., sitting and sleeping) and active behaviors (e.g., walking, barking, and jumping). Early methods used statistical classification [30], DTW distance [31], and discriminant analysis [32] to classify selected dog behaviors, providing proof of concept. Later, with the improvement in machine learning techniques and the increase in their popularity in different fields of research [36,38,39,40], more methods have been employed to recognize dog behaviors. For instance, Chambers et al. [ 34] aimed to validate dog behavior recognition, with a focus on eating and drinking, using FilterNet and a large crowd-sourced dataset. Using their method, Aich et al. [ 33] trained an artificial neural network (ANN) on sensor data to detect dog behaviors and classified their emotional states (positive, neutral, or negative) based on their tail movements. In addition, Wang et al. [ 36] classified dogs’ head and body postures separately using long short-term memory (LSTM) on sensor data, and then used complex event processing (CEP) to better differentiate between behaviors with similar body postures. Kim et al. [ 37] used a convolutional neural network (CNN) with LSTM on fused image and wearable sensors data to compensate for the shortcomings of this latter caused by noise in a multimodal system to improve the classification of a dog’s behaviors. By contrast, Fux et al. [ 35] used object detection to track a dog inside a clinical setting, extracted features from its movements, such as straightness, and classified them using random forest to recognize ADHD-like behaviors. While these methods achieved good results, their main purpose was to confirm the possibility of recognizing dog behaviors: they focused mainly on and concluded their work on dog behavior classification. However, with only that as a result, understanding a dog’s health and welfare remains a challenging task for owners, because relying solely on the recognized behaviors and manually reading through them to try to gain insight is impractical, time-consuming and may result in missing important details. Instead, in this paper, we propose a method that provides owners with summarization and visualization of their dog’s recognized behaviors to help them effectively visualize them and perceive important patterns and behavioral changes that would help assess its health and welfare. Furthermore, for better assessment, it is required at times to retrieve and visualize some behaviors to examine their intensity and significance [41,42], which makes it necessary for this method to collect video data as input. Most studies did not consider extracting the dog’s location information, which can be useful in detecting movement patterns [35]. In addition, only a few studies have considered real-time processing, which is needed to ensure quick feedback in cases of an alarming increase in the frequency of poor welfare-related behaviors that require immediate attention [41,42]. Finally, because the owner’s presence can influence the dog, to ensure a consistent observation of behaviors, including a preprocessing step to select only the data where the dog is alone without any person present can provide an additional advantage. This further supports the need for using image data in our system as it facilitates the detection of the presence of subjects of interest (i.e., dogs and people) in the input data. Hence, in this study, to overcome the limitations of previous studies, we used a camera-based system to monitor, recognize, and provide summarization and visualization of a dog’s location and behaviors when left unattended to help effectively understand its health and welfare. Accordingly, the system includes the following features. We propose an end-to-end system for dog video summarization based on detected behaviors and location information. The system uses the object detection model You Only Learn One Representation (YOLOR) to detect the dog’s location, followed by an adapted sequence bounding box matching algorithm to correct missed detections before selecting only sequences of images where the dog is alone. Subsequently, the images are cropped to focus on the dog and a two-stream CNN-LSTM is used for behavior recognition based on RGB and optical flow images. Both outputs from YOLOR and CNN-LSTM are stored as log data and then used to generate graphs to provide effective and efficient visualization summaries for owners and dog experts to assess the dog’s physical and mental health and welfare. ## 2. Related Work The most important task in our system is the summarization of the dog’s video data based on its recognized behaviors to provide a visualization of the results using analytical tools. Thus, to select a suitable approach for this task, we first explored the existing video summarization methods. Video summarization is a research field that aims to create a concise summary of a video by selecting the most important parts. It is generally divided into scene-based, where visual features are extracted to select key frames [43], and content-based [44], which uses information related to the content and semantics in the video, such as objects [45] and actions [46,47]. In terms of action-based summarization, although close to our purpose, the proposed methods mainly targeted humans and relied on motion [46,48], making them unsuitable for our system because we targeted dogs’ behaviors, which include not only actions (active behaviors) but also static behaviors that lack motion. However, because this type of summarization is performed in two steps, action recognition and summarization, by following a similar approach and using a behavior recognition method as a first step, we can achieve our summarization purpose. Accordingly, it is important to select an approach that delivers accurate recognition of dog behavior for our system to ensure good summarization performance. To this end, we examined recent methods used for animal behavior recognition to select a suitable method for dog behaviors and found that models based on the CNN-LSTM approach have been widely used for their performance. For instance, Chen et al. [ 49] used VGG16-LSTM to recognize aggressive behaviors of pigs in pig farms for injury prevention, and Chen et al. [ 50] used ResNet50-LSTM to classify the drinking behaviors of pigs to verify their adequate water intake. Recently, EfficientNet-BiFPN-LSTM was proposed by Yin et al. [ 51] to recognize the motion behavior of a single cow to help with farm monitoring. Each of these methods showed good results in terms of behavior recognition, proving that the method is suitable for our goal. However, because the background and presence of multiple animals make it difficult to extract optical flows, these methods rely on a single-stream CNN-LSTM, using only RGB frames. Because the use of both RGB for appearance and optical flow for motion can lead to better recognition performance [52], guaranteeing by that a more accurate summarization, especially in our system, which targets both active and static behaviors, a two-stream CNN-LSTM model is more appropriate for us to use. Accordingly, we propose an end-to-end system for behavior-based dog video summarization using four modules. The first module collects and preprocesses the image sequences and forwards them to the second module, namely, the YOLOR-based dog-alone sequence retrieval module. At this level, object detection is performed using YOLOR-P6 [53] to detect dogs and people, followed by sequence bounding box matching [54] to correct missed detections. The YOLOR-P6 model was used because it provides one of the best speed and accuracy tradeoffs among the object detection models. Further processing is performed to select sequences of frames containing a dog alone, and their detection results are saved as a dog’s location log data. After that, the selected frames are spatially cropped with a focus on the dog to reduce background noise and location dependence. The sequences of cropped images are then forwarded to the dog behavior recognition module, where a two-stream EfficientNetV2B0 is used to extract features from the RGB and optical flow frames, generated using the global motion aggregation (GMA) algorithm [55] and then a bidirectional LSTM to extract temporal features from the cropped dog sequences. The specific models and algorithms used in this module were selected because they guarantee good performance and inference speed. Finally, the detected behaviors are saved as log data and forwarded to the dog-behavior-based video summarization and visualization module. At this stage, data visualization techniques are utilized to generate an effective visual summarization of the dog’s location and behavior through different graphs to help identify patterns and features that can allow a better understanding and assessment of the dog’s health and welfare. ## 3. Behavior-Based Dog Video Summarization System The architecture of the proposed behavior-based dog video summarization system is illustrated in Figure 1. ## 3.1. Data Collection and Preprocessing Module The image data used by the system were transmitted at a frame rate of 21 fps from a top-down angle RGB camera installed in the ceiling to minimize occlusions and overlapping with people and other objects. This angle also provides an intuitive way of localizing the objects of interest inside a room and studying their movements, making it commonly used in monitoring systems [49,50,51,52,56]. In this module, the collected RGB images are resized to 960×960. pixels to match the input size of the YOLOR model and are then forwarded to the next module. ## 3.2. YOLOR-Based Dog-Alone Sequence Retrieval Module The data received at this stage contain frames with a dog alone, frames with one or more people, frames with people and a dog, or frames of an empty room. To ensure consistent observations and prevent the owner’s presence from influencing the dog’s behavior [27], this module selects only sequences of frames where the dog is alone and discards the remaining ones. YOLOR object detection was first used to detect humans and dogs in each sequence. If a sequence contains no detections or contains at least one human detection in every image, it is discarded. Otherwise, the sequence bounding box (Seq-Bbox) matching algorithm is applied to handle missed detections. Subsequently, the image sequences containing a dog alone were retrieved, and their corresponding bounding boxes were saved as dog location log data. Finally, an algorithm was applied to crop the images in each sequence to focus on the dog using a unified padded bounding box, generated from the dog’s bounding boxes. In short, this module receives continuous RGB frames as the input and output sequences of eight dog-focused cropped images. The entire process is described in detail in the following subsections. ## 3.2.1. Dog and Human Object Detection Owing to recent advances in deep learning, the field of object detection has shown continuous improvements in speed and performance and led to the development of methods and models targeting several areas of research and covering different scenarios [57,58]. Among the existing object detection models, You Only Look Once (YOLO) [59] and its variants have attracted considerable attention because of their performance and real-time inference speed, making them a popular choice for monitoring systems [37,56,60,61]. In this module, the YOLOR model was used for object detection of dogs and humans. YOLOR is a recent YOLO variant with a network that integrates both explicit and implicit knowledge to learn one general representation. More specifically, the YOLOR-P6 subvariant, which offers one of the best performance and speed tradeoffs guaranteeing real-time inference, was used for human and dog detection on each frame received and output the class, score, and bounding boxes of every object detected. First, the frames received from the previous module were grouped into sequences of 21 consecutive frames for object detection and analysis of each sequence separately. The sequence length was set to 21 frames to match the camera’s frame rate. After object detection is performed on the images in a sequence, if there is no detection in any frame of the sequence, or if at least one human is detected in every frame of the sequence, the whole sequence is discarded and the module moves to process the next sequence. Otherwise, the sequence and its detection results are retained for further analysis to retrieve from it sequences of data containing a dog alone. However, because YOLOR is a per-frame detection model, when performing object detection on a sequence of frames such as in this case, missed detections can occur due to factors such as unusual object poses [62]. To ensure the correct retrieval of frame sequences with a dog alone, it is important to handle such missed detections. *In* general, when the detection model targets a single object, methods such as linear interpolation can be used directly to replace the missing detections based on the detections in the closest surrounding frames [37]. However, as we target multiple objects (a dog and humans), in some scenarios when there is a missed detection, nearby frames can contain multiple detections. In such a case, to select the exact detections that need to be used from nearby frames to generate the missed detection, we first need to identify and match in a sequence all the detections that correspond to each object. For this purpose, the Seq-Bbox matching postprocessing method proposed by Belhassen et al. [ 54], which specifically performs this matching, was used, as explained in the next section. Accordingly, the sequences of the 21 frames that were not discarded are forwarded with their corresponding detection results to the Seq-Bbox matching postprocessing unit to handle missed detections. ## 3.2.2. Seq-Bbox Matching-Based Postprocessing This unit of the module takes a sequence of 21 frames and its detections as input, uses Seq-Bbox matching to correct any missed detections, and then outputs sequences of eight frames containing a dog alone and their detection results. The Seq-Bbox matching postprocessing algorithm used here is the one proposed in [54], and it uses the Seq-Bbox matching technique to match detections every two consecutive frames based on the distance score shown in Equation [1]. [ 1]distance=1similarity=1IoU×(Vctri·Vctrj) where intersection over union (IoU) represents the geographical proximity of two bounding boxes and the dot product of the two classification score vectors depicts the similarity in the semantics of bounding boxes i and j. Through the matching of detections in a sequence, tubelets that represent sequences of bounding boxes specific to objects detected in a sequence are generated. Figure 2 shows examples of a tubelet of a human marked in red and a tubelet of a dog marked in blue. *After* generating tubelets and to generate missed detections, the bounding boxes of the last frame belonging to each tubelet Ti are matched with the bounding boxes of the first frame of each tubelet Tj, given that the first frame of Tj starts temporally later than the last frame of Ti. Once the two tubelets are linked, the missing boxes in between are generated using bilinear interpolation. Figure 3 shows an example of tubelets linking a tubelet Ti (in red) and Tj (in blue) and the missed detections generated through bilinear interpolation (in green). Furthermore, to prevent matching tubelets of different objects, a threshold k is used to limit the accepted temporal interval between the candidate tubelets Ti and Tj and only link tubelets if the number of frames between the last frame of Ti and the first frame of *Tj is* less than k. Following the experimental method used in [54] to select a value for k, the optimal value for k on our dataset was set to $k = 15.$ Through Seq-Bbox matching postprocessing, missed detections are reduced in each sequence of 21 frames, and for each object, a tubelet is generated. Subsequently, tubelet matching and linking are applied between every current and previous sequence Sn and Sn−1 to generate any missed detections in between. Once the final tubelets are generated, they are analyzed to select the sequences of frames containing dog tubelets that do not overlap with human tubelets, as these represent sequences of images with a dog alone, and then the sequences are regrouped in sequences of eight frames. Unlike in the previous unit, where sequences contained 21 frames, at this stage, the grouping of frames with a dog alone uses eight frames as sequence length to match the input size of the EfficientNet-LSTM. Subsequently, new sequences of length 8 are forwarded to the next unit with their corresponding dog tubelets. Meanwhile, the dog’s bounding boxes from each frame, which represent the dog’s location tracking, are saved as log data. ## 3.2.3. Dog-Centered Sequence Spatial Cropping At this point, and to improve the behavior recognition results, the images in each sequence are spatially cropped to put more focus on the dog. This helps concentrate learning on our specific target region to explore its contextual features, reduce the impact of less significant elements, and prevent the model from associating actions with specific locations [52,63]. Accordingly, this unit receives sequences of eight frames with its dog tubelets and since only spatial cropping is performed at this level, the sequence length is maintained, and hence the output is a sequence of eight spatially cropped images. Because the dog’s tubelets are already detected through the YOLOR model and Seq-Bbox matching, it is possible to use them for image cropping with a focus on the dog. Nevertheless, because every bounding box in the tubelet has a different size, directly using them to crop the dog in every frame of the sequence will result in a sequence of cropped images of different heights and weights. When resized to match the image input size of the CNN-LSTM model, the proportions of the dog will differ from one frame to the next in the sequence, which will negatively affect the optical flow and image feature extraction. Thus, for cropping while maintaining the dog’s proportions, we propose a simple algorithm to unify the bounding boxes across each tubelet and use the unified bounding box to crop every frame in the sequence. The algorithm proceeds by examining the xmin, xmax, ymin and ymax values of every bounding box in a sequence of eight frames, selecting the smallest values of xmin and ymin and the highest values of xmax and ymax. These values are used to define a unified bounding box that includes all areas covered by the bounding boxes in a sequence. Furthermore, to ensure that all cropped sequences have a similar size, the dataset was analyzed to approximate the largest possible height and width of a unified bounding box, which was found to be 300×650, and padding was used on the unified box to reach that size. The algorithm first attempts to add padding equally from each side of the bounding box vertically and horizontally; however, when the padding exceeds the limit of the total image size on one side, excess is added to the other side. Finally, the unified and padded bounding box was used to crop every image in the sequence to produce a sequence of eight dog-centered cropped images (dog-centered tubelet). The process of generating, padding, and using a unified bounding box to spatially crop images in a sequence is illustrated in Figure 4. The cropped images were then resized to 224×224 to match the input size of the CNN-LSTM before being forwarded to the behavior recognition module. ## 3.3. Dog Behavior Recognition Module In this module, we used a CNN-LSTM model for dog behavior recognition, as it has been demonstrated to be efficient and perform well, making it popular for use in animal behavior recognition [49,50,51]. In particular, as shown in the comparative analysis presented in the work done by Yin et al. [ 51], when used as a spatial feature extractor, the EfficientNet [64] model was able to outperform other commonly used CNN models such as VGG16 and ResNet50 and matched the results of DenseNet169 in behavior recognition while using significantly fewer parameters. For this reason, we adopted a similar approach in our system, but instead of the EfficientNetV1, we used EfficientNetV2, which was introduced by Tan et al. [ 65] to solve some of the bottlenecks of its predecessor. This was accomplished through a combination of scaling and training-aware neural architecture search (NAS), with the extensive use of MBConv and fused MBConv in early layers to increase both training speed and parameter efficiency [52,64,65]. This makes it a suitable choice for our architecture because it can guarantee real-time application through fast inference. More specifically, the B0 variant was selected because it had the lowest number of parameters. Because using both RGB and optical flow can lead to improved results [52,66], in this module, we use a two-stream CNN-LSTM to recognize dog behaviors, using EfficientNetV2 and a bidirectional LSTM (Bi-LSTM). The Bi-LSTM was selected because of its good performance with time-series data and capability to integrate future and past information when predicting, which allows it to better define time boundaries for actions [52]. Accordingly, the sequence of eight cropped images received in this module was used for dog behavior recognition through a two-stream EfficientNetV2B0-Bi-LSTM model. The sequence was first input to the GMA [55] algorithm to extract the optical flow between every two consecutive RGB cropped images. Consequently, each sequence of eight cropped images is used by GMA to extract flow and generate a sequence of seven optical flow images. The GMA algorithm was used because it provides one of the lowest end-point error (EPE) values on the Sintel dataset benchmark [67] while ensuring low latency. Subsequently, due to the mismatch between the sequence of seven flow frames and the sequence of eight cropped RGB images, the first cropped RGB frame is dropped to allow both streams of data (RGB and flow) to have the same sequence length of seven frames, which will later guarantee that the LSTM layer receives a sequence with time steps of consistent features vector size. At this stage, each sequence is fed to its respective EfficientNetV2 model that was pretrained on similar data to serve as a spatial feature extractor to learn appearance features from the RGB sequence and motion features from the optical flow sequence. For use as a feature extractor, the last dense layer of both EfficientNetV2 models was removed to output a feature vector of size 1280 for each sequence of RGB and flow. Subsequently, both sequences are fed to a fusion layer, to be concatenated before being fed to the Bi-LSTM as one sequence of seven fused feature vectors, each of size 2560. At the Bi-LSTM level, the temporal features in the sequence were extracted and a softmax layer used to classify them and recognize the dog’s behavior, which was then saved in the database as log data and simultaneously forwarded to the next module. The behaviors recognized in this module are described in more detail in Section 4.1. ## 3.4. Dog Behavior Summarization and Visualization Module At this stage, the dog’s detected location and behavior are simultaneously received by this module to provide real-time feedback and saved as log data in the database. Simple postprocessing is applied by grouping the detected behaviors to define their occurrence, length, and temporal boundaries. In addition, in this module, data visualization techniques were used to convert the saved location information and summarize the behaviors from the log data into an effective visual representation. By doing so, the system can help owners and experts identify behavioral features, anomalies, and patterns to better understand the dog’s health and welfare. The following subsections present the different types of graphical and visual summarization used to cover different aspects of dog behavior that can help assess their state. ## 3.4.1. Poor-Welfare Indicator Monitoring Ensuring that a dog benefits from good welfare is one of the main responsibilities of an owner, which is why it is important for them to understand when their dogs are showing signs of possible poor welfare, and to manage and improve it. While precisely recognizing this is a difficult task, previous research has defined some dogs’ behaviors as possible indicators of poor welfare when they are displayed in high frequencies. Accordingly, we selected potentially abnormal behaviors displayed by the dogs in our data collection experiments to demonstrate how they can be used to detect possible poor welfare. Table 2 shows these behaviors and the frequency or time threshold starting from where the behavior becomes significant for poor welfare [68]. These behaviors can potentially cause physical harm to the dog and disturbance to the community and may require quick intervention. Therefore, providing a visualization of their level of occurrence in real time represents an effective way for owners to monitor them. For this purpose, we employ gauge charts to display the measure of occurrence for each of those behaviors to visualize when they reach their respective thresholds, and owners can choose to be notified when that happens. ## 3.4.2. Dog Movement Visual Summary A dog’s movement and locomotion can provide a basis for assessing aspects of its health and welfare. In fact, factors such as ambulation patterns and restlessness levels have been associated with health and welfare issues such as physical pain, stress, and hyperactivity-related disorders [22,69,70,71]. In addition, some movement patterns, such as pacing and circling, are considered signs of anxiety in dogs [72,73]. Therefore, our system provides a visual summary of the dog’s spatial movement based on the logged location information to allow owners and dog experts to observe and look for similar signs. The dog’s movement visual summary is presented in two graphs. The first is a heatmap generated using the saved bounding boxes of the dog to represent the areas covered by the dog’s movement to better understand the dog’s movements and activity level, whereas the second represents the trajectory of the dog’s movement. This second graph uses the centroid of the bounding boxes from the log data and connects them to each other using a color map in order to define the timeline of the trajectory. In addition, circles were used to highlight the beginning and end points of a dog’s movement. ## 3.4.3. Summarization of Dog’s Displayed Behaviors Two graphs were used to summarize and visualize the displayed behaviors of the dogs. The first is a nested doughnut chart that displays the percentage of active and static behaviors alongside the specific behaviors belonging to each category, which provides a general understanding of the dog’s displayed behaviors as a whole and allows observation of changes in the behaviors displayed. This is important, as increases or decreases in the frequencies at which some behaviors occur are a common sign of health and welfare issues [21,22,74]. A scatterplot was employed as a timeline to visualize the dogs’ behaviors and their time duration. Based on this, patterns such as the phases of resting and sleeping, which are important welfare indicators [75], can be observed, in addition to the levels and types of activity displayed. ## 4.1. Data Collection and Datasets The data were collected in a laboratory with a CCTV camera (Hikvision DS-2CE56D0T-IRMM (2.8MM), Hangzhou, China) recording frames with a resolution of 960×1080 sampled at 21 fps, mounted on the ceiling at a direct top-down angle with the participation of two small dogs: an 8-year-old rescue shih tzu and a 2-year-old spitz. The experiments’ recordings were conducted in a room located in Sejong City, South Korea, with the consent and presence of the owners and under continuous direct or remote supervision when the dog was left alone inside the recording area. The first few visits were done to ensure that the dogs had time to discover and familiarize themselves with the environment to avoid causing them any stress when collecting data. In addition, the recordings were limited to a maximum of 20 to 30 min with breaks when needed to prevent any discomfort, water was provided along with the dog’s own toys and items used at home, and the room temperature was maintained at a comfortable level. The camera recordings started before the arrival of the dog, during the breaks, and after the experiments were conducted to collect diverse data, including frames of the empty room, humans with and without the dog to be used for the object detection model training. The setup of the room was changed slightly to produce a different background, and people were invited to the recording area on different occasions for daily life tasks for the purpose of obtaining more real-life data. Figure 5 shows examples of the collected data. The image data of both humans and dogs were labeled with bounding boxes for object detection training, and only the dog was labeled for behavior recognition in the data where it was alone. The dataset used for object detection contained 12,000 samples from the shih tzu, 16,000 samples from the spitz, and 15,000 samples from different people. In order to select the length of the images sequence used as input to the EfficientNet-LSTM model, we considered the findings of the analysis done by Zhang et al. [ 66], where they compared results of a two-stream approach with different input sequence lengths on various datasets. Consequently, we determined that a sequence of length eight frames, which generally leads to good results, would work for our model, and this was further validated through our experimental results. Table 3 shows the number of sequences of eight images used for the behavior recognition training for each of the behaviors displayed by the dog in the data collection experiments alongside their descriptions. External stimuli were limited to avoid any bias and to collect data on the dogs’ naturally displayed behaviors. Because some of the dogs’ collected behaviors were less frequent than others, the samples of the frequent ones were limited to reduce the dataset imbalance while selecting random samples from different experiments. ## 4.2. Experimental Environment and Setup The system implementation and the experiments were all conducted using Python 3.8 in an Anaconda environment on a computer running Windows 10 with an Intel i7 8700 K CPU, 32 GB of RAM, and an RTX 2080Ti GPU. The YOLOR object detection model was trained using the PyTorch library following the officially recommended environment, whereas the EfficientNetV2 and LSTM models were trained with the TensorFlow 2.8 library. The GMA code was based on the official implementation. Both object detection and behavior labeling were performed using the ViTBAT [76] software, and a Python script was implemented to convert the bounding box labels to the YOLO format. It is also worth mentioning that the YOLOR-P6 model was used to automatically generate object detection labels after it was trained on part of the data that were manually labeled to speed up the labeling process on the remaining data. The tool introduced in [77] was used to calculate the mean average precision (mAP) for object detection evaluation. The visualization tools were implemented using Matplotlib and Plotly libraries. ## 4.3.1. Evaluation Metrics The following Equations [2]–[5] represent the different metrics used for the evaluation of the models in the second and third modules of our proposed system. [ 2]mAP=∑1CAP(C)C [3]Precision=TPTP+FP [4]Recall=TPTP+FN [5]F1 score=2×Precision×RecallPrecision+Recall where mAP is the mean average precision, AP is the average precision, C is the number of classes, true positive (TP) denotes the dog’s behaviors that are correctly classified as true, false positive (FP) is the number of falsely identified dog behaviors, and false negative (FN) is the number of behaviors incorrectly classified as false. ## 4.3.2. YOLOR-P6 Dog-Alone Sequence Retrieval Results The data used for the YOLOR-P6 object detection model training included samples of labeled images of dogs and people and images of an empty room. The dataset was divided according to a ratio of 8:2, resulting in training samples with 34,400 images and the validation samples with 8600 images. YOLOR-P6 was trained for 300 epochs with an input size of 960×960 pixels using default hyperparameters. To evaluate and compare YOLOR-P6 object detection with and without the seq-Bbox matching algorithm to confirm the effectiveness of the latter, the mean average precision (mAP) and latency in milliseconds were calculated, and the results are presented in Table 4. As seen in Table 4, the seq-Bbox matching postprocessing improves the results of the YOLOR-P6 model, especially the AP of the dog which reached 0.962, while only requiring 0.19 ms in additional latency. Furthermore, precision, recall, and F1 score were used to evaluate the effectiveness of the dog-alone retrieval module and confirm that it can accurately retrieve sequences of data containing a dog alone. We used a different set of sequences of eight images containing four different scenarios: a dog alone, one or more people, a dog with one or more people, and images of an empty room. The results, as seen in Table 5, confirm the efficacy of this method in differentiating between the different types of sequences and hence its efficacy in retrieving the sequences of data where the dog is alone. Although the average precision (AP) for people detection was relatively low, the results of the retrieval were significantly better, and this is due to the fact that some of the scenarios used in both evaluations (Table 4 and Table 5) contained multiple people, and in the most challenging ones, some of them stood too close to each other, which affected the object detection results. However, for the same scenarios, the detection of at least one person allows the sequence retrieval module to correctly classify them, especially in the dog and person scenarios, which explains the good retrieval results. Based on these results, we can confirm that this module performs well and provides accurate tracking of a dog’s location information and retrieval of sequences of a dog alone. ## 4.3.3. Dog Behavior Recognition Results In this section, we present the results of two experiments. The first is used to validate the effectiveness of the EfficientNetV2-LSTM model proposed in this paper using Precision, Recall and F1 score, and the second is to compare the results of the behavior recognition, with other models used for action-based summarization and behavior recognition. The data used in both the experiments are listed in Table 3. To train the models, the dataset was divided into training, validation, and testing data at a ratio of 7:2:1. EfficientNetV2 used for RGB images was trained for 60 epochs, whereas the one used for optical flow images was trained for 150 epochs, both of which were trained using the Adam optimizer with a learning rate of 0.00005 and an input size of 224×224. In contrast, the Bi-LSTM network consists of one layer of 60 hidden units, uses a dropout rate of 0.5, and 0.1 recurrent dropout, and it was trained for 200 epochs using the Adam optimizer with a learning rate of 0.0005 and categorical cross-entropy as a loss function. A softmax activation layer was used on top of the LSTM to classify the results and recognize the behaviors. The results of the first experiment show that our proposed method achieved an average F1 score of 0.955, as shown in Table 6, confirming the performance of the proposed method. As seen from the results, such behaviors as “idle” have relatively lower accuracy, as it is sometimes hard to differentiate it from other behaviors with similar postures, such as “lying down” or “walking”, when the dog’s walking speed is low. Similarly, “standing up” and “wall bouncing” sometimes share similar features in posture and motion, which can lead to misclassification. In the second experiment, other recent methods for action and behavior recognition were used to compare their recognition results with our proposed method. The TDMap–CNN method by Elharrouss et al. [ 46] used in their proposed action-based summarization method, VGG16-LSTM [49] and ResNet50-LSTM [50] used for animal behavior recognition, and our proposed EfficientNet-LSTM, using full-size images and cropped images as input data. The TDMap-CNN [46] was originally designed to generate a background using cosine similarity and to employ the generated background for segmentation and track people. However, in our case, as there were instances where the dog remained inactive for long periods, the generated background ended up including the dog and affected segmentation. To address this issue, for each video used, we manually selected a portion in which the dog was in constant motion to generate the background and use it. On the other hand, the second and third models were trained as single-stream CNN-LSTM, using only the RGB images and following the network and parameters available in their respective papers. The last two models are based on the two-stream EfficientNetV2-LSTM, where the first one was trained on the original full images, and the second was trained on the cropped images obtained from the dog-centered sequence spatial cropping. Table 7 shows a comparison of dog behavior recognition performance results using each model. As shown in the table, the EfficientNet-LSTM model performed better than the other methods. In addition, the results proved the effectiveness of using dog-centered cropped images, as opposed to full images as input data, which confirms our initial assumption about the impact that the background can have on the recognition and validates the benefit of the cropping unit that was included in the system. The TDMap-CNN showed a lower F1 score compared to the other models because the method relies heavily on motion information to classify actions, and this leads to misclassifications when used with static behaviors that contain little motion. On the other hand, one-stream methods rely solely on appearance features, which affect the recognition of behaviors with similar postures. This further confirms the effectiveness of exploiting both appearance and motion features when recognizing static and active behaviors, as is the case with the proposed method. Finally, the proposed method was evaluated for the inference time required for the system to operate, including YOLOR-P6 Seq-Bbox matching object detection, sequence retrieval, spatial cropping, GMA-based optical flow extraction, and EfficientNet-LSTM inference. The total was 0.226 s/image, which confirms the capacity of the system to execute in real time. ## 4.3.4. Dog Behavior Summarization and Visualization Results To demonstrate the effectiveness of the dog behavior-based summarization, a timeline of the recognized and summarized behaviors from a dog video is shown in Figure 6, along with the ground truth. As seen in the figure, our method delivers summarization results that are comparable with the displayed behaviors and their lengths, which further confirms its performance. The following figures demonstrate the visual summary of the logged dog’s behaviors and movement patterns provided by the system to help the owner and experts understand and monitor the dog’s health and welfare. Figure 7 shows an example of the real-time visualization of poor-welfare indicators using a gauge chart for each behavior during a 5 min session. The threshold is represented by the red line in each chart based on the values in Table 2. The current value for each behavior is indicated in green and displayed numerically inside each gauge. Both barking and grooming are tracked as continuous data in minutes, while wall bouncing is a discrete value for the number of times it occurred. The charts shown in Figure 7a,b correspond to the visualization of the shih tzu’s (dog 1) and spitz’s (dog 2) poor-welfare indicators, respectively. As seen in the figures, the first dog’s wall-bouncing and barking levels both exceeded the set threshold, indicating a higher possibility of a welfare issue. Due to its past as a rescue dog, dog 1 seems to be showing signs of anxiety in this scenario. In contrast, dog 2 displayed some barking and grooming, but both were at a normal level below their respective thresholds. Figure 8 presents a summary of the dogs’ movements around the room as a heatmap to highlight the areas where they have spent significant amounts of time. Areas with a darker shade of red correspond to places where the dog spent most of its time. In the scenario in Figure 8, both heatmaps used the tracked location data of each dog for 3.5 min right after they were left alone in the room to help assess their reaction. These first minutes are important to monitor as the period during which dogs with some health issues are likely to display abnormal behavioral patterns [78,79]. Dog 1 in Figure 8a covered a wide area of the room in a short period of time, indicating a high level of restlessness and movement, which are indicators of stress and anxiety [80,81]. Figure 8b shows how dog 2 spent that time near the exit from where its owner left, which is considered a normal behavior of attachment that healthy dogs commonly display [79]. To further detail the dog’s movement summary, the visual tool shown in Figure 9 was used to show the dog-specific trajectory. The scenarios shown in Figure 9 represent the same ones used in Figure 8 to detail both dogs’ movement trajectories starting from the blue circle and following the color map shown in the legend and ending in the red circle. As seen in Figure 9a, dog 1 shows signs of restlessness, pacing, and a few occurrences of circling, all of which indicate a level of anxiety and possible welfare issues. In contrast, dog 2 in Figure 9b shows a simpler trajectory with a lack of exploration and activity, which suggests a relaxed state. Another visualization provided by the system is the proportion of detected dog behaviors based on logged data using a doughnut chart. The chart shows the proportion of active and static behaviors as a general category and includes a nested level detailing the proportion of specific behaviors. Examples of these visual summaries are shown in Figure 10. Figure 10a,b both represent the proportions of the behaviors displayed by dog 1, with the first being from an early session during which the dog was still not well accustomed to the new environment, and the second representing a later session where the proportion of static behaviors relatively increased. In addition, we noticed a significant decrease in some indicators of poor welfare, such as wall bouncing, which represents a positive change and suggests that the dog’s welfare is improving. On the other hand, Figure 10c,d for dog 2 show consistency in the level of static and active behaviors displayed by dog 2 and no significant increase or decrease in activities that could indicate health and welfare issues. Finally, Figure 11 shows the scatterplot used to draw a timeline of the dog’s behaviors to observe when and for how long behaviors occurred and to visualize the level of activity displayed. Through this timeline, it is possible to understand the dog’s behavioral patterns through time (in minutes) and monitor its level of rest and sleep, which are also important factors related to its health and welfare [75]. Figure 11a shows the timeline of dog 1 behaviors, where the static ones are listed below and separated from the active ones by a dotted line. Dog 1 in this scenario displayed a high level of activity, and although there were times when it was idle and lying down, those behaviors were scattered, and active behaviors occurred throughout the session. In addition, the dog scratched and bit the door repeatedly, indicating its attempts to escape due to lack of comfort, and did not have continuous moments of rest. In contrast, dog 2, as seen in Figure 11b, displayed a good level of comfort during the session when it spent most of its time lying down or idle, both static behaviors related to resting. Further monitoring of such rest behaviors can help owners monitor the dog’s health states because some health issues can cause an increase and decrease in resting behaviors. ## 4.3.5. System Graphical User Interface A graphical user interface, shown in Figure 12 and Figure 13 below, was implemented to allow the user to easily monitor the dog’s behaviors and generate the summarization and visualization of the results. ## 5. Conclusions A dogs’ displayed behaviors can serve as indicators that help us to understand their health and welfare, which is why it is essential for owners to monitor and keep track of them to look out for relevant signs and behavioral patterns. To provide dog owners and experts with a suitable solution, we propose a real-time system to automatically summarize dogs’ videos based on their behaviors and provide effective visual tools to help understand and analyze the dogs’ movement and behaviors. The system is composed of four consecutive modules that collect data, retrieve sequences of images where the dog is alone and spatially crops them, recognizes the dog’s behaviors, saves both them and location information as log data, and summarizes and provides visualization of the saved dog’s movement and behaviors. Dog image sequence retrieval and spatial cropping were performed using the YOLOR-P6 model followed by Seq-Bbox matching to track and save the dog’s location data, and dog-focused cropped images were then generated from each sequence to improve the behavior recognition. Subsequently, in the behavior recognition module, the GMA algorithm is used to extract the optical flow, and then both RGB and optical flows are fed as input to a two-stream EfficientNetV2-Bi-LSTM that recognizes the displayed behavior. Finally, in the last module, the behaviors are summarized and visualization tools are utilized to generate effective visual summaries of the behaviors to help owners and experts understand the dog’s health and welfare and potentially discover issues. As demonstrated through the experimental results, our system achieves an F1 score of 0.955 in terms of behavior recognition, which also proves its performance in summarization, achieving better results than other recent methods used for behavior recognition and executing in 0.23 s/image on average. Furthermore, the experiments demonstrated the effectiveness of the dog’s behavior summarization and visualization in helping owners and experts understand and monitor their health and welfare. In our future work, we intend to introduce sound data into a multimodel system to detect vocalizations such as panting and whining, as they can also provide insight into their health. 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--- title: Chemical Composition of Hazelnut Skin Food Waste and Protective Role against Advanced Glycation End-Products (AGEs) Damage in THP-1-Derived Macrophages authors: - Ludovica Spagnuolo - Susanna Della Posta - Chiara Fanali - Laura Dugo - Laura De Gara journal: Molecules year: 2023 pmcid: PMC10054400 doi: 10.3390/molecules28062680 license: CC BY 4.0 --- # Chemical Composition of Hazelnut Skin Food Waste and Protective Role against Advanced Glycation End-Products (AGEs) Damage in THP-1-Derived Macrophages ## Abstract Glycation and the accumulation of advanced glycation end-products (AGEs) are known to occur during aging, diabetes and neurodegenerative diseases. Increased glucose or methylglyoxal (MGO) levels in the blood of diabetic patients result in increased AGEs. A diet rich in bioactive food compounds, like polyphenols, has a protective effect. The aim of this work is to evaluate the capacity of hazelnut skin polyphenolic extract to protect THP-1-macrophages from damage induced by AGEs. The main polyphenolic subclass was identified and quantified by means of HPLC/MS and the Folin–Ciocalteu method. AGEs derived from incubation of bovine serum albumin (BSA) and MGO were characterized by fluorescence. Cell viability measurement was performed to evaluate the cytotoxic effect of the polyphenolic extract in macrophages. Reactive oxygen species’ (ROS) production was assessed by the H2-DCF-DA assay, the inflammatory response by real-time PCR for gene expression, and the ELISA assay for protein quantification. We have shown that the polyphenolic extract protected cell viability from damage induced by AGEs. After treatment with AGEs, macrophages expressed high levels of pro-inflammatory cytokines and ROS, whereas in co-treatment with polyphenol extract there was a reduction in either case. Our study suggests that hazelnut skin polyphenol-rich extracts have positive effects and could be further investigated for nutraceutical applications. ## 1. Introduction Advanced glycation end-products (AGEs) are a heterogeneous group of compounds derived from spontaneous non-enzymatic glycation (or Maillard reaction) between reducing sugars and proteins, nucleic acids or lipids [1]. AGEs have been shown to cross-link with intracellular or extracellular proteins altering their physiological properties and functions [2], accumulate in cells or tissues contributing to chronic diseases, diabetic complications, cardiovascular diseases and are also involved in the progression of neurodegenerative diseases [3] such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) [4,5], and during the physiological aging process or in autoimmune disease [6,7,8]. During the Maillard reaction, Amadori products formed [9] are converted directly to AGEs and others are oxidized to α-di-carbonyl compounds such as 3-deoxyglucosone (3-DG), methylglyoxal (MGO) and glyoxal (GO), which covalently bind to long-lived proteins to form stable AGE compounds [10]. In addition to endogenous AGEs’ formation, these compounds are also derived from foods high in lipids and proteins and are called dietary AGEs (dAGEs) [11]. In addition, various processes such us thermal food processing, storage, frying and cooking can contribute to increased AGEs’ content [12,13]. The adverse effects of AGEs on cellular functions includes several mechanisms such as the production of reactive oxygen species (ROS), oxidation of nucleic acids or lipids and interaction with specific receptors for AGEs (RAGE) expressed in different cell types [14]. AGE–RAGE interaction activates some intracellular signaling, such as transcription of nuclear factor kappa B (NF-kB), resulting in the production of cytokines, chemokines and other pro-inflammatory molecules that induce inflammation, apoptosis and proliferation [15,16,17]. In addition, AGEs accumulate in atherosclerotic lesions contributing to endothelial dysfunction and up-regulating the expression of vascular cell adhesion molecule-1 (VCAM-1) or intercellular adhesion molecule-1 (ICAM-1) [18,19]. Several synthetic drugs have been used to reduce accumulation of AGEs: for example, metformin reduces blood glucose levels and thus MGO levels, a precursor of AGEs. Aminoguanidine (AMG) acting as scavenger of α-di-carbonyl groups and blocks the conversion of Amadori products into AGEs. However, these drugs cause side effects that limit their application [20,21]. To date, many studies have suggested that natural compounds can inhibit formation of AGEs and reduce the harmful consequences of glycation [22,23,24,25]. Phenolic compounds are secondary metabolites of plants with good antioxidant activities that can neutralize undesired ROS and reactive nitrogen species (RNS) produced during metabolic processes in the body [26]. These natural compounds show a broad range of biological activities such as anti-inflammatory and anti-apoptotic activities, and inhibition of enzymes like α-amylase and glucosidase [27,28,29]. Different classes of polyphenolic compounds share the structural features of an aromatic ring and at least one hydroxyl group; they are classified by their chemical structures into flavonoids, phenolic acids, stilbenes and lignans [30,31]. Our work focuses on evaluating the protective effect of hazelnut skin polyphenols extract (HSE) on AGE-dependent damage in mammalian cell cultures such as the THP-1-macrophage cell line. Monocyte-macrophages have been selected as a cellular model because they perform important immunological functions and contribute to the maintenance of homeostasis and tissue repair [32]. The anti-glycation effect of hazelnut skin polyphenols has been previously reported in vitro in a chemical assay [33], thus suggesting a putative role of hazelnut skin extracts as natural drugs able to prevent the harmful glycation effects in vivo. Several works have shown that nut by-products are rich sources of natural phenolic compounds with bioactive potential [34,35]. Hazelnut (*Corylus avellana* L.) belongs to the Betulaceae family and is one of the most popular tree nuts consumed worldwide due to its nutrients, fat-soluble bioactive components, and phenols/phytochemicals [36]. Among hazelnut by-products, hazelnut skin has been previously characterized for its (poly)phenolic profile that provides the basis to investigate its potential health effects [37]. Therefore, the recovery of active compounds from food waste residues can be an interesting strategy of a circular bioeconomy, because in addition to being a natural and safe source of polyphenols, they are an inexhaustible, low cost, and sustainable resource [38]. ## 2.1. HPLC-PDA/ESI-MS Qualitative–Quantitative Analysis of Phenolic Compounds in Total Extracts of Hazelnut Skin Since the level of phenolic compounds in plant tissues, apart being genetically determined, is strongly influenced by the pedo-climatic and environmental conditions in which the plant is grown, a preliminary qualitative–quantitative analysis of the phenolic molecules present in hazelnut skin was performed. The HPLC-PDA/ESI-MS method, previously described, was applied for phenolic compound determination in hazelnut skin. Qualitative analysis was performed considering the retention time, UV and MS spectra, use of standard compounds and data available in literature. Seventeen phenolic compounds have been identified in the extract. Twelve flavan-3-ols and two organic acids were detected at λ = 280 nm while four flavonols and one dihydrochalcone were detected at λ = 360 nm (Figure 1). For all identified compounds, retention time and their mass-to-charge ratio (m/z) are summarized in Table 1. Gallic acid, protocatechuic acid, procyanidin B2 dimer, (−) epicatechin, epigallocatechin-gallate, myricetin rhamnoside, quercetin-3-rhamnoside, kampferol rhamnoside, myricetin, phloretin-2-O-glucoside, quercetin and kaempferol were identified based on retention time of standard molecules and the mass-to-charge ratio (m/z) of the molecular ion. For procyanidin beta type dimer gallate, procyanidin C2 trimer, prodelphinidin B dimer and procyanidin dimers, molecular standards were not available and only mass-to-charge ratio (m/z) of the molecular ion was considered. ( +)-Catechin, and (−)-epicatechin, having the same mass-to charge ratio (m/z), were identified using purified (−) epicatechin as standard molecules and comparing the retention times. All the detected phenolic compounds were previously identified in hazelnut skin [33,37]. Calibration curves with external standard were constructed for each available standard molecule and linearity concentration range was between 1 and 100 mg/L for each curve. Phenolic compounds were quantified using the calibration curve of their standard molecule, if available, while procyanidins and prodelphinidins were quantified using the calibration curve of procyanidin B2 dimer, and (+) catechin using the calibration curve of (−) epicatechin. A total phenolic compound concentration of 445 mg/100 g was determined. As previously reported by Del Rio et al. [ 37], flavan-3-ols represent the main class of phenolic compounds in hazelnut skin. Procyanidin dimers resulted in being the two compounds present in high quantity with a concentration of 100 and 93 mg/100 g, respectively, followed by (+) catechin with a concentration of 62 mg/100 g. Among detected flavonols, quercetin-3-rhamnoside showed the highest quantity, with a concentration of 40 mg/100 g, confirming data reported in the literature [37]. The concentration of each identified phenolic compounds is reported in Table 2. ## 2.2. Total Phenolic Content (TPC) Quantification of the total phenolic content (TPC) in food or biological samples is based on the reaction of phenolic compounds with a colorimetric reagent which allows measurement in the visible spectrum. This approach is considered to give an approximation of the real polyphenol content. Our results indicate that polyphenols in the hazelnut skin represent about 100 mg GAE/g, (10 g of polyphenol/100 g of hazelnut skin). ## 2.3. AGEs’ Quantification Di-carbonyl compounds such as glycolaldehyde, GO, 3-DG and MGO, which are formed as intermediates during the glycation reaction, are more reactive and act as key components of carbonyl stress. In particular, MGO is an important precursor of AGEs that targets functional residues in proteins [39,40]. Several methods such as spectroscopy measurement or chromatography are available to determine parameters that are indicators of AGEs [41,42]. In our work, we have used the BSA–MGO model system for formation of AGEs, as mentioned in the materials and methods section. The presence of total AGEs in the sample was characterized by a fluorescence assay: the BSA–MGO sample showed a significant increase in specific AGE relative fluorescent units at λex 365 nm/λem 440 nm (Figure 2a). On the contrary, non-glycated BSA showed maximum fluorescent at λex 280 nm/λem 350 nm, as expected (Figure 2b). ## 2.4. Protective Role of HSE on Cell Viability Affected by AGEs Glycation inhibitors derived from natural compounds are good candidates for the development of new therapies against diabetes and its complications and other pathological conditions related to AGE accumulation [43]. To assess whether the administration of the HSE could induce toxicity in a biological system, we performed cytotoxicity analysis. Macrophages were treated for 1 h with different concentrations of HSE and then with BSA–MGO at 300 µg/mL for 24 h. The MTT assay showed that HSE failed to display toxicity in macrophages up to a concentration of 400 µg/mL gallic acid equivalents (GAE) and only the administration of 500 μg/mL GAE was toxic (Figure 3). This could explain why phenolic compounds lose their antioxidant capacity at high concentration and start to behave as prooxidants [44]. On the contrary, BSA–MGO treatment resulted in the reduction of cell viability, in a dose-dependent manner (Figure 4b), whereas administration of BSA alone did not significantly reduce macrophages viability until 450 µg/mL (Figure 4a). In Figure 4a,b control is represented by untreated macrophages. In the co-treatment, HSE protects against the reduction in viability following BSA–MGO treatment (Figure 5). Macrophages treated with BSA–MGO show a reduction in cell viability, which increases following HSE treatment at low concentration. When using HSE at high concentrations (from 100 to 400 µg/mL GAE) there seems to be a slight increase in viability even if it was not significantly different when compared to low concentrations (50 µg/mL GAE). In this context, in order to evaluate ROS scavenging activity and the inhibition of inflammation induced by AGE (used at 300 µg/mL) the concentration chosen for HSE was 50 µg/mL GAE. ## 2.5. Reduction of ROS by HSE AGEs determine an increase in oxidative stress derived through different mechanisms of action [45]. Polyphenols have the ability to scavenge reactive carbonyl compounds and to donate an electron or hydrogen atom to free radicals [46,47]. Therefore, to evaluate if HSEs exhibit protective effects against ROS, we have stimulated macrophages with AGEs and our results show that BSA–MGO leads to an increase in ROS production slightly higher than that observed in the control cell culture (Figure 6). Interestingly, treatment with HSE remarkably inhibits the ROS production increase. In addition, as shown in Figure 6, the HSE at 50 μg/mL reduced the ROS production induced by BSA–MGO (Mix). ## 2.6. Modulation of Inflammatory Gene Expression by HSE Inflammation plays a crucial role in the human body’s defense against pathogens and other harmful stimuli. However, uncontrolled inflammation can trigger activated macrophages to secrete excessive inflammatory mediators, leading to damage of otherwise healthy tissue [48]. Here, we have demonstrated that BSA–MGO (our AGEs’ model system) leads to a slight but significant increase in the gene expression of TNF-α, a key cytokine involved in acute inflammation while co-treatment with BSA–MGO and HSE (Mix) showed a reduction (Figure 7a). BSA–MGO treatment showed no effect on IL-1β gene expression, another mediator of the inflammatory response (Figure 7b). Treatment of cells with lipopolysaccharides (LPS) served as positive control for pro-inflammatory cytokine gene expression (Figure 7a,b). ## 2.7. Reduction in Pro-Inflammatory Cytokines’ Secretion Production of the pro-inflammatory cytokines TNF-α and IL-1β in THP1 cells were determined after 24 h treatment. Results showed that HSE attenuated macrophage inflammation caused by BSA–MGO stimulation for both TNF-α and IL-1β secreted protein levels after co-treatments of cells with BSA–MGO and phenolic extract (Mix) (Figure 8a,b). ## 3. Discussion A well-balanced diet in both macro- and micro-nutrients is an important factor in preventing or reducing chronic and systemic inflammation and can promote health, whereas an unhealthy diet can have the opposite effect [49]. In recent years the interest in plant based-foods, rich in bioactive molecules, has greatly increased based on the correlation with their positive effects on human health [50,51]. AGEs are a group of highly reactive chemical species, and their accumulation contributes to hyperglycemia, metabolic burden, increase in ROS production and inflammation which, along with insufficient production of endogenous antioxidants, induces oxidative stress leading to the development of chronic diseases [52,53]. Plant-derived polyphenols have been shown to have glucose lowering activities and, in some cases, direct AGE inhibitory functions [54]. Recently, many studies have proposed the antiglycation activities by polyphenols based on different properties including their structures, antioxidant abilities, and metabolism in the body [55,56]. The anti-glycation functions, depend on the ability to transfer electron free radicals, and are based on the total number of hydroxyl groups in the phenolic nuclear structure that can form stable radical complexes; such ability has been reported for some phenolic molecules [57]. The polyphenolic composition of hazelnut skins by HPLC-PDA/ESI-MS is comparable with the analysis carried out by Del Rio [37] with some differences in terms of the relative number of compounds found. These differences could depend on both the sensitivity of the analytical method used and the treatment of the raw material. Our analysis revealed that this food waste represents a rich source of several polyphenolic compounds some of which have already demonstrated a capacity to prevent AGEs’ related damaging effects. For example, it has been demonstrated that quercetin, a natural flavonol, could effectively inhibit the formation of AGEs in a dose-dependent manner via trapping reactive di-carbonyl compounds [58]. Phloretin prevented the formation of AGEs through trapping MGO in human umbilical endothelial cells (HUVECs) and also reduced inflammatory mediators [59]. Protocatechuic acid (phenolic acid) was effective in inhibiting formation of AGEs (BSA-glucose model system) resulting in a concentration dependent decrease [60]. Gallic acid (GA) showed a protective role in preventing AGE-mediated cardiac complications, through the attenuation of RAGE expression and also by modulating inflammatory downstream signaling pathways [61]. These and other compounds are present in abundance in hazelnut skin extract and therefore, we believe that the inhibitory effect on AGEs’ formation, as previously demonstrated [33] and the positive effect on macrophages obtained in this study, can be attributed to the synergistic effect of the (poly)phenolic compounds present in the total extract. Our data showed that HSE is able to counteract AGEs’ induced damage in a mammalian cell culture in vitro model. In our study, BSA–MGO (AGEs’ model system) lead to an increase in pro-inflammatory cytokines, such as TNF-α and IL-1β, in macrophages (M0). In particular AGEs determine an increase in IL-1β secretion comparable to LPS stimulation, indicating that these macromolecules can contributed to inflammation increments. HSE exerts anti-inflammatory activity, evident by the reduction in the expression of TNF-α (Figure 7a). Protein secretion induced by AGE of both TNF-α and IL-1β was significantly reduced after administration of HSE. We have also demonstrated the antioxidant capacity of HSE, which reduced ROS production in macrophages stimulated by AGEs. The administration of HSE in macrophages alone or in combination with AGEs reduce significantly the amount of ROS, directly proportionally to fluorescent measures. On the contrary, AGEs stimulate ROS production more than the control. These results confirm that HSE have specific anti-glycation activities in both pro-inflammatory and pro-oxidant pathways activated by AGEs and probably also correlate with the phenolic structure as described above. However, we believe that the complex composition of HSE may potentiate the efficacy leading to a greater effect than using a pure compound. The ability of HSE to prevent AGEs’ formation previously demonstrated [33], and the results reported here, strongly support a promising role for the use of HSE in all the diseases characterized by excessive production of AGEs. Our results support the possibility of using this food waste in the context of a circular bioeconomy as an interesting source of anti-AGEs and health-promoting compounds. We are willing to further investigate whether HSE is able to reduce the inflammatory response caused by AGEs, by altering the AGE–RAGE signaling pathway leading to the activation of NF-κB, a ubiquitous transcription factor involved in several diseases. This will be the next step towards a better understanding of the ability of HSE to decrease the AGEs’ dependent damage occurring in mammal cells [62]. ## 4.1. Preparation of HSE The HSE was obtained following the procedure reported by Del Rio et al. [ 37] with some modifications. Two sequential extractions were applied: an amount of 0.5 g of hazelnut skins was added to 5 mL of $1\%$ (v/v) aqueous formic acid solution in a 15 mL centrifuge tube and extracted for 30 min in an ultrasonic bath (Elmasonic S30H, Elma Schmidbauer GmbH, Singen, Germany) at room temperature, with a frequency of 37 kHz, and a heating power of 200 W. Then, the sample was heated at 70 °C for 1 h and centrifuged for 10 min at 2151× g. The procedure was repeated two times, the supernatant was recovered, and a second extraction was performed on the sample remaining after centrifugation. A solution of 5 mL of methanol/H2O (75:25, v/v) was added and it was placed for 15 min in an ultrasonic bath (Elmasonic S30H, Elma Schmidbauer GmbH, Singen, Germany) and vortexed for 15 min. This procedure was repeated twice. After centrifugation, 10 min at 2151× g, the supernatant was recovered and added to the extract obtained with the first extraction step. The solvent of the total extract was evaporated under vacuum at 30 °C in a rotary evaporator (Eyela, Tokyo, Japan). The extract was then dissolved in 1 mL of MeOH and analyzed using HPLC–PDA/ESI–MS. ## 4.2. HPLC–PDA/ESI–MS Analysis of HSE HSEs were analyzed using a Shimadzu Prominence LC-20A instrument (Shimadzu, Milan, Italy) equipped with two LC-20 AD XR pumps, SIL-10ADvp, CTO-20 AC column oven, and DGU-20 A3 degasser coupled to an SPD-M10Avp PDA detector and a mass spectrometer detector (LCMS-2010, Shimadzu, Tokyo, Japan) equipped with an electrospray (ESI) interface. Separation was performed using a Core Shell column (150 µm, 4.6 mm I.D., 2.7 µm d.p.) ( Merck KGaA, Darmstadt, Germany), with the mobile phase composed of $1\%$ aqueous formic acid (A) and acetonitrile (B), pumped at a flow rate of 1 mL/min. Phenolic compound separation was obtained by applying the following gradient: $t = 00$ $0\%$B; $t = 40$ $30\%$B; $t = 41$ $100\%$B; $t = 48$ $100\%$B; $t = 49$ $0\%$B; $t = 56$ $0\%$B. The injection volume was 2 µL. Data were acquired using a PDA in the range 210–400 nm and chromatograms were extracted at 360 nm and at 280 nm. MS-chromatograms were acquired in negative ionization mode, using the following parameters: nebulizing gas flow rate (N2): 1.5 mL min−1; event time: 1 s; mass spectral range: m/z 100–800; scan speed: 1000 amu/s; detector voltage: 1.5 kV; interface temperature: 250 °C; CDL temperature: 300 °C; heat block temperature: 300 °C; interface voltage: −3.50 kV; Q-array voltage: 0.0 V; Q-array RF: 150.0 V. ## 4.3. Determination of Total Phenolic Content The total extract of hazelnut skin was dried as described above and resuspended in 5 mL of methanol/H2O (50:50; v/v) solution, filtered with 0.22 µm filter under sterile conditions for use in cell cultures and subsequently analyzed for the total polyphenols content through a chemical reduction, measured by the Folin–Ciocalteau method [63]. Briefly, an aliquot of 20 µL of extract or standard compound was mixed with 100 µL of Folin reagent in 1580 µL of methanol/H2O (50:50; v/v) solution, followed by incubation for 8 min. Then, 300 µL of Na2CO3 0.2 g/mL solution was added. The absorbance was measured after incubation at room temperature for 2 h, in the dark using a microplate reader (Infinite 200 Pro, Tecan, Männedorf, Switzerland). The total phenolic content was determined from a standard curve using gallic acid (0−2000 µg/mL) as a standard and expressed as milligrams of gallic acid equivalents per grams of hazelnut fresh weight (mg GAE/g). All chemicals and reagents were purchased from Sigma (Sigma-Aldrich, Milan, Italy). ## 4.4. Cell Culture and Differentiation The THP-1 cell line (passages 6–20, ATCC: TIB-202) was cultured in RPMI 1640 medium (Corning, NY, USA) supplemented with 100 U/mL penicillin, 100 µg/mL streptomycin (Corning, NY, USA) 10 mM HEPES (Dominique Dutscher, Bernolsheim, France), 2 mM L-glutamine (Corning, NY, USA), and $10\%$ (v/v) heat-inactivated fetal bovine serum, FBS (Corning, NY, USA) at 37 °C in a humidified atmosphere containing $5\%$ (v/v) CO2. Routinely, THP-1 cells were cultured in T75 flasks and sub-cultured every three to four days at a concentration of 4 × 105 to 1 × 106 cells/mL. THP-1 cells can be differentiated into macrophage-like cells using 100 ng/mL phorbol 12-myristate 13-acetate PMA (Sigma-Aldrich, Milan, Italy) for 72 h. During this time, cell attach to the bottom of the cell culture plates and develop macrophage-like morphology. After macrophage differentiation, cells rest for another 24 h in the culture medium without PMA to obtain the resting state of macrophages (M0). ## 4.5. Preparation of Glycated BSA AGE-BSA was prepared by reacting bovine serum albumin (BSA, Sigma-Aldrich, Milan, Italy) with MGO (Sigma-Aldrich, Milan, Italy) according to the method described by Starowicz et al. with some modifications [64]. The method and analysis were validated in our previous work [33]. Briefly, BSA (4 mg/mL) was dissolved in phosphate buffered saline 1×, pH 7.4 (PBS, Corning, NY, USA) with the addition of $1\%$ pen/strep (to prevent microbe development) and filtered with a 0.22 µm filter, under sterile conditions. BSA with or without addition of 20 mM MGO (BSA glycated and BSA-non-glycated, respectively) were incubated for 168 h at 37 °C, in the dark. Glycation was confirmed by fluorescence of the BSA–MGO model system (AGEs) or BSA measured after incubation using a microplate reader (Infinite 200 Pro, Tecan, Männedorf, Switzerland) at excitation/emission wavelengths $\frac{365}{440}$ nm. Additionally, changes in intrinsic protein fluorescence were detected at excitation/emission wavelengths of $\frac{280}{350}$ nm. Quantification of the BSA–MGO or BSA samples was performed by the BCA assay (Merck, Darmstadt, Germany) according to the protocol. ## 4.6. Cell Viability Differentiated THP-1 macrophages (25,000 cells/well in 96-well plates) were exposed to different concentrations of HSE (25–50–100–200–400–500 µg/mL GAE) and with BSA or BSA–MGO (100–150–300–450–600 µg/mL). Untreated cells represented the control group. Cells were treated with or without HSE for 1 h prior to BSA–MGO (300 µg/mL) treatment. Cytotoxicity was determined after 24 h of incubation by the MTT assay: cell culture medium was discarded, and each well was washed with 200 μL PBS. MTT solution 0.5 mg/mL (Sigma-Aldrich, Milan, Italy), was added to cells (100 µL in each well) and the plate was incubated at 37 °C + $5\%$ CO2 for 3 h. Then, MTT solution was removed, and 150 μL/well of dimethyl sulfoxide (DMSO, Sigma-Aldrich, Milan, Italy) was added to each well to dissolve the formazan crystals. Optical density (OD) was measured at 570 nm using a multifunctional microplate reader (InfiniteM 200 Pro, TECAN, Männedorf, Switzerland). Cell viability was expressed as % of control (untreated macrophages). ## 4.7. ROS Measurement For measuring intracellular ROS, macrophages were used at density of 5 × 104 cells/well in 96-well black plates. Cells were loaded with 100 µL/well of H2DCF-DA (Merck, Darmstadt, Germany) diluted to 20 µM in PBS and incubated for 10 min at 37 °C. Then the solution with probe was removed and replaced by 100 µL/well basal medium. Basic fluorescence intensity was measured at 495 nm excitation and 525 nm emission. Medium was removed and treatments were applied. After 60-min, fluorescence intensity was measured as described above [65]. ## 4.8. Quantitative Real-Time PCR Total RNA was isolated from cells by a column-based method, Monarch Total RNA Miniprep Kit (New England BioLabs, Frankfurt am Main, Germany) according to manufacturer’s instructions including DNAse I-treatment. Concentration and quality of isolated RNA was spectrophotometrically assessed by NanoDrop (Thermo Fisher Scientific Inc., Waltham, MA, USA). Ready-to-use kit (Thermo Fisher Scientific) was used to reverse transcribe 0.5 µg RNA, according to manufacturer’s protocol. Quantitative real-time PCR was performed using the SYBR green master mix (Applied Biosystems, Waltham, MA, USA). Primer sets for TNF-α (NM_000594.4; Fw: 5′-CTCCTCACCCACACCATCAGCCGCA-3′; Rv: 5′-ATAGATGGGCTCATACCAGGGCTTG-3′) and IL-1β (NM_000576.3; Fw: 5′-CTCGCCAGTGAAATGATGGCT-3′; Rv: 5′-TGGTGGTCGGAGATTCGTAGC-3′), were used. Actin-β (NM_001101.5; Fw: 5′-GGGAAATCGTGCGTGACATT-3′; Rv: 5′-TCGTAGATGGGCACAGTGT-3′) was used as a housekeeping gene to normalize data. All reactions were performed in triplicates. ΔΔCt method was used for data analysis. Values of genes of interest were first substracted from the values of actin-β (ΔCt). N-fold change of gene expression was then calculated as 2−(ΔCt treated-ΔCt untreated). ## 4.9. Cytokine Quantification The levels of human TNF-α and IL-1β were measured in the harvested supernatants by solid-phase sandwich Enzyme-Linked Immunosorbent Assay (ELISA kit; Thermo Fisher Scientific, Waltham, MA, USA). THP-1 monocytes were seeded into six-well plates (1 × 106 cell/well) and differentiated into macrophages-M0. Cells were treated with 50 µg/mL HSE or 300 µg/mL BSA–MGO or in combination. After 24 h cell supernatant for each sample was collected and analyzed according to the manufacturer’s recommendation. Optical density (OD) was measured using the microplate reader (Infinite M 200 Pro, TECAN, Männedorf, Switzerland) at 450 nm. ## 4.10. Statistical Analysis The graphics and all statistical analyses were performed using GraphPad Prism version 5.0. The data were expressed as mean ± standard deviation of two/three independent experiments, with at least three technical replicates in each experiment. p-value, * $p \leq 0.05$, ** $p \leq 0.01$, *** $p \leq 0.001$ were considered statistically significant and were calculated using one-way ANOVA and Tukey as post-test or t-test of multiple or two comparisons, respectively. Different letters indicate a significative difference among samples. ## 5. Conclusions Glycation or Maillard reaction is a complex of spontaneous, non-enzymatic reactions that form compounds described as AGEs. Exogenous as well as endogenous AGEs interact with specific receptors resulting in the activation of a series of signaling pathways implicated in inflammation and progression of chronic and degenerative diseases [66]. Discovery of new potential anti-glycation agents, natural or synthetic, represents an effective approach to control the development and prevention of disease linked to AGEs’ accumulation. Several evidence have shown that diets rich in plant food are protective against a wide range of health conditions. Indeed, intake of flavonoid-rich foods has been shown to be very beneficial to human health [52]. Data obtained show that polyphenols in hazelnut skin have a protective effect in macrophages following AGE stimulation and could potentially pair with, or replace synthetic drugs. 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--- title: Essential Oil from Glossogyne tenuifolia Inhibits Lipopolysaccharide-Induced Inflammation-Associated Genes in Macro-Phage Cells via Suppression of NF-κB Signaling Pathway authors: - Wan-Teng Lin - Yen-Hua He - Yun-Hsin Lo - Yu-Ting Chiang - Sheng-Yang Wang - Ismail Bezirganoglu - K. J. Senthil Kumar journal: Plants year: 2023 pmcid: PMC10054403 doi: 10.3390/plants12061241 license: CC BY 4.0 --- # Essential Oil from Glossogyne tenuifolia Inhibits Lipopolysaccharide-Induced Inflammation-Associated Genes in Macro-Phage Cells via Suppression of NF-κB Signaling Pathway ## Abstract Glossogyne tenuifolia Cassini (Hsiang-Ju in Chinese) is a perennial herb native to Taiwan. It was used in traditional Chinese medicine (TCM) as an antipyretic, anti-inflammatory, and hepatoprotective agent. Recent studies have shown that extracts of G. tenuifolia possess various bioactivities, including anti-oxidant, anti-inflammatory, immunomodulation, and anti-cancer properties. However, the pharmacological activities of G. tenuifolia essential oils have not been studied. In this study, we extracted essential oil from air-dried G. tenuifolia plants, then investigated the anti-inflammatory potential of G. tenuifolia essential oil (GTEO) on lipopolysaccharide (LPS)-induced inflammation in murine macrophage cells (RAW 264.7) in vitro. Treatment with GTEO (25, 50, and 100 μg/mL) significantly as well as dose-dependently inhibited LPS-induced pro-inflammatory molecules, such as nitric oxide (NO) and prostaglandin E2 (PGE2) production, without causing cytotoxicity. Q-PCR and immunoblotting analysis revealed that the inhibition of NO and PGE2 was caused by downregulation of their corresponding mediator genes, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2), respectively. Immunofluorescence and luciferase reporter assays revealed that the inhibition of iNOS and COX-2 genes by GTEO was associated with the suppression of nuclear export and transcriptional activation of the redox-sensitive transcription factor, nuclear factor -κB (NF-κB). In addition, GTEO treatment significantly inhibited phosphorylation and proteosomal degradation of the inhibitor of NF-κB (I-κBα), an endogenous repressor of NF-κB. Moreover, treatment with GTEO significantly blocked the LPS-mediated activation of inhibitory κB kinase α (IKKα), an upstream kinase of the I-κBα. Furthermore, p-cymene, β-myrcene, β-cedrene, cis-β-ocimene, α-pinene, and D-limonene were represented as major components of GTEO. We found that treatment with p-cymene, α-pinene, and D-limonene were significantly inhibiting LPS-induced NO production in RAW 264.7 cells. Taken together, these results strongly suggest that GTEO inhibits inflammation through the downregulation of NF-κB-mediated inflammatory genes and pro-inflammatory molecules in macrophage cells. ## 1. Introduction Inflammation is a complex and crucial physiological response to many pathological conditions, including microbial invasion and tissue injury, which is characterized by redness, swelling, and pain [1]. As a result of bacterial infection, an endotoxin (lipopolysaccharide, LPS) is produced by Gram-negative bacteria which leads to many pathological symptoms, such as pyrogenicity, increased circulating leukocytes, macrophage activation, anti-platelet aggregation, and increased capillary permeability [2]. Generally, local inflammatory responses are benign as long as the process is properly regulated to keep the cells and inflammatory mediators sequestered. Moreover, the uncontrolled inflammatory response can result in death when it is not controlled, as is the case with anaphylactic shock, as well as with chronic inflammatory diseases such as arthritis and gout [1]. As macrophages become activated by endotoxins or pathogenic microbes; they produce a variety of pro-inflammatory molecules such as nitric oxide (NO), prostaglandin E2 (PGE2), tumor necrosis factor-α (TNF-α), and interleukin-1β/6 (IL-1β/6) [3]. There are a variety of inflammatory disorders associated with the constant secretion of these molecules which include rheumatoid arthritis, pulmonary fibrosis, asthma, hepatitis, and hepatitis B [1]. Therefore, inhibiting these pro-inflammatory molecules is a promising strategy to minimize the burden of inflammatory diseases. Traditional Chinese medicine (TCM) has been used to treat chronic diseases with food supplements and plant-based medicines. A number of TCMs contain essential oils (EOs), which are complex mixtures of volatile compounds obtained from plants through various extraction procedures, including azeotropic distillation (hydro-distillation, hydro-diffusion, and steam distillation) and extraction with solvents. A growing number of in vitro and in vivo studies have demonstrated that EOs possess various bioactivities, including antioxidant, anti-microbial, anti-inflammatory, and anti-cancer properties [4,5]. Glossogyne tenuifolia, locally known as Hsiang-Ju, is a perennial plant native to Penghu island, Taiwan, and also distributed in Southern Asia and Australia [6]. The herb has been used for making herbal tea on Penghu Island for centuries to treat pyrexia, hepatitis, and inflammation [7]. Recent studies have demonstrated that various extracts of G. tenuifolia possess a wide range of bioactivities, including anti-microbial [8], anti-inflammatory [9,10], anti-fatigue [11], antioxidant [12,13], antiviral [10], anti-angiogenesis [14], anti-cancer [15], hepatoprotection [16,17], and immunomodulatory effects [6,18]. In addition, Chyau, et al. [ 19] extracted essential oil from G. tenuifolia using simultaneous steam distillation and solvent extraction methods. A total of 62 compounds were isolated, including terpenes, which are the main constituents of G. tenuifolia essential oil. To the best of our knowledge, the bioactivities of G. tenuifolia essential oil (GTEO) have not been studied. Therefore, the present study was aimed at investigating the anti-inflammatory effects of GTEO on LPS-induced inflammation in murine macrophage cells (RAW 264.7) and delineating the underlying mechanism. ## 2.1. Effect of GTEO on Cell Viability in LPS-Activated RAW 264.7 Cells Prior to the in vitro anti-inflammatory assessment, the cytotoxicity of GTEO to the murine macrophages was determined. RAW 264.7 cells were incubated with increasing concentrations of GTEO (25–200 μg/mL) for 24 h. Next, the MTT colorimetric assay was used to measure the cell viability. As shown in Figure 1A, the number of RAW 264.7 cells were significantly increased following stimulation with LPS (1 μg/mL), whereas cell viability was not affected by GTEO doses up to 200 μg/mL, indicating that within the concentration ranges tested, GTEO was not cytotoxic to RAW 264.7 cells. ## 2.2. GTEO Inhibits LPS-Induced NO and PGE2 Production in RAW 264.7 Cells In this study, a significant increase in NO production (39.58 ± 2.31 μM) from 3.1 ± 0.28 μM (control) was observed upon stimulation with LPS, whereas co-treatment with GTEO significantly and dose-dependently reduced LPS-stimulated NO production to 32.37 ± 12.67 μM, 20.54 ± 2.3 μM, and 10.0 ± 0.74 μM by 25, 50, and 100 μg/mL, respectively (Figure 1B). In the next step, we examined the level of PGE2 in culture media. When cells were incubated with LPS for 24 h, PGE2 production markedly increased from 54 ± 13 pg/mL to 666 ± 47 pg/mL. This increase was significantly as well as dose-dependently inhibited by GTEO, as evidenced by the PGE2 production, which was reduced to 524 ± 41, 399 ± 40, and 153 ± 7 pg/mL by 25, 50, and 100 μg/mL GTEO, respectively (Figure 1C). ## 2.3. GTEO Inhibits LPS-Induced iNOS and COX-2 Expression in RAW 264.7 Cells In order to determine whether the inhibitory effects of GTEO on the pro-inflammatory molecules (NO and PGE2) are related to the modulation of their corresponding mediators, iNOS and COX-2 genes and protein expression levels were examined. As shown in Figure 2A,B, strong iNOS and COX-2 mRNA expression levels were observed upon stimulation with LPS. Indeed, treatment with GTEO significantly down-regulated LPS-induced iNOS and COX-2 mRNA expression in a dose-dependent manner. To further confirm this effect at the translational level, immunoblotting was performed. As shown in Figure 2C, LPS-stimulation markedly increased iNOS and COX-2 protein expression, while iNOS and COX-2 levels were low or undetectable in unstimulated RAW 264.7 cells. Indeed, co-treatment with GTEO significantly and dose-dependently inhibited iNOS and COX-2 protein levels in LPS-stimulated RAW 264.7 cells. ## 2.4. GTEO Suppressed LPS-Induced NF-κB Transcriptional Activity in RAW 264.7 Cells NF-κB is a family of inducible transcription factors that are involved in a wide array of inflammatory processes by up-regulating several inflammation-associated genes, including iNOS, COX-2, TNF-α, IL-1β, etc [20]. In order to determine whether the GTEO-mediated downregulation of iNOS and COX-2 genes was caused by the suppression of NF-κB activity, a luciferase reporter assay was performed. As shown in Figure 3A, regarding treatment with LPS a 8.6-fold increase in NF-κB reporter activity has been observed, whereas co-treatment with GTEO significantly as well as dose-dependently suppressed NF-κB reporter activity, as evidenced by the fact that reporter activity was reduced to 6.0, 4.4, and 2.4-fold by 25, 50, and 100 μg/mL, respectively. The nuclear export of cytoplasmic NF-κB is another hallmark involved in NF-κB transcriptional activity; immunofluorescence analysis enumerated LPS-stimulation markedly increased NF-κB nuclear translocation, while a significant reduction in NF-κB level in the nucleus was observed in cells which were co-treated with GTEO (Figure 3B). These results suggesting that GTEO might interfere with the dissociation of I-κB from the NF-κB/I-κB cytosolic complex, hence inhibiting the nuclear translocation of NF-κB. The process of transcriptional activation followed by nuclear translocation of NF-κB is regulated by the phosphorylation and proteosomal degradation of its endogenous repressor, I-κBα [21]. Therefore, the effect of GTEO on total and phosphorylated I-κBα protein expression was determined in LPS-induced RAW 264.7 cells. Western blot analysis exhibited a remarkable increase in the phosphorylation of I-κBα at Ser$\frac{32}{36}$ after LPS stimulation, while co-treatment with GTEO showed a significant reduction in LPS-induced phosphorylation of I-κBα which corresponded directly to the significant increase in cytosolic I-κBα (Figure 4). In addition, the phosphorylation of IKKα, an up-stream kinase of I-κBα, was significantly inhibited by GTEO in a dose-dependent manner (Figure 4). However, neither LPS nor GTEO affected the total IKKα level. ## 2.5. Chemical Compositions of G. tenuifolia Essential Oil The yield of G. tenuifolia essential oil (GTEO) obtained by hydrodistillation was $0.08\%$ (w/w). The major chemical constituents of the essential oil and their relative amounts were determined by GC–MS analysis. The GC–MS profiles and the major compounds of GTEO are shown in Figure S1. The relative contents (%) in GTEO are shown in Table 1. A total of 21 compounds were identified in GTEO, accounting for $95.95\%$ of the whole oil. The major components in GTEO were p-cymene ($35.5\%$), β-myrcene (14.68), β-cedrene (9.8), cis-β-ocimene (8.49), α-pinene (6.69), and D-limonene (5.17), which made up around $74.96\%$ of the content of the GTEO. ## 2.6. Nitric Oxide Inhibitory Effects of Major Constituents of GTEO A previous study reported that α-pinene, β-pinene, limonene, p-cymene, and β-phellandrene are major components of GTEO [19]. In contrast, β-phallandrene was not found, while cis-β-ocimene and β-cedrene were found in our sample. In order to further investigate GTEO’s anti-inflammatory effects, its major compounds were tested for their NO inhibitory effects. Prior to investigating anti-inflammatory effects, MTT tests were performed to assess cytotoxicity. Treatment with either p-cymene, α-pinene, β-pinene, or limonene did not display cytotoxicity in RAW 264.7 cells up to a concentration of 100 μM, while cis-β-ocimene and β-myrcene exhibited cytotoxicity over a dose of 25 μM for 24 h (Figure S2). Therefore, the NO inhibitory effects of p-cymene, α-pinene, β-pinene, and D-limonene were investigated. Interestingly, a significant and dose-dependent inhibition of NO production was achieved by p-cymene, α-pinene, and limonene in LPS-stimulated RAW 264.7 cells. However, treatment with β-pinene failed to modulate LPS-induced NO production (Figure 5). These results clearly indicate that α-pinene, limonene, and p-cymene could be responsible for the anti-inflammatory effects of GTEO. ## 3. Discussion Compared to conventional therapies, complementary and alternative treatments have been increasingly popular as a growing body of evidence has clarified their efficacy, safety, and mechanism of action. The herb G. tenuifolia has been used for thousands of years to treat inflammation and liver diseases in Taiwan [16]. A number of recent studies have revealed that G. tenuifolis has various bio-pharmaceutical properties that extend beyond its original use. Accordingly, G. tenuifolia possesses anti-microbial [8], anti-inflammatory [9,10], anti-fatigue [11], antioxidant [12,13], antiviral [10], anti-angiogenesis [14], anti-cancer [15], hepatoprotection [16,17], and immunomodulatory effects [6,18]. In particular, G. tenuifolia has been shown to have powerful anti-inflammatory properties. Wu et al. [ 9] reported that ethanol extract of G. tenuifolia inhibits LPS-induced NO, PGE2, TNF-α, IL-1β, IL-6, and IL-12 production in cultured RAW 264.7 cells. The inhibition of NO and PGE2 was reasoned by decrease in the protein and mRNA levels of their mediators iNOS and COX-2, respectively. Further analysis revealed that G. tenuifolia attenuates inflammatory mediators in LPS-induced macrophages by suppressing the transcriptional activity of NF-κB. A following study [10] also reported that ethanol extract of G. tenuifolia inhibits LPS-induced TNF-α and IL-6 production in human whole blood and peripheral blood mononuclear cells (PBMC), and secretion of IFN-γ in PHA-stimulated human whole blood. In addition, this study also revealed that ethanol extract of G. tenuifolia had potent anti-hepatitis B virus (HBV) activity on the human hepatocellular carcinoma cell line (PLC/PRF/5). Another study further explained G. tenuifolia’s suppressive effect on NF-κB transcriptional activity in TNF-α-induced human umbilical vein endothelial cells (HUVECs) [22]. Ethanol extract of G. tenuifolia and its major components, luteolin and luteolin-7-glucoside, inhibits adhesion molecules including intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), which in turn are mediated through blocking the activation and nuclear translocation of NF-κB [22]. In contrast, ethanol, n-hexane, ethyl acetate, and methanol extracts of the whole, areal, and roots of G. tenuifolia increased NO production in HUVECs; this increase was associated with the upregulation of endothelial nitric oxide synthase (eNOS) [23]. Several studies have investigated the anti-inflammatory mechanism of G. tenuifolia, but all of them have focused on various extracts of G. tenuifolia. However, the bioactivities, including the anti-inflammatory property of G. tenuifolia essential oil, are largely unexplored. In this study, it was found that GTEO treatment inhibited pro-inflammatory molecules in LPS-induced macrophages by suppressing NF-κB signaling. It has been well demonstrated that macrophages are critical immune effector cells and that they are sensitive to bacterial endotoxins such as LPS. In response to LPS stimulation, macrophages release pro-inflammatory cytokines, chemokines, and adhesion molecules [24]. NO, a prominent pro-inflammatory chemokine, functions as an intracellular messenger which regulates vasodilation and removes pathogens and tumor cells. However, aberrant production of NO can lead to several pathological conditions, including inflammation, asthma, diabetes, and septic shock [25]. Stimulating RAW 264.7 cells with LPS, NO is secreted into the culture media, which is measured by nitrite, a non-volatile breakdown product [26]. Our findings indicate that GTEO significantly inhibits LPS-induced NO production in RAW 264.7 cells. It is known that activated macrophages secrete PGE2 as one of their stable prostanoids, which can be detected in the culture media [27]. We found that GTEO strongly inhibited LPS-induced PGE2 secretion in RAW 264.7 cells. iNOS is an enzyme involved in reactive oxygen and nitrogen metabolism, while COX-2 catalyzes the rate-limiting step in prostaglandin biosynthesis [28]. Indeed, NO derived from iNOS and PGE2 is synthesized by COX-2. Therefore, we hypothesized that the inhibition of NO and PGE2 may result in downregulation of their mediator genes—iNOS and COX-2. As we expected, GTEO significantly and dose-dependently down-regulated iNOS and COX-2 expression at both the transcriptional and translational levels. The endotoxin LPS can activate NF-κB, a redox-sensitive transcription factor, and leads to the transcriptional activation of response genes such as iNOS and COX-2 [20]. Therefore, we determined whether suppression of NF-κB activity was a reason for iNOS and COX-2 downregulation. GTEO inhibits NF-κB activity, as evidenced by reduced promoter activity followed by nuclear export determined by a luciferase reporter assay and immunofluorescence, respectively. The nuclear translocation of the p65/p50 complex is an essential step involved in NF-κB transcriptional activation, which is controlled by phosphorylation and degradation of its repressor, I-κB [20]. In this study, we found that LPS treatment dramatically increased phosphorylation of I-κBα at Ser$\frac{32}{36}$ residues, whereas GTEO treatment significantly reduced I-κBα phosphorylation and restored the total level, thereby inhibiting NF-κB activity. Additionally, I-κBα phosphorylation is regulated by its upstream kinase IKKα [20]. Upon stimulation by endotoxin, IKKα is phosphorylated and further activates I-κBα. Our data indicate that GTEO treatment significantly inhibited LPS-mediated IKKα phorphorylation in a dose-dependent manner. However, the total form of IKKα was unaffected by either LPS or GTEO. Chyau et al. [ 19] extracted G. tenuifolia essential oil from dried herbs, which are collected in the four seasons in Taiwan. Chemical fingerprint analysis revealed that essential oils from the four seasons had similar volatile profiles. In total, 62 compounds were isolated using the simultaneous steam distillation and solvent extraction method. Among them, 30 compounds were chemically identified, including 13 terpenes, 16 oxygen-containing compounds, and one other compound. Indeed, terpenes constituted 61.3–$76.0\%$ of the total amount, with $69.1\%$ on average. Eight compounds, p-cymene, β-pinene, β-phellandrene, limonene, cryptone, α-pinene, 4-terpineol, and γ-muurolene were identified as the most abundant compounds, making up $71.5\%$ of the average GTEO. Several studies have investigated the anti-inflammatory effects of terpenes isolated from various essential oils. Kim et al. [ 29] reported that α-pinene inhibits the LPS-induced secretion of NO, TNF-α, and IL-6 in murine peritoneal macrophages through suppression of mitogen-activated protein kinases (MAPKs) and NF-κB signaling pathways. A study conducted on the anti-inflammatory property of β-pinene demonstrated that treatment with β-pinene inhibited carrageenan-induced paw edema in diabetic mice [30]. Limonene, a mono-terpene has been reported to inhibits LPS-induced NO and PGE2 production in RAW 264.7 cells via down-regulating their corresponding mediators, iNOS and COX-2 [31]. p-*Cymene is* a monocyclic monoterpene reported to inhibit LPS-induced NO and TNF-α production in murine peritoneal macrophages [32]. Likewise, 4-terpineol, the main component of tea tree essential oil, inhibits LPS-induced TNF-α, IL-1β, IL-8, IL-10, and PGE2 in human peripheral blood monocytes [33]. In the present study, we also found that α-pinene, limonene, and p-cymene significantly inhibited LPS-induced NO production in RAW 264.7 cells. According to our result, cis-β-ocimene and β-myrcene did not show NO inhibitory effects in the tested conditions up to a dose of 100 μM. However, both of these compounds exhibited cytotoxicity over a dose of 25 μM; thus, it may be of interest to further investigate its cytotoxic effects in various cancer cells. ## 4.1. Preparation of G. tenuifolia Essential Oil G. tenuifolia was collected in March 2022 from the Penghu Islands, Taiwan. 250 g of the air-dried and chopped whole plant of G. tenuifolia and 1.5 L of distilled water were added into 2 L flask (Clevenger-type apparatus), and hydrodistillation was carried out for 6 h. On completion of the extraction process, essential oil was collected. The oil yield was calculated as: Yield (%) = (weight of essential oil recovered/weight of air-dried whole plant) × 100. The oil content was then determined. G. tenuifolia essential oil (GTEO) was stored in airtight sample vials prior to bioactivity evaluation. ## 4.2. Chemicals and Reagents Dulbecco’s Modified Eagle’s medium (DMEM), fetal bovine serum (FBS), glutamine, and penicillin/streptomycin were obtained from Life Technologies (Grand Island, NY, USA). 3-(4,5-dimethyl-thiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) and 4′-6-diamidino-2-phenylindole (DAPI) were obtained from Sigma-Aldrich (St. Louis, MO, USA). Specific antibodies against iNOS, COX-2, IKKα, phos-IKKα, I-κBα, phos-I-κBα, NF-κB, and horseradish peroxidase (HRP)-conjugated anti-goat, anti-rabbit, and anti-mouse IgG secondary antibodies were obtained from Cell Signaling Technology (Danvers, MA, USA). Antibodies against glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was obtained from Santa Cruz Biotechnology Inc. (Dallas, TX, USA). All other chemicals were of the highest grade commercially available and supplied either by Merck (Darmstadt, Germany) or Sigma (St. Louis, MO, USA). ## 4.3. Cell Culture and Cell Viability Assay RAW 264.7 murine macrophage cells were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA). As recommended by ATCC, cells were cultured at 37 °C in DMEM with $10\%$ FBS, 4.5 g/L glucose, 4.5 mM glutamine, 100 units/mL penicillin, and 100 g/mL streptomycin. An MTT colorimetric assay was used to determine cell viability. Briefly, in 96-well culture plates, RAW 264.7 cells (1 × 104 cells) were seeded. We incubated cells with varying doses of GTEO (25–200 µg/mL) in the presence or absence of LPS (1 μg/mL) for 24 h. After treatment, the culture medium was removed and cells were incubated with MTT (10 µg/mL) in 200 µL of fresh DMEM for 1 h at 37 °C. Violet formazan crystals generated by MTT were dissolved in 200 μL of DMSO, and an ELISA microplate reader was used to measure absorbance at 570 nm (A570) and the background control at 630 nm (A630) (µQuant, Bio-Tek Instruments, Winooski, VA, USA). Cell viability (%) was calculated as: [(A570 − A630 of treated cells/(A570 − A630) of untreated cells) × 100. ## 4.4. Determination of NO and PGE2 NO levels in the culture media were determined using the Greiss reaction assay as described previously [34]. Briefly, RAW 264.7 cells (1 × 104 cells/well) were seeded in a 96-well culture plate. Cells were treated with LPS in the presence or absence of various doses of GTEO (25–100 μg/mL) for 24 h. After treatment, an equal volume of culture supernatants was mixed with Griess reagent and incubated at room temperature for 30 min. The intercellular level of nitrate, a major stable product of NO, was measured with an ELISA microplate reader at 540 nm (µQuant, Bio-Tek Instruments, Winooski, VA, USA). On the other hand, intercellular PGE2 levels were determined using an EIA kit (R&D Systems, Minneapolis, MN, USA) according to the manufacturer’s protocols. ## 4.5. RNA Extraction and Q-PCR Analyses RAW 264.7 cells (1 × 106 cells/dish in 6-cm dish) were treated with LPS in the presence or absence of various doses of GTEO (25–100 μg/mL) for 6 h. After treatment, total RNA was extracted from cultured RAW 264.7 cells using the Trizol Reagent (Thermo Fisher Scientific, Waltham, MA, USA). A NanoVue Plus spectrophotometer (GE Health Care Life Sciences, Chicago, IL, USA) was used to quantify total RNA concentration. Real-time PCR detection system and software (Applied Biosystems, Foster City, CA, USA) was used for quantitative PCR. A SupeScript IV reverse transcriptase kit (Invitrogen, Waltham, MA, USA) was used to generate first-strand cDNA. A qPCR reaction was performed to quantify mRNA expression for genes of interest using equal volumes of cDNA, forward and reverse primers (10 μM), and power SYBR Green Master Mix (Applied Biosystems) under the following conditions: 96 °C for 3 min followed by 40 cycles at 96 °C for 1 min, 50 °C for 30 s, and 72 °C for 90 s. The primer sequences of each gene for qPCR were as follows. iNOS: forward primer (F), 5′-TCCTACACCACACCAAAC-3′; reverse primer (R), 5′-CTCCAATCTCTGCCTATCC-3″ COX-2: forward primer (F), 5′-CCTCTGCGATGCTCTTCC-3′; reverse primer (R), 5′-TCACACTTATACTGGTCAAATCC-3′; GAPDH: forward primer (F), 5′-TCAACGGCACAGTCAAGG-3′; reverse (R), 5′-ACTCCACGACATACTCAGC-3′. The copy number of each transcript was calculated as the relative copy number normalized by the GAPDH copy number. The relative abundance of target mRNA for each sample was calculated from the ΔCt values for the target and endogenous reference gene GAPDH using the 2ΔCt cycle threshold method. ## 4.6. Protein Extraction and Immunoblotting RAW264.7 cells (1 × 106 cells/dish in 6-cm dish) were co-treated with LPS with or without various doses of GTEO (25–100 μg/mL) for various time points. After treatment, cells were detached and washed in cold PBS twice. Then, they were lysed in a radioimmunoprecipitation assay (RIPA) buffer (Pierce Biotechnology, Rockford, IL, USA). The concentrations of proteins were determined using a Bio-Rad protein assay reagent (Bio-Rad Laboratories, Hercules, CA, USA). Equal amounts of protein samples (60–100 mg/well) along with sample dye were denatured for 5 min at 94 °C. SDS-PAGE was used to separate the protein samples, followed by overnight transfer onto polyvinylidene fluoride (PVDF) membranes. The membranes were blocked with $0.1\%$ Tween-20 in PBS containing $5\%$ non-fat skim milk for 30 min at room temperature, reacted with primary antibodies for 2 h, and then incubated with either HRP-conjugated goat anti-rabbit or anti-mouse antibodies for 1 h. An enhanced chemiluminescence reagent (Advansta, Inc., San Jose, CA, USA) was used to develop the immunoblots, images were captured by the ChemiDoc XRS+ docking system, and the protein bands were quantified by using Imagelab software (Bio-Rad Laboratories, Hercules, CA, USA). ## 4.7. Immunofluorescence Assay RAW 264.7 cells at a density of 1 × 104 cells/well were cultured in an 8-well glass Nunc Lab-Tek chamber slide (Thermo Fisher Scientific) treated with LPS in the presence or absence of various doses of GTEO (25–100 μg/mL) for 1 h. After treatment, cells were washed with PBS twice, fixed in $4\%$ paraformaldehyde in PBS for 15 min at room temperature, permeabilized with Triton X-100 in PBS for 10 min, washed and blocked with $10\%$ FBS in PBS, and then incubated for 2 h with anti-NF-κB antibody in $1.5\%$ FBS. The cells were then incubated with the fluorescein isothiocyanate (FITC) and conjugated with a secondary antibody for another 1 h in $6\%$ BSA. Next, the nucleus was stained with 1 μg/mL DAPI for 5 min, washed with PBS, and visualized using a florescence microscope (Motic Electronic Group, Fujian, China) at 100× magnification. ## 4.8. Luciferase Reporter Assay A dual-luciferase reporter assay system (Promega, Madison, WI, USA) was used to measure NF-κB transcriptional activity as described previously [34]. Briefly, RAW 264.7 cells were incubated for 5 h in DMEM without antibiotics in a 24-well culture plate that had reached 70–$80\%$ confluency. By using lipofectamine 2000 (Invitrogen), cells were transfected with a pcDNA vector or an NF-κB construct along with β-galactosidase. Cells were treated with LPS in the presence or absence of various doses of GTEO (25–100 μg/mL) for 2 h. The relative fluorescence intensity was quantified using a spectrometer (Hidex Oy, Turku, Finland) at 405 nm (A405). The fold increase of luminescence activity was calculated as (A405 of treated cells/A405 of untreated cells). The luciferase activity was normalized to β-galactosidase activity in the cell lysates. ## 4.9. GC-MS Analysis To determine the chemical composition of GTEO, GC-MS analysis was carried out using an ITQ 900 mass spectrometer coupled with a DB-5MS column as described previously [35]. The temperature program was as follows: 45 °C for 3 min, then increased to 3 °C/min to 180 °C, and then increased to 10 °C/min to 280 °C hold for 5 min. The other parameters were injection temperature, 240 °C; ion source temperature, 200 °C; EI, 70 eV; carrier gas, He 1 mL/min; and mass scan range, 40–600 m/z. The volatile compounds were identified by the Wiley/NBS Registry of mass spectral databases (V. 8.0, Hoboken, NJ, USA), National Institute of Standards and Technology (NIST) Ver. 2.0 GC/MS libraries, and the Kovats indices were calculated for all volatile constituents using a homologous series of n-alkanes C9–C24 [36]. The major components were identified by co-injection with standards (wherever possible). ## 4.10. Statistical Analysis Data are expressed as mean ± SD. All data were analyzed using the statistical software Graphpad Prism version 6.0 for Windows (GraphPad Software, San Diego, CA, USA). Statistical analysis was performed using one-way ANOVA followed by Dunnett’s test for multiple comparisons. A p-value of less than 0.001 Δ was considered statistically significant for the LPS alone vs. control group. p-values of less than 0.05 *, 0.01 **, and 0.001 *** were considered statistically significant for the LPS + GTEO treatment groups vs. LPS alone treatment group. ## 5. Conclusions In the present study, we report for the first time the anti-inflammatory properties of G. tenuifolia essential oil as well as its mechanism of action. 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--- title: Changes in Left Ventricular Ejection Fraction and Oxidative Stress after Phosphodiesterase Type-5 Inhibitor Treatment in an Experimental Model of Retrograde Rat Perfusion authors: - Milos Krivokapic - Israpil Alisultanovich Omarov - Vladimir Zivkovic - Tamara Nikolic Turnic - Vladimir Jakovljevic journal: Medicina year: 2023 pmcid: PMC10054412 doi: 10.3390/medicina59030458 license: CC BY 4.0 --- # Changes in Left Ventricular Ejection Fraction and Oxidative Stress after Phosphodiesterase Type-5 Inhibitor Treatment in an Experimental Model of Retrograde Rat Perfusion ## Abstract Background and objectives: Taking into consideration the confirmed role of oxidative stress in ischemia/reperfusion injury and the insufficiency in knowledge regarding the phosphodiesterase 5 (PDE5)-mediated effects on the cardiovascular system, the aim of our study was to investigate the influence of two PDE5 inhibitors, tadalafil and vardenafil, with or without the addition of N(G)-nitro-L-arginine methyl ester (L-NAME), on oxidative stress markers, coronary flow and left ventricular function, both ex vivo and in vivo. Methods: This study included 74 male Wistar albino rats divided into two groups. In the first, 24 male Wistar rats were orally treated with tadalafil or vardenafil for four weeks in order to perform in vivo experiments. In the second, the hearts of 50 male Wistar albino were excised and perfused according to the Langendorff technique in order to perform ex vivo experiments. The hearts were perfused with tadalafil (10, 20, 50 and 200 nM), vardenafil (10, 20, 50 and 200 nM) and a combination of tadalafil/vardenafil and L-NAME (30 μM). The CF and oxidative stress markers, including nitrite bioaviability (NO2−), superoxide anion radical (O2−), and the index of lipid peroxidation, were measured in coronary effluent. Results: The L-arginin/NO system acts as the mediator in the tadalafil-induced effects on the cardiovascular system, while it seems that the vardenafil-induced increase in CF was not primarily induced by the NO system. Although tadalafil induced an increase in O2− in the two lowest doses, the general effects of both of the applied PDE5 inhibitors on oxidative stress were not significant. The ejection function was above $50\%$ in both groups. Conclusions: Our results showed that both tadalafil and vardenafil improved the coronary perfusion of the myocardium and LV function by increasing the EF. ## 1. Introduction Phosphodiesterase inhibitors (PDIs) selectively antagonize phosphodiesterase (PDE), which catalyzes cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP), and is an important determinant in the regulation of the intracellular concentrations and biological actions of these secondary messengers. PDE5, which is cGMP-specific, is found in high abundance in a variety of human cells [1]. These phosphodiesterase inhibitors are drugs that can accumulate nitric oxide, which is formed from cGMP, and as a result, vasodilatation begins in the corpus cavernosum and vasculature among lungs. These physiological properties of PDE-5 inhibitors are a good choice in treating erectile dysfunction and pulmonary arterial hypertension [2]. As the myocardial tissue contains PDE-5, it is possible that this could also be cardioprotective [3,4]. The cardioprotective effect of PDIs has been linked with apoptosis and necrosis by using the many signaling mechanisms, such as the higher expression of nitric synthase (endothelial and inducible), the activation of the protein C and G kinases, etc. Generally, it is suspected that PDE5 is not present in normal myocytes, and the selective inhibition of type 5 PDE likely does not have an inotropic effect in physiological conditions [5]. Sildenafil (Viagra®), vardenafil (Levitra®), and tadalafil (Cialis®) are three major PDE5 inhibitors. Sildenafil was the first PDE5 inhibitor shown to exert a protective effect against ischemia-reperfusion injury in the hearts of rabbits, mice, rats, and dogs [6,7,8]. It is also known that sildenafil acts as a reductor of pulmonary and systemic resistance. In addition, sildenafil improves pulmonary gas diffusion and increases cardiac output. The hemodynamic effects of sildenafil are based on changing the left ventricular pressure and lead to an improvement in left ventricular function [8]. Similarly, tadalafil acts on the Beta-adrenergic signaling cascade in the heart, which is the most highly responsible mechanism of these drugs. In addition, the myocardial response to catecholamine stimulation is some kind of outcome of Beta stimulation. In this case, phosphodiesterase inhibition is highly responsible for changing the function of the myocardium [6,7,8,9]. It is well known that oxidative stress impairs the vasodilation of the coronary, pulmonary, and peripheral vasculature [9]. The state of oxidative stress as an imbalance of pro-oxidants and antioxidants in the body is the key mechanism underlying myocardial infarction. Free radicals can be divided into two categories: reactive oxygen species (ROS) and reactive nitrogen species (RNS). Additionally, enzymatic antioxidant defense, including superoxide dismutase, glutathione peroxidase and catalase activity, is very important for maintaining health [10]. Thus, when the content of ROS and RNS in an organism exceeds the scavenging ability of its own antioxidant capacity, this can destroy the redox balance and trigger various areas of damage in different organs [10]. However, there is a lack of information regarding the effect of PDE5 inhibitors on endothelial oxidative status. Previous studies have suggested that sildenafil could prevent oxidative stress by reducing the free radicals and improving the antioxidant enzyme systems [10]. On the other hand, vardenafil could reduce the formation of 3-nitrotyrosine and increase the bioavailability of nitric oxide in rat models and human studies [11]. The balance between the production and removal of cGMP is an important regulator of coronary blood flow [12]. Through NO/cGMP-dependent pathways, vardenafil relaxes the resistance in coronary vessels [13]. While these effects have been widely reproduced, a smaller number of studies have attested a similar cardioprotective effect of vardenafil and tadalafil [14]. Taking into consideration the confirmed role of oxidative stress in cardiac homeostasis and the insufficient knowledge about the PDE5-mediated effects on the cardiovascular systems, the aim of our study was to investigate the influence of two PDE5 inhibitors, tadalafil and vardenafil, with or without the addition of N(G)-nitro-L-arginine methyl ester (L-NAME), on oxidative stress markers, coronary flow, and left ventricular function, ex vivo and in vivo. ## 2.1. Ethical Concerns All research procedures were carried out in accordance with the EU Directive $\frac{2010}{63}$/EU for animal experiments and the principles of Good Laboratory Practice (GLP), approved by the ethical committee of the Faculty of Medical Sciences, University of Kragujevac, Serbia and Ministry of Health, Republic of Serbia. ## 2.2. Animals This study included 74 male Wistar albino rats divided into two groups. In the first, 24 male Wistar rats were orally treated with tadalafil or vardenafil for 4 weeks in order to perform in vivo experiments. In the second, the hearts of 50 male Wistar albino were excised and perfused according to the Langendorff technique in order to perform ex vivo experiments. The animals were housed under standard controlled environmental conditions, with a temperature of 23 ± 1 °C and a $\frac{12}{12}$ h light/dark cycle. Food and water were provided ad libitum. All animals were obtained from the Military Medical Academy (Belgrade, Serbia). ## 2.3. Two-Dimensional Echocardiography of Rat Heart In Vivo In the two groups of male Wistar albino rats ($$n = 24$$; 8 weeks old, 200 ± 30 g) who were treated with tadalafil and vardenafil (20 mg/bw/day per os) for four weeks, the echocardiography method was used for evaluating the LV function in vivo. The transthoracic 2D echocardiography (EHO) evaluation was carried out using a Hewlett-Packard Sonas 55000 (Palo Alto, CA, USA) sector scanner furnished with an MHz phased-array transducer. The rats were anesthetized by an intraperitoneal injection mixture of 10 mg/kg ketamine (0.025 mL of 100 mg/mL, Pfizer Pharmaceuticals, New York, NY, USA) and 2 mg/kg xylazine (0.025 mL of 20 mg/mL, Intechemie, Waalre, Holland) [15]. The following structural variables were measured:Interventricular septal wall thickness at end-diastoles (IVSds) and end-systoles (IVSs);Left ventricle (LV) internal dimension at end-diastoles (LVIDds) and end-systoles (LVIDs);LV posterior wall thickness at end-diastoles (LVPWds) and end-systoles (LVPWs);Fractional shortening (FS) percentage. On M-mode tracking, the average values were derived from a minimum of five cardiac sets. The ejection fraction (EF) values were calculated according to the Teicholz formula:EF = 100 × (LVEDV − LVESV)/LVEDV LVESV = 7 × LVESD/(2.4 + LVESD); LVEDV = 7 × LVEDD/(2.4 + LVEDD) ## 2.4. Retrograde Perfusion of Rat Heart From fifty male Wistar albino rats (aged 8 weeks, weight circa 200 g), the hearts were isolated according to the Langendorff technique [16]. Langendorff apparatus is a system for retrograde perfusion ex vivo, purchased from Experimetria Ltd., Budapest, Hungary, which mimics the physiological conditions of heart pumping. After using general anesthesia (ketamine/xylazine), the rats were sacrificed, and using surgical intervention, the rat hearts were isolated. Immediately after that, the aortas were cannulated and the hearts were perfused with Krebs–Henseleit solution, which contains the following substances in mmol/1: NaCl 118, KCI 4.7, CaCI2 • 2H2O 2.5, MgSO4 • 7H2O 1.7, NaHCO3 25, KH2PO4 1.2, glucose 11, and pyruvate 2, equilibrated with $95\%$ O2 plus $5\%$ CO2 and warmed to 37 °C (pH 7.4). After a period of stabilization for 30 min, perfusion was performed at gradually increasing pressures, from 70 to 120 cm H2O. Coronary venous effluent was continuously collected (mL/min) and measured twice for each pressure of the water column [16]. The hearts were perfused with the PDE5 inhibitors, tadalafil (PubChem CID 110635) (10, 20, 50, 200 nM) and vardenafil (PubChem CID 110634) (10, 20, 50, 200 nM), separately or with an inhibitor of nitric oxide synthesis, N(G)-nitro-L-arginine methyl ester (PubChem CID 39836) (L-NAME, 30 μM, minimum 5 min), and compared with the controls, respectively. The testing of the substances was started after the control perfusion and after stabilization for a minimum of 5 min at each point of coronary perfusion pressure. ## 2.5. Measuring of Biomarkers of Oxidative Stress After collecting the effluent, spectrophotometric determination was used to measure the various markers of oxidative stress, such as nitrites, superoxide anion radicals, and the index of lipid peroxidation. Krebs-Henseleit was always used as a blank probe. All biochemical parameters were determined spectrophotometrically using a Shimadzu UV 1800 spectrophotometer (Kyoto, Japan). ## 2.5.1. Nitrite (NO2−) Determination The determination of nitric oxide was performed by the indirect method of measuring the levels of nitrite in an effluent. Griess reagents, perfusate, and sulpho-salicylic acid were used for the procedure of determination and measured at 543 nm [15]. ## 2.5.2. Superoxide Anion Radical Determination (O2−) This biomarker of oxidative stress was determined using Nitro blue Tetrazolium and its reaction with TRIS buffer measured at 530 nm [16]. ## 2.5.3. Index of Lipid Peroxidation (Thiobarbituric Acid Reactive Substances, TBARS) The concentration of lipid peroxidation in the coronary venous effluent was measured through the estimation of thiobarbituric acid reactive substances (TBARS) using $1\%$ TBA (Thiobarbituric Acid) in 0.05 NaOH incubated with coronary effluent at 100 °C for 15 min and read at 530 nm. Krebs-Henseleit solution was used as a blank probe [17]. ## 2.6. Statistical Analysis Values are expressed as the mean ± standard error of mean. Two well-known tests of normality, the Kolmogorov-Smirnov test and the Shapiro-Wilk test, were the methods used to test the normality of the data. For testing the differences between groups in each parameter, two-way ANOVA or Student’s t test was used to confirm the differences. Normality tests and analytical tests were conducted using the statistical software SPSS version 26. The statistical significance threshold was set at 0.05. ## 3.1. LV Function using Echocardiography In Vivo This part of the study evaluates the effects of the different PDE-5 inhibitors (tadalafil and vardenafil) on LV function by ultrasound evaluation (Table 1). In the comparison of these two groups, we observed similar effects on the LV function and all tested parameters. The EF was not significantly different (Table 1). ## 3.2. Coronary Flow (CF) The coronary flow (CF) increased proportionally to the coronary perfusion pressure in the entire range of perfusion pressures studied in both the control and study groups. During the control conditions, the CF varied in a range between 3.14 ± 0.60 mL/min/g wt at 40 cm H2O and 10.40 ± 0.92 mL/min/g wt at 120 cm H2O (average values for all eight experimental protocols—Figure 1 and Figure 2). Tadalafil induced a significant increase in the CF in all applied doses (Figure 1A–D), while vardenafil induced similar changes when applied in concentrations of 20 and 200 nM (Figure 2B,D). The simultaneous application of L-NAME significantly reduced the influence of both inhibitors on the CF (Figure 1E–H and Figure 2E–H). ## 3.3. Nitrite Outflow (NO2−) Under the control conditions, the nitrite outflow varied between 4.22 ± 1.62 mL/min/g wt at 40 cm H2O and 14.36 ± 2.92 mL/min/g wt at 120 cm H2O, which was parallel with the CPP–CF curve (average values for all eight experimental protocols—Figure 3 and Figure 4). Tadalafil-induced changes in the CF were accompanied by a significant increase in the nitrite outflow in all applied doses, except in the dose of 10 nM (Figure 3A–D). On the other hand, vardenafil-induced changes in the CF were accompanied by non-significant changes in the nitrite outflow in the first three doses (Figure 4A–C), while 200 nM of vardenafil significantly reduced the nitrite outflow in the isolated rat hearts (Figure 4D). The simultaneous application of L-NAME abolished the effects of tadalafil on the nitrite outflow (Figure 3E–H). In contrast, L-NAME did not significantly change the primary effect of vardenafil on the nitrite outflow (Figure 4E–H). ## 3.4. Superoxide Anion Production (O2−) Under the control conditions, the superoxide anion outflow varied between 16.88 ± 4.53 mL/min/g wt at 40 cm H2O and 40.71 ± 11.32 mL/min/g wt at 120 cm H2O and was parallel with the CPP–CF curve (average values for all eight experimental protocols—Figure 5 and Figure 6). Tadalafil- and vardenafil-induced changes in CF were accompanied by a significant increase in the superoxide anion production at all of the applied doses (Figure 5B–D and Figure 6A–D), except when these drugs were applied at a dosage of 50 nM (Figure 5C and Figure 6C). The simultaneous application of L-NAME did not induce any significant changes in the tadalafil-treated hearts (Figure 6E–H). In contrast, L-NAME induced a significant reduction in the superoxide anion production at doses of 20 and 200 nM (Figure 6E–H). ## 3.5. Index of Lipid Peroxidation (TBARS Production) Under the control conditions, the TBARS outflow varied between 3.25 ± 1.53 μL/min/g wt at 40 cm H2O and 5.23 ± 2.16 mL/min/g wt at 120 cm H2O and was parallel with the CPP-CF curve (average values for all eight experimental protocols—Figure 7 and Figure 8). Tadalafil-induced changes in the CF were accompanied by a significant increase in the TBARS production at doses of 20 and 200 nM (Figure 7B,D), while the other two doses did not induce significant changes in the TBARS production (Figure 7A,C). Furthermore, vardenafil did not induce significant changes in the TBARS production at any of the applied doses (Figure 8A–D). The simultaneous application of L-NAME did not induce any significant changes in the TBARS production in either the tadalafil- or vardenafil-treated hearts (Figure 7E–H and Figure 8E–H) compared to the controls. ## 4. Discussion The aim of our study was to assess the effects of two selective and highly affinitive PDE5 (tadalafil and vardenafil) inhibitors on the oxidative stress markers in isolated rat hearts as there is currently not enough information on these effects. Additionally, using an in vivo model, we treated rats with therapeutic doses of these drugs in order to compare their effects on LV function. In order to exclude the contribution of the L-arginin/NO system to these effects, we also performed additional experiments that consisted of the simultaneous application of a PDE5 inhibitor and L-NAME. The study design and applied doses in our work are very similar to the ones published by du Toit and coworkers, who investigated the effects of the same doses of sildenafil on the infarct size in experimental acute myocardial infarction [17]. Tadalafil and vardenafil are two of the most widely used PDE5 inhibitors in the management and treatment of chronic obstructive pulmonary disease, erectile dysfunction, pulmonary hypertension, and heart failure [17]. The main molecular mechanism is based on preventing cAMP and cGMP degradation, which induces many effects, such as muscle relaxation, vasodilatation, and bronchodilatation [18]. Both treatments could be used either as a monotherapy or in combination with other agents in relation to the condition. In the heart, the precise mechanism is based on increasing the ionized calcium, vasodilating the peripheral vessels, and preventing the platelet aggregation [19]. At the endothelial level, PDE5 inhibitors induce the realization of the nitric oxide, which relaxes the vessels in the corpus cavernosum. Previous research has suggested that these inhibitors could reduce inflammation, cell proliferation, and blood viscosity [19]. As there is a lot of vasoconstriction in heart failure, NO release is one of the major factors involved in improving heart function. Inhibitors of PDE5 exert their very important effects in the heart and myocardium, and their role can be very significant in left or right ventricular hypertrophy, or congestive heart failure [20]. The application of tadalafil induced a significant increase in the coronary flow at all applied doses. On the other hand, vardenafil induced similar effects only in two doses—the middle one (20 nM) and the highest one (200 nM)—which suggests that there is not a dose-dependent effect of this PDE5 inhibitor. When those PDE5 inhibitors were applied with the addition of L-NAME, their previously expressed effects on the coronary flow were abolished. This finding suggests an important role of the L-arginin/NO system in the PDE5 inhibitor-induced changes in the coronary flow in the isolated rat hearts. This effect is in accordance with the previously reported interaction between sildenafil and L-NAME in severe hypertension and myocardial ischemia-reperfusion injury [20]. Tadalafil-induced changes in the coronary flow were accompanied by a significant increase in the nitrite outflow in all applied doses, except in the smallest one. On the other hand, vardenafil did not induce significant changes in the nitrites unless administrated at the highest dose. The simultaneous application of L-NAME reversed the effects of tadalafil, while there were no significant changes in the case of vardenafil. This supports the hypothesis regarding the contribution of the L-arginin/NO system on the effects of tadalafil and suggests that there may be another endothelial pathway for vardenafil-induced vascular effects [21,22,23,24,25,26,27,28,29]. It seems that tadalafil expresses its effects similarly to sildenafil, through the augmentation of NO synthase and cGMP levels, which points to the possibility that the cardiovascular dysfunctions that include decreased NOS activity may be alleviated by tadalafil treatment [30,31]. The changes seen in the extent of superoxide anion radical production after administration of 10 and 20 nM of tadalafil and the absence of these changes when tadalafil was applied with L-NAME point to the role of nitric oxide synthase in the observed increase in free radical production. The results regarding the effects of vardenafil and vardenafil + L-NAME on superoxide anion radical production again suggest that there is not a possibility to establish the rule according to which vardenafil expresses its effects. The fact that the application of tadalafil in combination with L-NAME abolished the effects of tadalafil, seen in both the superoxide anion radical and nitric oxide, confirms the hypothesis regarding the role of nitric oxide synthase in the tadalafil-induced increase in oxidative stress. The effects of tadalafil on the oxidative stress markers found in our study are not in agreement with the results obtained by some other authors. In one study, tadalafil decreased the levels of hydrogen peroxide, while in two others, sildenafil expressed the same effects on both the superoxide anion radical and hydrogen peroxide [21,22,23]. However, it should be taken into account that these studies were performed on men with erectile dysfunction and models with heart failure [24,25,26,27]. In both these cases, the basic antioxidant system was seriously damaged, which was not the case in our study. The index of lipid peroxidation did not follow the dynamics observed in the above-discussed parameters following tadalafil administration. It seems that only 20 nM of tadalafil induced a similar increase in the oxidative stress parameters, which was abolished by NO releasing. The other applied doses of both inhibitors did not significantly influence the oxidative stress. The increase in the index of lipid peroxidation may be the consequence of increased nitric oxide production, which is in accordance with our previous data [28,29]. Elrod et al. observed the reduction in myocardial ischemia/reperfusion injury by sildenafil in an animal model, and that the reduction is induced by nitric oxide release [32]. Taken together with the hemodynamics examination, we can conclude that PDE-5 inhibitors, such as tadalafil and sildenafil, act similarly on cardiac function. Although there were mild changes in the oxidative stress, we have concluded that from a functional perspective, there were no significant differences affecting the LV function. This is expected because PDE5 inhibitors can cause nitrate-like hemodynamic effects, lowering wedge pressure, pulmonary dilatation, etc. This makes them useful for treating a wide range of medical conditions, now with the knowledge that oxidative stress reduction is the underlying mechanism. Finally, it is important to emphasize that the limitations of this study could have contributed to the absence of heart rate and contractility measurements, as well as cGMP concentrations (which could more clearly show interaction between the L-arginine/NO system and PDE5). However, taken together, this is one of the first experimental studies to present both ex vivo and in vivo results of heart function after sildenafil and vardenafil treatment. ## 5. 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--- title: Xanthan-Based Materials as a Platform for Heparin Delivery authors: - Narcis Anghel - Irina Apostol - Maria Valentina Dinu - Cristina Daniela Dimitriu - Iuliana Spiridon - Liliana Verestiuc journal: Molecules year: 2023 pmcid: PMC10054415 doi: 10.3390/molecules28062757 license: CC BY 4.0 --- # Xanthan-Based Materials as a Platform for Heparin Delivery ## Abstract Heparin (Hep), with its anticoagulant activity, antiangiogenic and apoptotic effects, and growth factor binding, plays an important role in various biological processes. Formulations as drug delivery systems protect its biological activity, and limit the potential side effects of faulty administration. The objective of this study was to develop novel xanthan-based materials as a delivery carrier for heparin. The materials exhibited remarkable elastic behavior and toughness without any crack development within the network, which also support their application for tissue engineering. It was found that all materials possessed the ability to control the release of heparin, according to the Korsmeyer–Peppas release model. All Hep-containing materials caused significant exchanges of the activated partial thromboplastin time (aPTT) and prothrombin time (PT) parameters, indicating that formulated natural/natural synthetic polymeric networks conserved heparin’s biological activity and its ability to interrupt the blood coagulation cascade. The obtained results confirmed that developed materials could be carriers for the controlled release of heparin, with potential applications in topical administration. ## 1. Introduction Drug delivery systems based on natural polymers became of high interest in the last decades, due to their biocompatibility and biodegradability, as well as resource availability. The presence of reactive groups on the natural polymers is a great advantage, because other functional groups could be introduced, offering new physical and chemical properties. Thus, polymer-based materials’ properties can be tailored toward specific functionalities and adapted for different applications. One of the most important applications is their use as a platform for controlled drug release. Polysaccharides, which are mostly obtained from plants, animals, microbes, and algae, are macromolecules that contain glycosidic linkages. In addition to serving as an energy source for organisms, polysaccharides play a crucial role in the functioning of cell membranes and other biological processes. Numerous biological processes, including immune system control, anti-tumor activity, control of gut flora, antioxidation, etc., are carried out by polysaccharides [1]. Polysaccharides’ structural characteristics are directly correlated with their biological activities. The structure of polysaccharides contains a variety of functional groups, including hydroxyl, amino, and carboxylic acid groups [2]. Novel biological activities of polysaccharides can be created by altering their chemical structure or adding additional groups. To deliver medications to the target site efficiently and control their pharmacokinetics, effectiveness, toxicity, immunogenicity, and biometrics, drug delivery systems employ a variety of multidisciplinary techniques. However, the rate of drug release, tissue selectivity, and drug stability in vivo are difficult to anticipate. Drug delivery systems are built with a variety of materials and chemicals policies to address these issues [3]. The creation of new intelligent drug delivery systems has a lot of potential, thanks to the growth of nanotechnology. Since the structural units of nanomaterials are often smaller than cells, they can exhibit unique functions and properties by way of their size, surface and interface effects, etc. Porous materials have gained significant attention in the field of drug delivery, due to their ability to control the release of drugs. Among various porous materials, xanthan, alginate, and polyurethanes are widely used for controlled drug delivery. The current study was dedicated to the development of novel xanthan-based materials as a delivery carrier for heparin. Xanthan (Xn) is a heteropolysaccharide that is produced by *Xanthomonas campestris* bacteria through aerobic fermentation. Repeating units of D-glucose connected by β1-4 linkages, as well as a side chain of D-mannose and D-glucuronic acid are present in the Xn macromolecular chain. The primary uses of xanthan are linked to its exceptional properties, including its high viscosity at low concentrations; its high solubility in hot and cold water; its viscoelastic behavior; its resistance to enzymatic degradation, temperature, and salt solutions; its interaction with other polymers; and also because of its straightforward processing mechanism. The xanthan molecule’s unique helical structure gives it remarkable qualities including its pseudoplastic nature and quick recovery, which expands its applications in a variety of areas such as industrial applications, biomedical engineering, and agricultural fields. In the pharmaceutical sector, drug delivery systems are where xanthan gum is most commonly used [4]. In both culinary and non-food applications, xanthan is primarily utilized as a suspending agent, viscosity maintainer, gel forming agent, and flocculator. The inclusion of xanthan to uniformly suspend solid components in formulations has improved flow behavior in fungicides, herbicides, and insecticides used in agriculture. At low temperatures, Xn presents an ordered and rigid double helical strand structure while a disordered and flexible coil structure is recorded at high temperatures. This behavior, as well as its compatibility with metallic salts, stability under a wide range of pH levels, and high viscosity at low concentrations, make it useful in specific applications [5]. Xn is also used in healthcare applications as wound dressing material [6] or as delivery systems for biologically active compounds [7]. Numerous investigations have been conducted on hydrogels based on xanthan for drug delivery purposes. Xanthan hydrogels enable the controlled release of drugs. Modified Xn with succinic anhydride has been utilized to create hydrogels that are sensitive to ionic strength for the delivery of gentamicin. A swift release of gentamicin was initially observed as the ionic strength of the release medium increased. Subsequently, sustained drug release was observed due to the strong interaction between polymer molecules, creating a compact network [8]. An in situ hydrogel was synthesized to enhance the bioavailability and contact time between the drug and the precorneal membrane for drug delivery. Mucoadhesive polymers such as Xn and sodium alginate were employed, whereas poloxamer 407 and poloxamer 188 were used to encapsulate moxifloxacin hydrochloride. The formulations developed were uniform in consistency, transparent, with good spreadability, and optimal bioadhesion properties [9]. The pore size of xanthan-based materials can be controlled by adjusting the degree of crosslinking, which affects the diffusion of drugs through the material. For example, Lee et al. developed a xanthan-based hydrogel with tunable pore sizes for the controlled release of curcumin, an anti-inflammatory drug. The hydrogel showed sustained release of curcumin for up to 24 h, and the release rate could be controlled by varying the crosslinking density of the hydrogel [10]. Alginates (Alg) are natural anionic polysaccharides that present numerous advantages such as good availability, biocompatibility, and biodegradability [11,12], and low toxicity, thickening, and gelling properties, which make them suitable for numerous applications, including drug-controlled release systems [13,14,15]. Alginates consist of 1,4-linked β-d-mannuronic acid (M) and 1,4 α-l-guluronic acid (G) residues; their composition and the sequence of G and M residues are dependent on the sources used to extract alginate. It is worth mentioning that the M/G ratio and its structure substantially influence alginate properties. Alginates may also mix consistently with a range of other polymers to make films, membranes, microbeads, scaffolds, and hydrogels that work well as platforms for research into how cells interact with their microenvironments. It is important to remember that alginates could be formed in the form of gel under mild circumstances, unlike other polysaccharides [16]. Alginates do not affect the viability of cells, and are also safe for biological systems [17]. Due to their swelling properties through the hydrophilic groups, solubility (covalent bonds prevent them from dissolving even after swelling) [18], and pH-sensitive responsiveness, alginate-based polymeric systems have been shown to be more effective in controlled/sustained drug release investigations. Since alginates contain carboxyl groups, they aid in the dissolution of alginate in neutral and alkaline pH conditions, protecting the drug molecules from acidic environments. In contrast, microbial infections have been acknowledged as a severe issue in recent years, and the substance used should be harmless and widely available. As a result, the use of naturally occurring alginate as an antimicrobial agent and as a material for wound dressings has been growing quickly for years. Alginate-based porous materials have been extensively studied for drug delivery applications, due to their ability to form gels in the presence of divalent cations such as calcium ions. The gelation process forms a network of pores that can trap drugs and control their release. Alginate-based materials can also be easily modified by incorporating other polymers or molecules to enhance their drug delivery properties. For example, Balanč et al. developed porous alginate-based microspheres loaded with resveratrol, a natural antioxidant. The microbeads exhibited a sustained release of resveratrol for up to 8 h, and the release rate could be controlled by varying the concentration of calcium ions in the polymeric matrix [19]. Alginates are readily available in a variety of forms in moderate environments without the need of hazardous chemicals. The synthetic polymers known as polyurethanes (PUs) have urethane (or carbamate) linkages (–NH–COO–) in their primary chains. The vast array of building elements that may be included into PUs allows for the customization of their material attributes to serve a number of purposes. It is significant that PUs can be produced in vast quantities and treated in a variety of ways. These factors have led to the widespread use of PUs in industry, such as for foams, coatings, fibers, adhesives, sealants, electronics, elastomers, actuators, and biomaterials [20,21]. Their biocompatibility, durability, and mechanical properties extended their application in the medical field to wound dressings, catheters, hospital beddings, or surgical drapes [22]. There has been a lot of interest in biodegradable PUs to address the requirement for tissue repair and regeneration. Biodegradable PU mimics the biomechanical behaviors of soft and elastic tissues by exhibiting high mechanical strength, softness, and high elasticity. The adaptable chemistry of PU synthesis can also produce a variety of biodegradable PUs to fulfill the unique requirements of various tissues. Hydrolyzable linkages, such as ester, amide, anhydride, and carbonate linkages, are incorporated into polymer backbones to create biodegradable polyurethanes (PUs) [23]. Thermoplastic polyurethanes (PUs) are linear, and can be produced into three-dimensional (3D) scaffolds using a number of manufacturing processes. They are referred to as elastomers because of their extreme elasticity and softness, which set them apart from widely used materials. Polyurethane-based porous materials are commonly used for drug delivery applications, due to their ability to form porous structures with high surface area and tunable pore size. The pore size of polyurethane-based materials can be controlled by adjusting the concentration of the porogen used during synthesis. The release rate of drugs from polyurethane-based materials can also be controlled by varying the degree of crosslinking, or by incorporating other polymers or molecules to modify the drug release behavior. For example, Wang et al. developed a polyurethane-based porous material loaded with doxorubicin, an anti-cancer drug. The material exhibited sustained release of doxorubicin for up to 24 h, and the release rate could be controlled by varying the degree of crosslinking [24]. It was reported [25] that PU exhibited overall biocompatibility and excellent resistance to thrombosis. Despite this, the development of polyurethane heart valves faces several points of stagnation, due to limitations in their long-term biological durability, as well as to the competition with mechanical and bioprosthetic valves. In this study, we used a water-soluble PU as a binder and plasticizer, in order to assure the mechanical strength of the developed materials [26]. This aspect is very important, while the mechanical integrity under dynamic flow conditions assures medical device function. In conclusion, xanthan, alginate, and polyurethanes are versatile materials that can be used to develop controlled drug release systems with tunable properties. The structural importance of these materials lies in their ability to form porous structures with high surface area and tunable pore size, which can be used to trap drugs and control their release. These materials have shown great potential in drug delivery applications, and further research in this area is expected to lead to the development of more effective and efficient drug delivery systems. Heparin (Hep) is a poly-anionic, poly-dispersive, highly sulfated linear polysaccharide consisting of alternating N acetyl-d-glucosamine and d-iduronate residues [27]. Heparin inhibits intracellular protein kinase activity during signal transduction [28], and modulates the function and expression of numerous growth factors. It has an important role in modulating smooth muscle cell migration, as well as in neointimal proliferation. Hep interacts with proteins through hydrophobic effects and hydrogen bonding. Being water-soluble, it is present in some tissue such as arterial blood vessels, the liver, and the lungs. It is frequently used as an anticoagulant for the prevention of venous thrombosis and pulmonary embolism. Heparin binds to antithrombin III and accelerates the enzyme-neutralizing effect of a serine protease inhibitor, thus preventing the formation of thrombin. It was approached in our study because, in our opinion, the dosages and controlled release of heparin could expand its medical applications. Due to its low half-life, *Hep is* eliminated in a short time and, as a result, its frequent use can induce systemic side effects. The interest for materials that do not provoke thrombosis, that are associated with a high level of morbidity and mortality, is continuously increasing. This is why numerous efforts are directed towards improving the biomaterials used as devices in short- or long-term treatments to prevent thrombosis. Having in mind that drug delivery systems allow reduced dosage and frequency of administration of drugs, thus reducing drug-related side effects, we used xanthan/modified xanthan, polyurethane, and alginate as a matrix to obtain materials with a controlled release of Hep. The materials were characterized in terms of mechanical and morphological properties, and the Hep release mechanism was monitored. ## 2.1. FTIR (Fourier Transform Infrared Spectroscopy) Analysis of Materials FTIR spectra of the obtained materials are shown in Figure 1. In Figure 1A are presented the FTIR spectra of xanthan–alginate-based materials. The broad adsorption bands at 3338 cm−1 are attributed to the presence of –OH groups. Stretching vibrations of aliphatic C–H were identified at 2923–2856 cm−1 [29]. The bands present in the region between 1633 and 1598 cm−1 were assigned to asymmetric and symmetric stretching vibrations of carboxylate ions. The presence of glucuronic acid residues from alginate were evidenced by the peak at 773 cm−1. The chemical modification of Xn was evidenced by the increase in the absorption band at 1737 cm−1, characteristic for the carbonyl group. Furthermore, an intensification of the stretching vibrations of the –CH2– groups at 2922 cm−1 was recorded [15,30]. In samples containing heparin (Xn–Alg–Hep and XnOA–Alg–Hep), bands at 1433–1434 cm−1 and 1029 cm−1 were recorded, corresponding to asymmetric stretching of –COO- and to asymmetric stretching of C–O–C, respectively; meanwhile, in the region 1240–1155 cm−1, characteristic absorption bands of S=O asymmetric stretching associated to sulphate groups of Hep were observed [31]. The FTIR spectra of materials based on Xn and PU are presented in Figure 1B. It was observed that a broad signal between 3348 and 3373 cm−1 remained. This signal is due to the superimposition of –NH– stretching vibrations of the urethane group of the Pus, as well as to terminal Xn or XnOA groups. Furthermore, the presence of the carbonyl group from the PU structure was evidenced by the bands from the region of 1739–1625 cm−1 [32]. The presence of heparin in Xn–PU–Hep and XnOA–PU–Hep materials was confirmed by the appearance of signals between 1430 and 1404 cm−1 attributed to –COO- group. The bands present in the region of 1037 cm−1 correspond to asymmetric stretching of C–O–C bonds [31]. In the region of 1249 cm−1, characteristic signals of asymmetric stretching of S=O group were observed. Comparing heparin-containing samples’ spectra with the FTIR spectra of Hep, some shifting in the peaks was observed from 1434 cm−1 to 1431 cm−1, or from 1041 cm−1 to 1035 cm−1. These shifts were attributed to strong hydrogen bonding interactions between polymeric matrices and heparin [33]. ## 2.2. Mechanical Properties The uniaxial compressive measurements were used to assess the elasticity, toughness, and stability of various materials based on the xanthan/chemically modified xanthan matrix loaded with heparin (Hep). The assessment of the influence of the materials formulations on the compressive mechanical performance sponges revealed that all materials exhibited typical compressive stress–strain (σ–ε) profiles characteristic of macroporous materials, as shown in Figure 2A. All of the formulations could be compressed to over $50\%$ strain without any fracture development, due to the complete release of solvent (ethanol) from the macroporous structures of the formulations (see SEM images, Figure 3) upon compression. In addition, as Figure 2A shows, the stress–strain profile of the Xn–Alg–Hep system comprised the following three domains: [1] up to $15\%$ strain was observed as an initial linear elastic domain; [2] up to around $60\%$ plateau domain strain was noted; and afterwards, [3] a densification domain as a result of the gradual compression of the pores was observed. On the other hand, the stress–strain profiles of the Xn–PU–Hep, XnOA–Hep, and XnOA–PU–Hep systems revealed only two regions: the linear elastic domain up to about $80\%$, $68\%$, and the $61\%$ strain and beyond the densification domain. Therefore, the elasticity and toughness of the prepared materials could be controlled either by incorporation of PU within the Xn matrix, or by its modification with OA. Other authors reported similar results related to the same systems loaded with antifungal or anti-inflammatory compounds [15], or for other gels based on an alginate/gelatin methacryloyl interpenetrating network [34] nano clay and natural polysaccharides [35], or for sponge-based systems on two oppositely charged polyelectrolytes (chitosan and poly(cyclodextrin citrate)) [36]. The elastic moduli (G, kPa) of all formulations were determined from the slopes of the linear parts of the stress−strain curves (Figure 2B), in agreement with the protocol already established for materials having Xn as a matrix component [15]. As can be seen from Figure 2C, the Xn–Alg–Hep system exhibited the highest elastic modulus, being fifteen-times higher than that of the Xn–PU–Hep system. The mechanical properties of the Hep-containing formulations depend on the composition of the formulation of the matrix, i.e., the presence of Alg or PU in the mixture with Xn (Figure 2C,D). All samples exhibited remarkable elastic behavior and toughness without any crack development within the network, which also supports their applications for tissue engineering. The Xn–Alg–Hep formulations exhibited a modulus of elasticity of 36.71 kPa and a compressive strength of 49.94 kPa at $77.34\%$ strain, while the Xn–PU–Hep formulations displayed a modulus of elasticity of only 2.48 kPa and a compressive strength of 34.37 kPa at $80.44\%$ strain, which support a robust network with high toughness for the former ones. The use of XnOA in the preparation of Hep-loaded formulations led to more rigid networks, since the maximum sustained compression decreased to $68.39\%$ for the XnOA–Alg–Hep formulation and $60.86\%$ for the XnOA–PU–Hep material. Thus, the sustained compression of Xn-based formulations could be modulated either by changing the entrapped polymer (Alg or PU) or by modification of Xn with AO. The variety of pore sizes displayed by the Xn-based formulations (Table 1) support different applications for these materials. Generally, large pores are beneficial for cell attachment [37], while small pores enhance the mechanical performance of porous scaffolds/constructs [38]. Thus, the improvement in the compressive nominal stress of materials could be correlated to the decrease in pore sizes and in the wall thickness (Table 1), and to non-covalent interactions established between components of materials, which provide the basis for energy dissipation required for the improvement in the material’s mechanical properties [39]. ## 2.3. Drug Delivery The release of drugs from the polymeric matrix was also studied. The importance of mathematical models in the evaluation of drug release processes is well known. The kinetics models have the role of clarifying the release mechanism, and allowing the measurement of some important parameters. Two mathematical models were used to fit the release data: the Korsmeyer–Peppas and Higuchi models [40]. The Higuchi equation is based on Fick’s first law of diffusion, which was the starting point for quantitative measurements in the controlled release studies. The Higuchi model was developed to cover various porous systems and especially for evaluating the release kinetics of water-soluble and encapsulated materials with a low solubility that are encapsulated into solid matrices. The Higuchi model was used to assess the release kinetics of the active agents from the porous materials. Equation [1] represents the simplified Higuchi model:[1]Mt=kH×t where kH is the release constant of Higuchi expressed in mg × min−$\frac{1}{2}$, and *Mt is* the concentration at time t. The Korsmeyer–Peppas model was developed to describe the drug release from polymeric systems (Equation [2]):[2]MtM∞=k×tn where M∞ is the amount of drug in the initial state, *Mt is* the amount of drug released at time t, k is the release rate constant expressed in min−n, and n (dimensionless) is the exponent of release as a function of time t. A value of the exponent of release equal to 0.5 indicates a Fickian diffusion mechanism of the drug from the inside of the material (the drug release is governed by diffusion), while a value of the exponent of release between 0.5 and 1 indicates non-Fickian diffusion (the drug release is governed by the swelling or relaxation of the polymeric chain). Hep was not covalently bound in either the Xn–Alg/XnOA–Alg or Xn–PU/XnOA–PU matrix, but there was no doubt that electrostatic synergy was formed between heparin and the matrix components. A similar release trend was observed for all materials. Figure 4 and Table 2 show information related to the Hep release profile from the studied materials. According to this information, our experimental data were best fitted by the Korsmeyer–Peppas model. Xn–Alg–Hep, XnOA–Alg–Hep, and XnOA–PU–Hep presented non-Fickian transport (n value between 0.63 and 0.69), with heparin being released due to the combined effect of diffusion and polymer swelling. The amount of drug released at the initial burst phase, as well as the cumulative amount of drug released, were related to the porosity of the microparticles. As seen in Figure 4, the materials comprising unmodified Xn presented a faster release profile, probably due to its hydrolytic degradation (rate constant between 2.6–2.9). The use of XnOA as a polymeric matrix component led to a slower release process of Hep (rate of the drug release between 0.5–1.7). The values of the transport parameter n (Table 2), being greater than 0.5 for all the tested materials, indicated non-Fickian diffusion. However, a value of 0.88 suggests a more significant contribution of swelling and/or erosion to the drug release mechanism, compared to a value of 0.62. This means that the release rate may slow down more significantly over time for materials with a greater n value, due to the increased effect of swelling and/or erosion on the polymer matrix (Figure 4). It is important to note that the value of n was not the only factor that determined the drug release rate and mechanism. Other factors, such as the chemical composition, structure, and degradation characteristics of the polymeric matrix, can also affect the drug release behavior. The literature supports the notion that a smaller pore size distribution and lower porosity can lead to a slower release rate of drugs, while a larger pore size distribution and higher porosity can lead to a faster release rate of drugs. The specific relationship between pore size, porosity, and drug release rate can vary depending on the specific drug and delivery system, but these general trends have been observed in numerous studies. One study investigated the effect of pore size and porosity on drug release from a polyurethane-based matrix system containing paclitaxel. The results showed that increasing the pore size and porosity of the matrix increased the drug release rate. This was attributed to the increased diffusivity of the drug through the larger pores, and the increased surface area of the matrix due to the higher porosity [41]. Another study evaluated the effect of pore size and porosity on the release of red cabbage’s anthocyans from an alginate cryogel. The study found that increasing the pore size and porosity of the cryogel increased the drug release rate. The authors attributed this to the increased penetration of the release medium into the cryogel and the higher surface area available for bioactive principle diffusion [42]. In a similar study, the effect of pore size and porosity on the release of doxorubicin hydrochloride from an alginate hydrogel was investigated. The study found that increasing the porosity of the hydrogel increased the drug release rate, while increasing the pore size had a minimal effect. The authors attributed the increase in drug release rate to the higher surface area available for drug diffusion in the more porous hydrogels [43]. Corroborating the data from Table 1 and Table 3 with those concerning the release rate of heparin (Figure 4), indeed, its release rate was higher in the case of the Xn–PU–Hep material, which had the highest porosity ($83.11\%$) and pore size (49.39 µm). As expected, the chemical modification of xanthan determined a greater degree of packing of the polymer chains by establishing hydrophobic interactions between the hydrocarbon chains of the oleic acid, which led to a decrease in the porosity and pore sizes of the materials in question. All of this is reflected by the decrease in the release rate of heparin in the environment (e.g., XnOA–Alg–Hep). The biggest influence on the release speed was related mainly to the porosity of materials, with the pore size having a smaller affect on the delivery process. Overall, this study suggests that there is a correlation between drug release from a xanthan/alginate and xanthan/polyurethane matrix, the porosity, and pore dimensions. However, the exact nature of this correlation may depend on the specific drug and matrix system being used. ## 2.4. Antithrombotic Activity Blood–biomaterials interactions are dependent on various pathological/health biological parameters, and also are strongly connected with the surface properties and the end application of the medical devices [44]. Blood contains cells (platelets, red cells, and white cells) and plasma; the liquid phase is abundant in proteins and other small molecules, and the surface of the biomaterial interacts with these components. Blood–surface interactions are very complex and involve biological processes such as protein adsorption, fibrinolysis, complement activation, platelet interactions, blood coagulation, and other cellular reactions [45]. Activated partial thromboplastin time (aPTT) and prothrombin time (PT) are reliable blood tests used to evaluate the behavior of the material. The aPTT values provide information about the effect of tested materials on possible delays in blood coagulation through the intrinsic pathway and prothrombin time (PT) to assess the material-induced changes in the extrinsic pathway of the coagulation cascade [46,47]. The in vitro anticoagulant activity of the prepared materials was evaluated in coagulation assays, such as the aPTT and PT, and other coagulation parameters, as the end-point for heparin-induced antithrombotic activity. The obtained results for some coagulation factors are presented in Table 4. Despite the analyzed materials containing a small amount of heparin, all of them caused significant exchanges of the aPPT and PT parameters (prolonging of the aPTT and PT), and the values exceeded the measurement limit of the instrument, 600 s and 120 s, respectively, indicating an antithrombotic effect. Similar data have been reported by Liu et al. on silk fibroin–polyurethane film containing heparin, as blood compatibility materials [48]. It is generally acknowledged that plasma proteins are firstly adsorbed onto the surface of the material, and can initiate the coagulation cascade. Fibrinogen (Fg) plays a key role in the coagulation cascade, as the protein can bind platelet glycoprotein IIb/IIIa receptor and activated platelets. Low Fg values indicate blood compatibility of the material surface, and the normal biochemical domain in the blood is 200–400 mg/dL. All of the materials with Hep induced a decrease in fibrinogen values. Heparin is an indirect anticoagulant that activates antithrombin via a high-affinity pentasaccharide sequence, and promotes its capacity to inactivate thrombin and coagulation factor Xa. As a result of inactivation, factor Xa showed a reduced ability to bind to fibrinogen, and Hep-induced antithrombotic activity resulted [49]. The values for other proteins, albumin (g/dL), and total proteins (g/dL) were comparable to those of the reference. Generally, the hematocrit (the percentage of red blood cells in blood, the oxygen carrier) and hemoglobin levels were slightly increased in the presence of the tested materials, but the values for these biological parameters remained within their normal domains. Having in mind that the sustained release of heparin from different polymeric matrixes is still in its early stage of development, there are many several issues to be managed in order to reach clinical applications. ## 3.1. Materials Xanthan gum (Xn), with a molar ratio of D-glucose:D-mannose:D-glucuronic:pyruvic acid ketal:O-acetyl of 3.0:3.0:2.0:0.6:1.7, and a molecular weight of approximately 2.5 × 106 Da from CP Kelco, U.S., was used as matrix. Heparin sodium (Hep, >150 IU/mg) was acquired from Sigma-Aldrich and used as received. 4-toluenesulfonyl chloride (TsCl), pyridine (Py), methylene chloride, oleic acid, 4,4′-methylene dicyclohexyl diisocyanate (H12MDI), 4,4′-diphenylmethane diisocyanate (MDI), dimethylol propionic acid (DMPA), polyhexamethylene carbonate diol (PHC–M 2000), 1,4-butanediol (BD), and triethylamine (TEA) were purchased from Sigma-Aldrich (USA). ## 3.2. Synthesis of Xanthan Oleate The esterification of xanthan with oleic acid was performed according to the method presented by Dimofte et al. [ 15]. The esterification of xanthan with oleic acid was performed in the presence of TsCl and Py, in methylene chloride. A round-bottomed flask was used, and varying amounts of TsCl (5.1 g), pyridine (6 mL), oleic acid (8.5 mL), and methylene chloride (50 mL) were mixed together at room temperature using a magnetic stirrer. After 24 h, 10 g of xanthan was introduced to the flask and stirred for an additional 3 h. The resulting product (XaAO) was filtered and sequentially washed with methylene chloride, water, and ethanol, before being dried at room temperature. ## 3.3. Synthesis of Polyurethane The synthesis of polyurethane was carried out following the method presented in reference [12]. Initially, 4,4’-methylene dicyclohexyl diisocyanate (H12MDI—10.48 g) or 4,4′-diphenylmethane diisocyanate (MDI—10 g), and 2.64 g of dimethylol propionic acid (DMPA) were stirred in 30 g of acetone (99.5 wt% purity) as the solvent. Additionally, 2–3 drops of dibutyltin dilaurate (DBTL) were included as a catalyst. The mixture was homogenized under reflux conditions (56 °C, 2 h). In the next step, 28 g of polyhexamethylene carbonate diol (PHC–M 2000) was added and stirred for 30 min. Then, 0.54 g of 1,4-butanediol (BD) was included as a chain extender, and stirring was continued for an additional hour at 56 °C. Finally, the polycarbonate urethane, which contained carboxylic groups, was neutralized using 2 g of triethylamine (TEA, 99 wt% purity) for 30 min. The reaction was completed by slowly adding deionized water (30 g) over approximately 30 min, resulting in an anionic polyurethane water dispersion. ## 3.4. Preparation of Biomaterials Equal amounts of xanthan (Xn) or modified xanthan (XnOA) and polyurethane (PU) or alginate (Alg) were mixed in distilled water at a material:water ratio of 1:100 and heated at 70 °C for 60 min. To this mixture, heparin was added at a matrix:heparin ratio of 1:0.25. The codes of the materials obtained by freeze–thawing cycles, followed by lyophilization, are as follows: Xn–Alg–Hep; XnAO–Alg–Hep; Xn–PU–Hep; XnAO–PU–Hep. ## 3.5. FTIR (Fourier Transform Infrared Spectroscopy) Analysis The FTIR spectra of the materials were recorded using a Vertex 70 FTIR (Brüker, Karlsruhe, Germany) that was equipped with an ATR device (ZnSe crystal) with a 45-degree angle of incidence. The spectra were analyzed in the ranges of 4000–400 cm−1 and 4500–600 cm−1. For the measurements, an average of 64 scans and a spectral resolution of 2 cm−1 were used. ## 3.6. Scanning Electron Microscopy (SEM) SEM images were obtained at a magnification of 200× using a VEGA TESCAN microscope (Tescan, Kohoutovice, Czech Republic), with an acceleration voltage of 20 kV, at room temperature, with a low-vacuum secondary electron detector. ## 3.7. Determination of Materials’ Porosities The density of the studied materials (ρpb) was calculated using Equation [3]:[3]ρpb=WiV=WiL×l×h, g/cm3 where Wi (g) represents the dry weight of the sample, V (cm3) is the volume of the studied material (equal with the product of length, L (cm), width, l (cm) and height, h (cm) of the sample). The porosities of the studied materials were determined using the saturation method described by Long et al. [ 50]. Ethanol was used as the wetting fluid. Material samples with weights between 0.0100 and 0.182 g were immersed in ethanol. After 24 h, the samples were withdrawn, and the excess ethanol was removed using filter paper. All of the samples were re-weighed, and their porosities were calculated according to Equation [4]:[4]Porosity=Wf−WiρEtOH×V×100, % where *Wf is* the weight of the sample after immersion in ethanol, and ρEtOH represents the density of ethanol. ## 3.8. Mechanical Tests Ethanol-swollen samples, as plates of about 8–10 mm thickness, 10–12 mm width, and 5–7 mm height, were tested using a Shimadzu Testing Machine (EZ-LX/EZ-SX Series, Kyoto, Japan). An initial force of 0.1 N was applied before performing each measurement. The cross-head speed was 1 mm × min−1, while the applied force was fixed at 20 N. The compressive stresses (σ, kPa), strains (ε), and elastic moduli (G, kPa) were evaluated at room temperature following the procedure previously published in [51,52]. ## 3.9. In Vitro Drug Release An amount equivalent to 25 mg of heparin from each formulation was incubated at 37 °C in 25 mL of phosphate buffer solution (PBS, pH = 7). Aliquots of 4 mL were taken at 30 min intervals for a total duration of 240 min, and the absorbance intensities at 260 nm were measured using a Jenway 6405 spectrophotometer (Jenway Ltd., Dunmow, UK). The concentrations of the released drugs were evaluated based on the calibration curve of heparin. In order not to change the hydrodynamic profile, after each sampling, the release medium was supplemented with 4 mL of fresh PBS solution. The calibration curve for heparin was plotted using the absorbances of the standard solutions containing different concentrations of heparin in PBS (0.05, 0.1, 0.2, 0.5, and 1 mg/mL) at 260 nm. The experiments were performed in triplicate, and the standard deviations (SDs) were computed. ## 3.10. Blood Coagulation The measurements of the activated partial thromboplastin time (aPTT), the prothrombin time (PT), and fibrinogen were carried out according to the routine procedure [53]. In brief, PT, aPTT, and fibrinogen were measured on integral blood with anticoagulant (aqueous sodium citrate $3.8\%$ w/v; ratio $\frac{1}{9}$ v/v). The materials were incubated with 5 mL of blood at room temperature, for 30 min, and then were separated by centrifugation (2500 rpm, 10 min). The biochemical parameters in blood plasma were determined using a semi-automatic Helena coagulometer with 2 channels, photo-optical technique coagulation systems and a PT-Fibrinogen kit (International Sensitivity Index (ISI) = 1.07). The control sample was considered the free integral blood. ## 4. Conclusions Materials containing heparin with controlled release were obtained using xanthan/modified xanthan, polyurethane, and alginate as matrices. The mechanical properties of the Hep-containing formulations were found to depend on the composition of the matrix. All of the samples exhibited impressive elastic behavior and toughness without any crack development within the network, making them suitable for tissue engineering. The Xn–Alg–Hep formulations showed a modulus of elasticity of 36.71 kPa and a compressive strength of 49.94 kPa at $77.34\%$ strain, while the Xn–PU–Hep formulations displayed a modulus of elasticity of only 2.48 kPa and a compressive strength of 34.37 kPa at $80.44\%$ strain, indicating a robust network with high toughness for the former formulations. The use of XnOA in the preparation of Hep-loaded formulations led to more rigid networks. Additionally, the dense pore walls provided great structural support to the entire interconnected porous network, resulting in high elasticity, flexibility, and non-brittleness in comparison with the Xn-based formulations. The release of heparin in Xn–Alg–Hep, XnOA–Alg–Hep, and XnOA–PU–Hep exhibited non-Fickian transport (n values between 0.43 and 0.85), due to the combined effect of diffusion and polymer swelling. The use of XnOA as a component of the polymeric matrix led to a slower release process of Hep (release rate between 0.5–0.7) compared to the matrix containing chemically unmodified xanthan (2.6–2.9). Porosity was the most significant factor that affected the release speed, with a considerable statistical difference in the release rate of heparin from the tested materials. The critical Fisher coefficient (0.0393) was much lower than the theoretical value (322.57). The analysis of the variation coefficients showed that the difference in pore size between the tested materials had a relatively small impact on the drug release speed (with a negative coefficient value of −0.1776). In coagulation assays, such as the aPTT and PT, and other coagulation parameters, the in vitro anticoagulant activities of the prepared materials were evaluated as the endpoint for heparin-induced antithrombotic activity. All Hep-containing materials prolonged the aPTT and PT, proving their antithrombotic effects. 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--- title: 'Patient Characteristics in the Recording Courses of Vascular Diseases (Reccord) Registry: Comparison with the Voyager Pad Endovascular Cohort' authors: - Michael Czihal - Nasser Malyar - Jürgen Stausberg - Ulrich Hoffmann journal: Journal of Cardiovascular Development and Disease year: 2023 pmcid: PMC10054422 doi: 10.3390/jcdd10030115 license: CC BY 4.0 --- # Patient Characteristics in the Recording Courses of Vascular Diseases (Reccord) Registry: Comparison with the Voyager Pad Endovascular Cohort ## Abstract Background: To compare the characteristics of a “real world” population included in a prospective registry to patients enrolled in a randomized, controlled trial (RCT) after endovascular revascularization (EVR) for symptomatic peripheral artery disease (PAD). Methods: The RECcording COurses of vasculaR Diseases (RECCORD) registry is an observational registry prospectively recruiting patients undergoing EVR for symptomatic PAD in Germany. VOYAGER PAD was an RCT which demonstrated the superiority of rivaroxaban and aspirin versus aspirin to reduce major cardiac and ischemic limb events following infrainguinal revascularization for symptomatic PAD. For this exploratory analysis, the clinical characteristics of 2.498 patients enrolled in RECCORD and of 4.293 patients from VOYAGER PAD who underwent EVR were compared. Results: The rate of patients aged ≥ 75 years was considerably higher in the registry (37.7 vs. $22.5\%$). More patients in the registry had undergone previous EVR (50.7 vs. $38.7\%$) or suffered from critical limb threatening ischemia (24.3 vs. $19.5\%$). Registry patients were more commonly active smokers (51.8 vs. $33.6\%$), but less frequently suffered from diabetes mellitus (36.4 vs. $44.7\%$). While statins (70.5 vs. $81.7\%$) were less frequently used, antiproliferative catheter technologies (45.6 vs. $31.4\%$) and postinterventional dual antiplatelet therapy (64.5 vs. $53.6\%$) were more commonly applied in the registry. Conclusions: There were many similarities but some clinically meaningful differences in clinical characteristics between PAD patients who underwent EVR and were included in a nationwide registry and PAD patients from the VOYAGER PAD trial. ## 1. Introduction Lower extremity peripheral arterial disease (PAD) affects approximately 50 million inhabitants in Europe [1]. PAD patients are at high risk for developing myocardial infarction, stroke, lower extremity ischemic events and cardiovascular death. Endovascular revascularization (EVR) procedures of the lower extremity arteries are increasingly used for the treatment of PAD, aiming at improving the quality of life in symptomatic patients and saving limbs in patients suffering from critical limb threatening ischemia (CLTI) [2]. Despite substantial advances in medical treatment over the past decades, the cardiovascular risk of PAD patients after having undergone EVR remains high, and the risk of acute ischemic limb events is substantially increased [3]. Unfortunately, until recently there has been an eminent lack of evidence on the efficacy and safety of antithrombotic treatment after EVR in PAD, making treatment decisions subject to individual physicians’ judgements based on patients’ and procedure characteristics [4]. The recently published VOYAGER PAD trial led to a paradigm change in antithrombotic treatment after revascularization of PAD, as it demonstrated a net clinical benefit of a dual antithrombotic regimen (ASA and low dose Rivaroxaban) over ASA and placebo [5]. It is of great clinical importance to identify factors potentially interfering with the translation of these pivotal trial results into broad daily clinical practice. Therefore, this study aimed to compare the clinical characteristics of patients prospectively recruited into a large prospective German EVR registry (RECording COurses of vasculaR Diseases, RECCORD [6]) with those of the patients included in VOYAGER PAD. ## 2. Materials and Methods The RECcording COurses of vasculaR Diseases (RECCORD) registry was established by the German Society of Angiology—Society for Vascular Medicine in order to address the lack of contemporary real-world data regarding the current practice of medical and interventional care in vascular patients (list of RECCORD Registry Collaborators in the Appendix A). The RECCORD study protocol was approved by the Ethics Committee of the Ludwig-Maximilians-University, Munich, Germany. The study protocol, the clinical characteristics of the first 1.000 patients and the current practice of EVR in different anatomic regions of the lower limbs have been published previously [6,7,8]. Having provided written informed consent, all patients with symptomatic lower extremity PAD (lesions located from the aorto-iliac bifurcation to the distal crural arteries) undergoing EVR can be included, whereas there are no dedicated exclusion criteria. RECCORD collects data regarding the diagnosis of PAD (based on ICD-10-codes) and of the endovascular procedures (based on OPS-codes) together with 84 items regarding anthropometry, medical history including previous revascularization, cardiovascular comorbidities and risk profile, medication, PAD symptoms including walking distance, hemodynamic situation (ankle brachial index, ABI), and quality of life. VOYAGER PAD was a randomized, controlled, double-blind trial which compared the combination therapy of ASA + low dose Rivaroxaban compared to ASA + placebo after infrainguinal revascularization for PAD [5]. The study design, including in- and exclusion criteria and the principle outcomes of the VOYAGER PAD, have been published elsewhere [9]. Briefly, patients aged ≥ 50 years with moderate to severe, symptomatic lower extremity PAD were eligible for randomization after successful arterial revascularization (either endovascular or surgical) below the inguinal ligament. PAD-related exclusion criteria included asymptomatic or only mildly symptomatic PAD, prior revascularization of the index leg within 10 day of the qualifying revascularization, acute limb ischemia, and major tissue loss. VOYAGER PAD revealed a significantly lower incidence of the composite primary outcome of acute limb ischemia, major amputation for vascular causes, myocardial infarction, ischemic stroke, or death from cardiovascular causes in the combined treatment group compared to patients treated with aspirin alone. For the current analysis, 2.498 subjects enrolled in RECCORD between February 2019 and September 2020 and 4.293 patients from the VOYAGER PAD cohort who had undergone EVR (including hybrid procedures) and were recruited between August 2015 and January 2018 were compared. Aggregate data of the VOYAGER PAD endovascular cohort, including demographic information, clinical and procedural characteristics as well as cardiovascular medication, were provided by the VOYAGER PAD steering committee. Based on these aggregate data of the RCT, matching variables of the RECCORD database were exported. If necessary, the categorization of nominal and ordinal variables of the RECCORD cohort was modified for proper comparison with the aggregated RCT data. Analysed parameters included PAD severity (claudication vs. critical limb ischemia), the type of endovascular procedure, the history of prior lower limb revascularization (either endovascular or surgical) or amputation, a cardiovascular risk profile including severe chronic renal insufficiency (defined as eGFR < 30 mL/min/1.73 m2), cardiovascular comorbidities including coronary artery disease (CAD) and cerebrovascular disease (CVD), ABI of the index leg prior to EVR, and cardiovascular medication (single or dual antiplatelet treatment, statin treatment, ACE inhibitors/AT1-antagonists and ß-Blockers). The definition of CLTI in the RECCORD-cohort was based on ICD-10-coding (I70.23, I70.24, I70.25), whereas in VOYAGER PAD a diagnosis of CLTI was assigned to patients with PAD fulfilling established clinical (rest pain, ulcers, gangrene) and hemodynamic criteria (ankle pressure ≤ 50 mmHg and rest pain; ankle pressure ≤ 70 mmHg and tissue loss) [10]. CVD was characterized as a composite of prior stroke, history of carotid revascularization or carotid artery stenosis > $50\%$ in VOYAGER PAD, but was not further specified in RECCORD. For all comparisons regarding cardiovascular medication we used VOYAGER PAD baseline data (representing any medication started 30 days before and after randomization). For the comparison of the rates of antihypertensive and statin treatment, we used RECCORD baseline data (obtained prior EVR). For the comparison of the rates of dual antiplatelet treatment we relied on the documented drug information covering the time period between the RECCORD baseline visit (prior EVR) and a maximum of 14 days following the index intervention. Due to limited items in the RECCORD database, we were not able to provide exact data on the type of single antiplatelet therapy (ASA vs. clopidogrel). As the analysis relied on aggregate data, we performed exploratory analyses of differences between both cohorts, without testing for statistical significance. Continuous data are presented as mean ± standard deviation. Categorical data are given as absolute numbers (percentages). ## 3. Results The comparison between both cohorts is outlined in Table 1. Females represented $34.1\%$ of patients in the registry and $28.8\%$ of patients in the trial (male to female ratio 1.93 in the registry; 2.47 in the RCT). The mean patient’s age was somewhat higher in registry patients (70.3 ± 10.4 years) compared to the RCT patients (67.6 ± 8.6 years). Correspondingly, the rate of patients aged ≥ 75 years was considerably higher in the registry ($37.7\%$ vs. $22.5\%$). The proportions of White, Black/ African American and Asian ethnicities were $76.3\%$, $3.2\%$, and $18.5\%$ in the RCT. RECCORD did not collect data on the distribution of ethnic groups. More than half of the registry patients ($50.7\%$) had previously undergone any limb revascularization (previous EVR in $47.2\%$, previous bypass surgery in $12.9\%$). In the RCT, the respective rates for any previous revascularization, previous EVR and previous bypass surgery were somewhat lower ($38.7\%$, $35.2\%$, $6.6\%$). By contrast, the rate of any prior amputation was lower in the registry (4.0 vs. $6.0\%$). Almost every fourth of the registry patients ($24.3\%$) suffered from CLTI, compared to nearly every fifth patient in the RCT ($19.5\%$). However, the mean ABI of the index leg was higher in the registry (0.65 ± 0.3) than in the RCT (0.57 ± 0.18). Due to differences in categorization, lesion lengths (registry: <10 cm, 10–20 cm, RCT: < 5 cm, 5–14.9 cm, >15 cm) were not directly comparable between the cohorts. Antiproliferative technologies (drug coating balloons, drug eluting stents) were applied in 1.138 registry patients ($45.6\%$) and in 1.330 RCT patients ($31.4\%$). More precise information regarding the lesion location and type of procedure was available for the registry cohort but not for the RCT dataset, and therefore comparisons were not feasible. Although the mean weight and mean BMI were very similar between both groups, there was a higher rate of diabetes mellitus in the RCT ($44.7\%$) compared to the registry ($36.4\%$). Conversely, many more patients in the registry than in the RCT were active smokers (51.8 vs. $33.6\%$). We further observed a higher percentage of patients with severely impaired kidney function in the registry ($3.0\%$) than in the RCT ($0.8\%$). Otherwise, there were no remarkable differences regarding the presence of classic cardiovascular risk factors. While the reported rate of CAD and a history of heart failure were similar in both cohorts, the reported frequency of CVD was lower in the registry ($15.9\%$) compared to the RCT ($32.8\%$). Dual antiplatelet treatment was commenced in 2.259 RCT patients ($53.6\%$), compared to roughly two thirds of registry patients ($$n = 1$.611$, $64.5\%$). Comparisons regarding cardiovascular medication are given in Table 2. Statins as well as ACE-inhibitors/ARB-antagonists were less commonly taken by registry patients ($70.5\%$ and $58.1\%$) than by RCT patients ($81.7\%$ and $65.4\%$). ## 4. Discussion This exploratory analysis elucidated many similarities but some important differences in clinical characteristics between PAD patients who underwent EVR within routine care and were included in a nationwide registry, and patients randomized to EVR in the VOYAGER PAD trial. The most important differences included a considerably higher rate of patients aged ≥ 75 years (registry $37.7\%$ vs. RCT $22.5\%$), and of patients with a history of previous revascularization procedures (approaching $50\%$ in patients treated during routine clinical practice) in the registry cohort. Moreover, the proportion of CLTI patients and of patients with advanced chronic kidney disease was somewhat higher in the registry compared to the RCT. The rate of major adverse limb events (MALE, defined as composite of acute limb ischemia, amputation and unplanned index limb revascularization) in the VOYAGER PAD endovascular cohort was estimated to be as high as $30\%$ after 3.5 years, with $23.5\%$ represented by unplanned index limb revascularization [11]. Recently published health claims-based data underscored a substantial risk of MALE after EVR, with a rate of hospitalization for MALE of $12.9\%$ in 400.000 patients who underwent EVR of PAD in the US (median follow-up: 2.7 years) [3]. CLTI and advanced age, both somewhat more common in the registry compared to the RCT, have been shown to be negatively associated with extremity outcomes (e.g., amputation free survival) in PAD cohorts [12,13,14,15]. The same is true for advanced chronic kidney disease, which was three times more common in the registry, although absolute numbers were low [14,16]. Repeat EVR after previous revascularization procedures may also be associated with worse outcomes [17,18]. In the RECCORD registry, almost every second patient had previously undergone an endovascular procedure. Thus, the cohort comparison of RECCORD and the RCT indicates an ischemic risk profile which could be worse in patients treated within routine clinical practice, underlining the need for effective treatment strategies in order to avoid repeated ischemic events and/or target lesion revascularization. Results of a comparison of the Danish Vascular Registry and the overall cohort of the VOYAGER PAD trial (including surgically revascularized patients) point in the same direction, with higher mean age and substantially higher rates of critical limb ischemia and current smoking in the registry but a lower percentage of patients under statin treatment [19]. It is of interest in this context that the rate of patients under guideline-recommended pharmacotherapy was lower in the RECCORD registry (e.g., statin therapy $70\%$) compared to the RCT (e.g., statin therapy $80\%$), but higher than in contemporary analyses of routine ambulatory care (e.g., statin therapy in $50\%$ of patients in a health claims based study by Rammos et al.) [ 20]. Drug eluting technologies (balloon catheters, stents) were applied more frequently in registry patients, compared to the RCT. This difference probably reflects the international variation of endovascular practice, which may be influenced by reimbursement issues. Furthermore, study periods were different (the registry started shortly after recruitment for the RCT had been completed) and endovascular practice in both study populations with regard to the use of drug eluting technologies may have been influenced by a much-acclaimed publication from 2018, suggesting an increased mortality risk with paclitaxel-based devices [21], and several subsequent studies which contradicted this study’s findings [11,22,23]. It is common clinical practice to prolong dual antiplatelet therapy after the application of drug coated devices [24], and in the registry two out of three patients were put on dual antiplatelet therapy after EVR. However, due to a lack of scientific evidence on the clinical benefit of dual antiplatelet therapy after EVR, and considering the results of VOYAGER PAD, dual antithrombotic therapy rather than dual antiplatelet treatment is favored after infrainguinal EVR by current European expert recommendations [25]. In VOYAGER PAD there was an increased risk for bleeding events under dual antithrombotic treatment (low dose rivaroxaban and aspirin) compared to aspirin monotherapy, but no excess of intracranial and fatal bleeding [5]. Short term clopidogrel did not further increase the bleeding risk [26], but the impact of patient’s characteristics on bleeding complications has not been analysed in detail so far. It is well known, however, that the risk factors of ischemic events which we found more commonly in the RECCORD registry (advanced age and CLTI) are also important risk factors for bleeding events under single or dual antiplatelet therapy [27,28]. Both factors were recently confirmed as independent predictors of bleeding complications in a health claims data-based analysis of patients who were hospitalized for symptomatic PAD [29]. Given these data, the cohort comparison of RECCORD and the RCT also indicates a bleeding risk profile which could be rather worse in patients treated within routine clinical practice. Patient registries are promoted to close the efficacy–effectiveness gap between evidence from RCTs and outcomes that could be achieved in daily health care [30]. The need to control most of the confounders typically leads to a homogeneous cohort of patients with lower risks in RCTs. The comparison between both cohorts highlights this situation with lower frequencies of some—but not all—relevant risk factors in the VOYAGER PAD trial. Furthermore, protocol-based procedures of an RCT result in an optimized therapy, as indicated here by the more frequent guideline-recommended pharmacotherapy in the VOYAGER PAD trial. In view of the higher rate of female patients in RECCORD, the comparison also underpins the observation that women are underrepresented in the enrolment of RCTs [31]. Registry-based RCTs might be an option to combine the advantages of both designs and to better control for the efficacy–effectiveness gap [32]. The main limitation of this study is that it is an exploratory analysis based on aggregate and not on single patient data. Patients in the RCT may have been characterized more deeply, which, for example, could explain the higher rate of diabetes mellitus in the RCT. Due to differences in categorizations, we were not able to compare some variables such as ethnic origin, exact data on the drugs used for single antiplatelet therapy, and lesion lengths of the target lesions. Given the lack of information on the ethnic descent of patients in RECCORD, a comparison with the subgroup of German patients who received endovascular treatment within the RCT might be of interest. However, data on the German subgroups of the VOAYAGER PAD are not yet available. Different definitions of CLTI and CVD may have affected the observed frequency of these conditions in the two cohorts, and the different timings of medication recording could have impacted the observed rates of medical treatments, such as dual antiplatelet and statin therapy. Finally, in contrast to the RCT the registry also included patients with iliac artery involvement. Nevertheless, our study has implications for clinical practice. We observed no serious differences in demographic characteristics, cardiovascular disease/risk profiles and treatment that could prohibit the extrapolation of the RCT results on the registry. Noteworthy was a higher rate of elderly patients and of patients with CLTI and/or a history of previous revascularization in the registry indicating worse risk profiles for both ischemic as well as bleeding events in routine clinical practice. 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--- title: 'Vascular Responses following Light Therapy: A Pilot Study with Healthy Volunteers' authors: - Adam Saloň - Bianca Steuber - Ruslan Neshev - Karin Schmid-Zalaudek - Patrick De Boever - Eva Bergmann - Rainer Picha - Per Morten Fredriksen - Benedicta Ngwechi Nkeh-Chungag - Nandu Goswami journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054429 doi: 10.3390/jcm12062229 license: CC BY 4.0 --- # Vascular Responses following Light Therapy: A Pilot Study with Healthy Volunteers ## Abstract [1] Background: Studies have reported the effectiveness of light therapy in various medical conditions. Our pilot study aimed to assess the effect of Maharishi light therapy (MLT) on physiological parameters, such as the heart rate (HR), HR variability (HRV), blood pressure (BP), BP variability (BPV), and the retinal microvasculature of healthy participants; [2] Methodology: Thirty (14 males and 16 females) healthy, non-smoking participants between 23 and 71 years old (46 ± 18 years) were included in this randomized crossover study. Each participant was tested with a placebo (using LED light) and gem lights, 24 h apart. Hemodynamic parameters were recorded during the session, and 24 h heart rate and BP levels were assessed via mobile devices. Retinal vascular responses were captured with fundus images and the subsequent analysis of retinal vessel widths. A linear model, using repeated measures ANOVA, was used to compare the responses across the sexes and to assess the effect of the MLT; [3] Results: Changes in the central retinal artery equivalent (CRAE) ($p \leq 0.001$) and central retinal vein equivalent (CRVE) ($$p \leq 0.002$$) parameters were observed. CRAE and CRVE decreased under MLT and increased under the placebo condition from before to after. However, the baseline values of the participants already differed significantly before the application of any therapy, and the variation in the retinal vessel diameters was already large in the baseline measurements. This suggests that the observed effect results may only reflect naturally occurring fluctuations in the microcirculation and not the effect of MLT. Furthermore, no significant effects were observed in any other investigated parameters; [4] Conclusion: Our study with healthy participants finds significant changes in retinal parameters, but the biological variation in the baseline measurements was large to begin with. This suggests that the observed effect results only reflect naturally occurring fluctuations in the microcirculation and not the effect of MLT. However, in the future, larger studies in which MLT is applied for longer periods and/or in patients with different diseases could discover the physiological impacts of this type of therapy. ## 1. Introduction The disturbance of cardiovascular physiological processes is the foundation of cardiovascular morbidity and mortality. There are many risk factors, including high blood pressure, high blood cholesterol, smoking, diabetes, and others, that contribute to the development of cardiovascular disease (CVD). Aging reduces the elasticity of arteries, which decreases the flow of blood and oxygen, and can result in a permanently high blood pressure [1]. High cholesterol intake increases the level of LDL cholesterol and contributes to atherosclerosis development, resulting in narrowed arteries and hypertension [2]. Moreover, smoking increases cholesterol, LDL, and triglycerides, but decreases HDL [3]. The status of diabetes increases the level of oxygen radicals and reduces the level and bioavailability of NO, which decreases the elasticity and narrowing of blood vessels [4]. Yoga and meditation practices are considered to be non-invasive approaches to improving cardiovascular health [5,6]. These types of Vedic techniques also include light therapy. However, evidence and claims about the effect of light therapy are limited and insufficient [7,8,9]. It is suggested that light treatments produce biological effects in molecules, living cells and tissues [10,11,12,13,14,15]. One of the most common health issues treated by phototherapy is wound healing. Red light is typically used for wound healing due to its increased penetration through tissue and its lower absorption by hemoglobin and melanin [10]. The irradiation of human fibroblasts with red light (λ = 628 nm) leads to an increase in DNA and RNA synthesis with gene expression upregulation, with most of them playing a role in increasing cell proliferation and suppressing apoptosis [11]. Other proteins whose activity can be affected by phototherapy include superoxide dismutase (max in 644 nm), glucose oxidase (464 nm), cholesterol esterase and cholesterol oxidase, and lipase (400 nm) [12,13]. The effectiveness of therapy that uses wavelengths in the visible region has been shown for various medical conditions, such as dengue fever, insomnia, diabetes, psychiatric illnesses, hypertension, seasonal affective disorder (SAD), immunity, hyperacidity, cutaneous wound healing, chronic joint diseases and inflammation [12,14,15,16,17,18,19]. Thrombocytopenia is a typical symptom in patients with dengue fever. Chromotherapy by red-colored radiation (644 nm) has been shown to inhibit platelet degradation [15]. Furthermore, the limited options for treating insomnia during pregnancy has led to the application of chromotherapy. It has been shown that the color turquoise (495 nm) improves sleep, and decreases fatigue and drowsiness during pregnancy [16]. In turn, a light therapy with green, yellow or orange light can be helpful in controlling diabetes [19]. Bright Light Therapy has been proven to be an adequate countermeasure for SAD and other mental health disorders [18]. A detailed discussion of the different methods is summarized in a paper by Azeemi and coworkers [17]. Despite the presentation of different studies focused on light therapy, most of them struggle with problems regarding the sample size and heterogeneity, so further research is needed [8]. Maharishi light therapy uses Vedic technology, which was first applied more than 30 years ago by Joachim Roller, an apprentice of Maharishi Mahesh Yogi [20,21]. Following Maharishi’s guidance, a jewelry designer, Joachim Roller, developed gem beamers. Since 2007, the gem beamer technology has been used around the world. Maharishi light therapy (MLT) focuses on light passing through gems (such as diamonds, emeralds, and rubies) and it is applied to specific areas of the body. People report that the therapy is enjoyable, deeply relaxing, and refreshing for their mind and body [20,21]. To date, however, only a limited number of articles have evaluated the impact of light therapy on physiology, and none have focused on Maharishi light therapy. The lack of knowledge about Maharishi light therapy is evident and, as Travis et al. noted, “an assessment of the impact of light therapy on the physiology of the human body is necessary” [22]. This pilot study investigated the effects of MLT on physiological parameters within a triple-blinded randomized, crossover study. We assessed hemodynamic parameters, heart rate variability (HRV), blood pressure variability (BPV), and microvascular responses in healthy participants. ## 2. Materials and Methods The investigations of this study were performed at the Medical University of Graz, Austria. The study was submitted to and approved by the Ethics Committee of the Medical University of Graz, Austria (EK: 30-515 ex $\frac{17}{18}$). Data collection was performed in accordance with good clinical practices and following the WMA Declaration of Helsinki [2013]. Every participant received detailed information about the study protocol and provided written consent. ## 2.1. Participants In total, 30 (14 males and 16 females) healthy, non-smoking participants were enrolled in this study. They were between 23 and 71 years of age (46 ± 18 years), of 160–185 cm in height (170.9 ± 7.8 cm), and 51–130 kg in weight (71.0 ± 18.7 kg) (Table 1). The exclusion criteria were individuals who smoked, consumed alcohol on a regular basis, had psychological problems, had heart disease, were on medications that influence cardiac parameters (e.g., beta blockers), or were pregnant. ## 2.2. Study Design This was a triple-blind, randomized, crossover study. Neither the administrator of the light therapy nor the participant receiving the treatment knew about the order of the MLT vs placebo intervention. The measurements took two days (48 h, 24 h per study condition). Participants were randomly assigned to two appointments within two successive days. The participants who received MLT on the first day crossed over to the second intervention (placebo) on the second day and vice versa. All measurements were obtained within two days (48 h). The placebo intervention was nonrecognizable from MLT with real gems. The study was conducted to investigate the effect of MLT on the physiological parameters and microvasculature. Data analysis was performed offline by a person (R.N.) who had no knowledge of the treatments/condition (MLT or placebo) on a given day. Randomization was performed by using a free, demo version of online software https://www.randomizer.at (accessed on 1 April 2019). ## 2.3. Light Therapy Application Device Gems that emitted different colors of light were used. A device comparable to the one that administered the MLT was also made, but only LED lights of similar colors to the ones used in the MLT were used. It was not possible to differentiate the gems- vs the placebo light-administering device. ## 2.3.1. Light Therapy Pens The MLT pens were around 1.5 cm in diameter and 15 cm long, powered by a battery. The light passed through 13 different gems: amber, amethyst, blue sapphire, carnelian, cat’s eye, coral, diamond, emerald, green tourmaline, pearl, ruby, yellow sapphire, and zircon. The light was projected through the gems to the core of the body (abdomen, chest). The incident lights were focused in circles, whose size indicated how far the pens were placed from the participant’s body. ## 2.3.2. Placebo Light Pens The placebo light pens were of the same shape, color, and material as the authentic light therapy pens. They projected light through colored glass instead of gems. The light was similar in color and diameter to that in the light therapy pens, and the real application device and placebo version could not be distinguished from each other. ## 2.4. Light Therapy Protocol As mentioned in the study design, the participants were given two appointments, one for the MLT with real gems and one for the placebo intervention. Each intervention was 24 h apart and each participant was investigated under both conditions, using MLT and placebo light therapy, in a randomized crossover design. The MLT light therapy was performed by an experienced practitioner (E.B.), who had no knowledge of who received which intervention (MLT or placebo) on a given day. After the participant arrived, they received detailed information about the study protocol and provided written consent. The protocol began with the retinal imaging (5 min). Thereafter, electrodes were placed on the participant’s body, and with lying them in a supine position, the 10 min baseline values of the hemodynamic parameters (TFM, Task Force Monitor) were recorded. The protocol continued with an interview with the practitioner of the study (20 min) (information not included in manuscript). Following, the participants were exposed to either MLT or placebo light intervention, using the same apparatus; however, instead of gem beams, LED beams with the same light colors were used (20 min). The administration of the two conditions was randomized and blinded, and both conditions (–MLT/placebo light) were administered on successive days. Physiological measurements using TFM (epochs T1–T25) were collected during the whole intervention, as well as during recovery in the supine position (5 min). After recovery, BP and HRV devices for continual 24 h measurements were placed on the participant (10 min). The devices measured the BP and HR of the participants over the following 24 h until the participant underwent the alternating intervention. These measurements enabled the evaluation of a potentially longer light therapy impact. Before the participant left, the second retinal imaging procedure was performed (5 min). Participants returned the next day (after 24 h) to receive the other condition/intervention. The procedure for the light therapy protocol is described in Figure 1. ## 2.5. Physiological Measurements All measurements were collected using a Task Force Monitor® (TFM, CNSystems, Graz, Austria). BP (upper arm oscillometry and finger plethysmography), HR (3-lead ECG) and thoracic impedance were measured for the purposes of hemodynamic monitoring. For detail of the electrode’s placement, see Trozic et al., [ 2020] [23]. The collected physiological data were analyzed by calculating the means of 30 s epochs. The last 30 s of the baseline were taken as a reference (epoch T0), and then analogous with the light intervention, which lasted between 13 and 30 min. In order to remain consistent, the first 25 epochs of the MLT/placebo were taken: T1-T25. Only means with more than $85\%$ valid values (more than 25 s) were taken, and the rest were set to missing values in order to reduce the bias that could have arisen in any of the analyses [24]. The means and the plots of the epochs were generated using MATLAB R2018a (Version 9.4.0, The MathWorks Inc., Portola Valley, CA, USA). The totals of the 26 epochs were then analyzed using SPSS (Version 26.0, SPSS Inc., Armonk, NY, USA). ## 2.6. Heart Rate Variability and Blood Pressure Variability Measurements A portable ECG-measurement device (eMotion Faros, Biosign, Ottenhofen, Germany) was used to record the participants’ ECG over the course of 24 h after each intervention (MLT or placebo). These data were then applied to a long-term (24 h) HRV analysis. A similar dataset with the participants’ BP measurements (TM-2430, A&D) over the 24 h after each intervention was also acquired and analyzed. The HRV data were analyzed by removing any large motion artifacts with the help of the Symlets 4 (sym4) wavelet transformation. Then, the Pan-Tompkins algorithm was used to detect the R-peaks in the 24 h ECG signal and build the normal-to-normal intervals (NN intervals) of the participants [25]. The NN intervals were analyzed with statistical time domain methods—e.g., SDNN (standard deviation of all NN intervals), SDSD (standard deviation of differences between adjacent NN intervals), etc. [ 25]. The parameters that were analyzed are all in the time domain as the frequency domain parameters and are more prone to errors due to artifacts. Furthermore, the time domain parameters correlate directly to frequency domain parameters and therefore can be used as a measure for those [25]. The 24 h BPV data were partly analyzed externally. The University of Minnesota provided the sphygmochron data, which contain the MESOR; this is an adjusted 24 h mean, which was obtained by fitting a cosine model to the original data [26]. ## 2.7. Retinal Measurements The retinal images (resolution of 1536 × 1536) of the right eye were obtained from each of the participants before and after each intervention, as indicated in the protocol. To capture the optic disc-focused retinal images, a non-mydriatic digital retinal camera, the Canon CR-2 (Canon Medical Systems Europe B.V., Zoetermeer, The Netherlands), was used. Retinal images were arranged, organized, and prepared for analysis. A trained operator, without any previous knowledge about the details of the study, used the semi-automated MONA REVA software (VITO, Mol, Belgium; [27]) to analyze the retinal images. The software automatically processed the retinal images and analyzed the diameters of retinal microvessels in areas 0.5 to 1 of the optic disc radius from the optic disc margin. Post-processing, including double thresholding, blob extraction, the removal of small connected regions, and filling holes, was performed. Subsequently, the vessels (arterioles, venules) were checked, corrected, and labeled by the grader. The Parr–Hubbard–Knudtson formula, which uses the 6 largest retinal arterioles and the 6 largest retinal venules, was used to calculate three retinal parameters: central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), and artery-to-vein ratio (AVR) [28]. ## 2.8. Statistical Analysis The physiological parameters obtained during the study were first analyzed by the Shapiro–Wilk normality test to check the distribution of the data. Afterward, repeated measures one-way and two-way ANOVA, and analyses of the effects of the different covariates on the linear model, were used. The repeated measures ANOVA was performed for all the participants pooled together and once additionally for sex as a between-subject factor. Three covariates were additionally considered for the analysis: age, weight, and height. Any between-subject factors and covariates that were found not to be statistically significant were removed from the further analysis. All statistical tests were performed with the proper assumptions checks (e.g., Shapiro–Wilk test for normality), and any inconsistencies were removed. The data are presented as means ± standard deviation. The data from the 24 h HRV and BPV measurements were checked for normal distribution with the Shapiro–Wilk test. The HRV parameters were non-normally distributed and were, therefore, analyzed using the non-parametric Wilcoxon test. The data are presented as means ± standard deviation. Because the BP variability parameters were normally distributed, the standard arithmetic means to perform t-tests were used. The data are presented as means ± standard deviation. The normal distribution of retinal parameters was also analyzed using the Shapiro–Wilk test, and a repeated measures ANOVA was applied to analyze the data; this included before and after, and the MLT or placebo as the repeated measures factor, testing all participants, triple-blinded, under both conditions in a randomized design. To evaluate specific effects, respective post hoc tests were performed, correcting the alpha level according to Bonferroni. ## 3. Results Thirty participants were recruited for this crossover study. Five participants were excluded from the retinal imaging analysis due to the very low quality of the retinal images obtained from them. Table 1 summarizes the basic characteristics of the study participants. ## 3.1. Physiological Parameters Obtained with the Task Force Monitor None of covariates age, weight, and height, showed an effect on the linear model. Thus, the parameters were excluded from the analysis. The cardiovascular parameters were assessed at six different time points (T0–T5, see Supplementary Table S1). Of all the hemodynamic parameters examined, only one significant effect was found for HR ($$p \leq 0.044$$), indicating a lower HR (mean ± SD) under the placebo condition than under the MLT condition (mean ± SD); however, the difference in the means was less than 2 bpm (1.616) (Supplementary Table S1). ## 3.2. Heart Rate and Blood Pressure Variability Measurements No statistically significant results were found in the 24 h HRV and BPV measurements (Supplementary Tables S2 and S3). ## 3.3. Retinal Measurements In this study, retinal data were available for 25 participants, comparing images taken before and after the MLT and placebo interventions. Significant differences were found in the change in the CRAE ($p \leq 0.001$) and CRVE ($$p \leq 0.002$$) before and after the MLT/placebo intervention (Table 2 and Supplementary Table S4). While under MLT the CRAE and CRVE decreased from before to after, the CRAE and CRVE increased under the placebo condition. However, the measures of the participants already differed significantly before the start of any of the interventions. As can be seen in Table 2, the variation in the retinal vessel diameters was large already in the baseline measurements. Hence, the significant effect results from the opposing change in CRAE (and CRVE) under MLT compared to the placebo, which might only reflect naturally occurring fluctuations in the microcirculation, rather than an effect of MLT. ## 4. Discussion In this study, we investigated the effect of MLT on cardiovascular physiology. We observed that CRAE and CRVE became smaller after MLT, and to the same extent, wider after placebo therapy. However, CRAE after MLT reached values similar to those achieved under the baseline condition before the placebo light therapy. Furthermore, baseline values of the same individual differed to the same extent before the application of any therapy, suggesting that the observed effect is only due to naturally occurring fluctuations in the opposing direction. Furthermore, no significant effects on HRV and BPV were found. To our knowledge, no previous studies have examined the effect of light therapy on retinal microcirculation. Light therapy, as well as yoga or meditation, is a type of energy therapy in which the belief that there are energy fields that flow through and around your body plays an important role. One recent study investigated the effect of a 4-week cardiac rehabilitation intervention on 2 groups of patients, using typical exercise therapy (control group) and typical exercise therapy plus transcendental meditation (intervention group) to determine both cardiovascular and muscular responses [29]. They observed a significant reduction in systolic blood pressure and a nearly significant reduction in HR; they also observed a significant elevation in the RR interval after 4 weeks of rehabilitation, without interactions between the groups [29]. This study also examined the retinal microcirculation parameters. It included one more follow-up measurement and another rehabilitation group of patients (typical exercise therapy and yoga exercise). However, no significant results were observed during the study, as well as between the different study rehabilitation groups (data not published). Several previous studies showed a decrease in the HRV, and a switch in the sympathovagal balance to the sympathetic side after light therapy [30,31,32]. We did not observe changes in the HRV parameters. The narrowing of vessels limits blood flow, hence increasing BP within the walls of the blood vessels [33]. However, we did not find changes in BP in our study. Light therapy in the visible range spectrum can affect photosensitive molecules, such as ATP, superoxide dismutase, or cytochrome C oxidase, which then affect the redox balance in the cells [11,12,13]. Current studies suggest that light therapy leads to an increase in mitochondrial activity, ROS production, as well as NO and, therefore, in vasodilation [11,34,35,36]. We did not find that light therapy had any significant effects on systolic blood pressure (SBP) or diastolic blood pressure (DPB). A pilot study that included 44 hypertensive subjects investigated the effect of laser acupuncture on BP, body weight, and HRV [37]. The low-level laser treatment (90 days, at least 12 treatments per subject) caused a significant reduction in both SBP and DBP [37]. Therefore, in our case, a short period of light therapy and the fact that our study group included only healthy individuals could be reasons for the lack of significant results found. To support the light therapy findings above, Heiss and colleagues, in a randomized crossover study that included 14 healthy male subjects, investigated the 2-day effect of monochromatic blue light or blue light with a filter foil (control light) on cardiovascular health. One light session took 30 min [36]. They saw that monochromatic blue light causes a decrease in SBP and arterial stiffness, and improves endothelial function [36]. Moreover, they also observed increased blood flows and increased levels of nitric oxide species as clear signs of vasodilatation, which is in contrast with the present study. However, our baseline values in the same individual differed to the same extent before the application of any therapy, suggesting that the observed effect is only due to naturally occurring fluctuations. Furthermore, this was not confirmed by any significant effects in other investigated parameters. Regarding HR, a study that included 7 participants observed a decrease in the HR after 10 min of blue light (456 nm) exposure [30]. Another study investigating free-living trends in sleep and recovery found that the mean HR was significantly lower the night after light therapy [38]. The study included 12 athletes, who were exposed to visible red (660 nm) and near-infrared (NIR, 850 nm) light in an average of 8.5 ± 7.5 sessions/athlete, while one session took 20 min. No more than 2 sessions and no sessions on consecutive days were allowed. Distinct from their study, we observed a higher HR after MLT ($$p \leq 0.044$$). However, the significant effect was so small that the difference in the means was less than 2 bpm (1.616), so it could be easily caused by any small variation during the flow of the protocol. Unfortunately, the statistical tests only detect relative differences and no absolute values, such as 2 or 20 bpm. Therefore, these results must be interpreted very carefully and should be repeated in future research. No significant effects on HRV and BPV were found in our study. The crossover study of Travis et al. found that MLT had a significant effect on the subjective feeling of wellness in 18 individuals with experience in meditation [22]. The design of their study was similar to ours, but all subjects were long-term meditation practitioners, and the favorable results of the study could be easily caused by the effect of meditation rather than by MLT itself. The same study that observed a decrease in HR after 10 min of exposure to blue light (456 nm) also noted a decrease in HRV [30]. Yuda et al. found a significant decrease in high frequency (HF) and an increase in the low frequency (LF)/HF ratio as an indicator of reduced parasympathetic activity; this was due to the effect of 6 min of blue, red, and green light exposure [31]. Another study included 20 participants and found that 10 min of exposure to red light increases LF/HF ratio and LF, hence increasing sympathetic activity [32]. On the other hand, blue light causes a reduction in LF and the LF/HF ratio, and an increase in HF causes more cardiac relaxation via parasympathetic activity [32]. While we could not find any additional studies that examined the effects of light therapy on HRV and BPV, the available literature from yoga studies show that yoga exercise leads to a significant increase in HRV parameters, especially those associated with the vagal tone [39,40,41]. Khattab and colleagues observed an increase in HRV as the effect of a 5-week (once week/90 min) yoga program in 11 healthy (7 women and 4 men, mean age: 43 ± 11; range: 26–58 years) study participants [39]. Similarly, Papp and colleagues noticed increased vagal tone and reduced sympathetic activity after an 8-week yoga program [40]. In agreement with the previous two studies, a shift in the sympathovagal balance in favor of parasympathetic dominance was observed after meditation practice (once per day, 4 times per week for one year) [41]. However, most studies investigating the effect of yoga on HRV are completed in India, struggle with sample size, are poor in design and quality, and use a range of heterogeneous measures [41,42,43,44]. Overall, the effect of yoga on HRV parameters appears to be beneficial, and shifts the autonomic regulation on the parasympathetic side; however, more research, especially from western countries, is needed in order to confirm these findings. ## 5. Limitations There are some limitations to this study: [1] We do not have detailed information about the gem lights used for the MLT or knowledge about wavelengths. It is difficult to compare our results with previous research and an overall interpretation of the results must be performed carefully; [2] According to previous studies about the effects of light therapy on human health, the majority of the studies applied light for longer periods of time than our study (the length of the intervention in our protocol was set according to the recommendations of the MLT practitioner), and it is possible that we did not see changes in any other parameters because the application time of the light was short; [3] While our study investigated cardiovascular physiology parameters in healthy participants, most studies used light therapy as a treatment (e.g., depression, hypertension, wounds healing, etc.), when the effect of light therapy could be possibly more pronounced by the imbalance of the body; [4] As it is presented in the results section, the significant effects might only reflect naturally occurring fluctuations in the microcirculation, rather than an effect of MLT, and, therefore, these results need to be interpreted very carefully; and [5] The observed caliber of the retinal microvasculature could also be influenced by errors introduced while measurements were being taken. We do not believe that this is the case, as all the retinal measurements were carried out by the same person (A.S.). ## 6. Conclusion and Future Directions The present pilot study observed changes in CRAE ($p \leq 0.001$) and CRVE ($$p \leq 0.002$$). CRAE and CRVE decreased under MLT and increased under the placebo condition from before to after. Hence, the significant effect results from the opposing change in CRAE (and CRVE) under MLT, compared to the placebo. However, because the baseline values of the participants already differed significantly before the application of any therapy, and the variation in retinal vessel diameters was large already in the baseline measurements, the observed effect results may only reflect naturally occurring fluctuations in the microcirculation and not the effect of MLT. Thereby, the results observed in the present pilot study should be treated with caution. No other significant changes in the measured physiological parameters were found to support the findings related to retinal microcirculation. It is possible that the application of the MLT was of a rather short duration. The present pilot study investigated the effects of MLT on healthy volunteers. In the future, larger studies, in which MLT is applied for longer periods of time and/or in patients with different diseases (e.g., depression, hypertension), could discover the physiological impacts of this type of therapy. ## References 1. Boutouyrie P., Chowienczyk P., Humphrey J.D., Mitchell G.F.. **Arterial Stiffness and Cardiovascular Risk in Hypertension**. *Circ. Res.* (2021.0) **128** 864-886. DOI: 10.1161/CIRCRESAHA.121.318061 2. Cimminiello C., Zambon A., Polo Friz H.. **Hypercholesterolemia and cardiovascular risk: Advantages and limitations of current treatment options**. *G. Ital. Cardiol.* (2016.0) **17** 6S-13. DOI: 10.1714/2254.24276 3. 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--- title: 'Variation Patterns of Hemoglobin Levels by Gestational Age during Pregnancy: A Cross-Sectional Analysis of a Multi-Center Retrospective Cohort Study in China' authors: - Mengxing Sun - Tingfei Gu - Tianchen Wu - Xiaoli Gong - Xiaona Li - Jiaqi Huang - You Li - Yangyu Zhao - Huifeng Shi - Yuan Wei journal: Nutrients year: 2023 pmcid: PMC10054432 doi: 10.3390/nu15061383 license: CC BY 4.0 --- # Variation Patterns of Hemoglobin Levels by Gestational Age during Pregnancy: A Cross-Sectional Analysis of a Multi-Center Retrospective Cohort Study in China ## Abstract Background: *Pregnancy anemia* is a global health concern. However, to our knowledge, there still has little consensus on the reference value of hemoglobin levels. Particularly, little evidence from China was accessible in most existing guidelines. Objective: To evaluate hemoglobin levels and anemia prevalence of pregnant women in China and offer evidence for anemia and its reference values in China. Methods: A multi-center retrospective cohort study was conducted among 143,307 singleton pregnant women aged 15–49 at 139 hospitals in China, with hemoglobin concentrations routinely tested at each prenatal visit. Subsequently, a restricted cubic spline was performed to reveal a non-linear variation of hemoglobin concentrations during the gestational week. The Loess model was used to describe the changes in the prevalence of different degrees of anemia with gestational age. Multivariate linear regression model and Logistic regression model were applied to explore influencing factors of gestational changes in hemoglobin level and anemia prevalence, respectively. Results: Hemoglobin varied nonlinearly with gestational age, and the mean hemoglobin levels decreased from 125.75 g/L in the first trimester to 118.71 g/L in the third trimester. By analyzing hemoglobin levels with gestational age and pregnancy period, we proposed new criteria according to 5th percentile hemoglobin concentration in each trimester as a reference for anemia, with 108 g/L, 103 g/L, and 99 g/L, respectively. According to WHO’s criteria, the prevalence of anemia sustainably increased with gestational age, with $6.2\%$ ($\frac{4083}{65}$,691) in the first trimester, $11.5\%$ ($\frac{7974}{69}$,184) in the second trimester and $21.9\%$ (12,$\frac{295}{56}$,042) in the third trimester, respectively. In subsequent analysis, pregnant women in non-urban residents, multiparity, and pre-pregnancy underweight tended to have lower hemoglobin levels. Conclusions: This research, the first large-sample study to present a set of gestational age-specific reference centiles for hemoglobin levels in China, could be used to obtain a better understanding of the overall levels of hemoglobin in Chinese healthy pregnant women and ultimately offer clues for a more precise hemoglobin reference value of anemia in China. ## 1. Introduction Anemia is a state in which the number of red blood cells or hemoglobin is not reduced enough to meet the physiological needs of the body [1]. Particularly, gestational anemia, associated with increased risk of cesarean section, maternal mortality, reduced birthweight, and preterm birth [1,2,3,4], remains a global health concern [5,6]. Appropriate guidelines for the measurement of hemoglobin and the definition of anemia are crucial for both clinical and public health medicine. The most widely used guideline of anemia is WHO’s recommendations, with severe, moderate, and mild anemia for pregnant women referring to hemoglobin concentrations of less than 70 g/L, 70 to 99, and 100 to 109 g/L, respectively. It should be emphasized that WHO’s guideline was first proposed based on five studies of predominantly white populations in Europe and North America, with little available data from China. However, reference for anemia should particularly consider complexities across different populations, especially with racial and environmental factors [1]. Moreover, although other guidelines have already recommended a hemoglobin cutoff lower than 110 g/L to define anemia during pregnancy, there is a lack of evidence in China, and therefore, further work is needed to validate them. In fact, several studies have already reported similar or even lower risks of low birthweight and stillbirth in pregnant females with mild anemia compared with those who had normal hemoglobin concentrations according to WHO recommendations [7,8]. Particularly, a national study in China reported that mild anemia in Chinese pregnant women is associated with improved maternal and fetal survival and fetal growth [9]. Conversely, studies have already reported a U-shaped curve for risk associated with maternal hemoglobin, iron status, or iron supplementation, with routine iron supplements bringing higher risks of SGA (Small for Gestational Age) and hypertension disorder [8,10]. Thus, although anemia remains one of the most common laboratory diagnoses, consensus on the hemoglobin threshold below which it should be defined is limited, especially when it comes to China [9]. In response to these issues, this study, by depicting the variation curve of hemoglobin levels with gestational age, aimed to provide clues for a more precise reference range of maternal hemoglobin levels during pregnancy in China. ## 2.1. Study Design and Data Collection We used the data from a multi-center prospective cohort study designed to explore the correlation between serum vitamins A and E during pregnancy and preeclampsia from 2015 to 2020, recruiting pregnant women who received routine prenatal care during whole pregnancy at 180 hospitals in 23 provinces across three geographical regions in China. In order to guarantee data quality, at least one tertiary maternity hospital was invited as the research center in each province. This study collected results of maternal blood routine examinations and correspondent medical records in at least one follow-up during the 1st, 2nd, and 3rd trimesters of pregnancy. We conducted a multi-center retrospective study and a secondary analysis based on the prospective cohort. A total of 143,307 singleton pregnant women, aged 15–49 were recruited in this study. We used data whose records contained at least one hemoglobin measurement during 5–41 gestational weeks. Cases of pregnant women who did not have credible results of hemoglobin concentration (<30 g/L or >180 g/L), were conceived by assisted reproductive technology, or had pregnancy complications (hypertension, preeclampsia, diabetes, gestational diabetes, intrahepatic cholestasis, abnormal amniotic fluid, premature rupture of membranes, threatened abortion, etc.) were excluded from this study. All the procedures of this study were reviewed and approved by the Peking University Third Hospital Medical Science Research Ethics Committee (IRB00006761-2015277). ## 2.2. Traditional RANGE of Hemoglobin Measurement and Maternal Anthropometrics Hemoglobin concentrations were routinely tested at the local laboratory at each prenatal visit. Anemia for pregnant women was classified by hemoglobin levels according to WHO definitions: severe anemia (<70 g/L), moderate anemia (70~100 g/L), and mild anemia (100~110 g/L). Provinces were divided into three geographical regions: eastern China (Beijing, Tianjin, Hebei, Liaoning, Shandong, Jiangsu, Zhejiang, and Guangdong), central China (Anhui, Henan, Shanxi, Hubei, Hunan, Jilin, and Heilongjiang), and western China (Chongqing, Yunnan, Sichuan, Guangxi, Qinghai, Ningxia, Shaanxi, and Inner Mongolia). Age, ethnic origin, education, Hukou (urban residents, rural residents, or rural-to-urban migrants), primigravida, labor year, height, and weight prior to pregnancy were extracted from medical records. Underweight, normal BMI, overweight, and obesity were defined as a BMI of <18.5,18.5–23.9, 24–27.9, and ≥28, respectively, by using the diagnostic criteria in Chinese adults. ## 2.3. Statistical Analysis We summarized the baseline characteristics of pregnant women (Table 1). We calculated the mean and SD of hemoglobin concentration and anemia prevalence (refer to WHO criteria) of each gestational week. Pearson’s chi-square test was applied to categorical variables and the one-way ANOVA test was applied to continuous variables for comparison. Restricted cubic spline was performed to reveal a non-linear variation of hemoglobin concentrations during the gestational week. Loess-model was used to describe the changes in the prevalence of different degrees of anemia with gestational age. Multivariate linear regression model and logistic regression were applied to explore influencing factors of gestational changes in hemoglobin level and anemia prevalence in different trimesters, respectively. All statistical analyses were performed with SPSS software version 26.0, SAS software, version 9.0, and the R statistical software, version 3.6.2. $p \leq 0.05$ was regarded as statistically significant. ## 3. Results A total of 143,307 pregnant women with required data from 139 hospitals were included (Figure 1). ## 3.1. Baseline Characteristics In our study, the major labor years of participants were between 2015 and 2018($93.4\%$). The mean age of pregnant women was 28.78 (±4.48) years old. Most participants lived in urban areas ($69.6\%$) and attained an educational of level more than high school ($62.7\%$). The majority of participants were divided into the normal pre-pregnancy BMI group ($69.7\%$) and were from eastern China ($54\%$). The proportion of primigravid and multipara was $55.4\%$ and $44.6\%$, respectively; $97.8\%$ of participants’ ethnicity were Han and $21.8\%$ of participants’ ethnicity were minorities (Table 1). ## 3.1.1. Hemoglobin Levels during Pregnancy Results of hemoglobin concentration during 5–41 weeks of 143,307 pregnant women were calculated, in which 65,691, 69,184, and 56,042 participants had effective hemoglobin values in the first, second, and third trimesters, respectively. The mean (SD) and percentile of hemoglobin concentrations and the anemia prevalence according to gestational age were displayed in Table 2. The median hemoglobin concentration was highest (128 [IQR 121–135] g/L) in the 8th gestational week and 119 (IQR 110–116) g/L in the 40th gestational week. We modeled gestational age by applying restricted cubic splines to allow the pattern of hemoglobin concentration to vary in a smooth manner across the whole period. The estimated 1st, 5th, 10th, 50th, 90th, 95th, and 99th percentiles for hemoglobin concentration by gestational age were displayed in Figure 2. To assess the validity of the model, we visually compared the predicted mean and SD with the crude data and calculated the percentage of hemoglobin measurements that fell within the predicted limits for 1 and 2 SDs (where $77.6\%$ and $96.1\%$, respectively, would be expected in a perfect model). We supposed that the 5th percentile hemoglobin concentration level is a new definition of maternal anemia in China for avoiding overtreatment. ## 3.1.2. Prevalence of Anemia among Pregnant Women The prevalence of anemia of all degrees was presented in a slightly increasing trend by gestational age shown in Figure 3. We calculated hemoglobin concentrations and the prevalence of anemia according to trimesters in WHO criteria and our definition. As shown in Table 3 and Figure 4, hemoglobin tended to decrease with advancing trimesters from 125.75 g/L in the first trimester to 118.71 g/L in the third trimester. The prevalence of anemia was $6.2\%$ ($\frac{4083}{65}$,691) in the first trimester, $11.5\%$ ($\frac{7974}{69}$,184) in the second trimester, and $21.9\%$ (12,$\frac{295}{56}$,042) in the third trimester (Table 4) by WHO criteria. Mild anemia was predominant in all trimesters of pregnancy. However, the anemia prevalence was $4.8\%$ in the first trimester, $4.9\%$ in the second trimester, and $4.4\%$ in the third trimester by regarding hemoglobin level below the 5th percentile hemoglobin concentration reference in each trimester as anemia. ## 3.2. Subgroup Percentages of Maternal Hemoglobin Concentration and Anemia Table 4 and Table 5 showed hemoglobin concentrations and the prevalence of anemia in each trimester of subgroups classified by different characteristics, including year, area, Hukou, age group, education, and p-BMI group. ## 3.3. Subgroup Logistic Regression Analyses of Hemoglobin Levels and Anemia As shown in Table 6 the multivariate linear regression analysis identified the associated factors with hemoglobin concentrations in each trimester. The association between labor year and hemoglobin concentration varied by gestational age. The labor year was positively associated with hemoglobin concentration in the first trimester, while negatively associated with hemoglobin concentration in the second and third trimesters. Pregnant women in eastern China had higher serum hemoglobin concentrations during pregnancy than those in central China and western China in the first trimester (B, −2.146 [$95\%$CI, −2.392, −1.899]), (B, −2.664 [$95\%$CI, −2.926, −2.402]), but this trend gradually disappeared in the third trimester. Compared with urban pregnant women, migrants, and rural pregnant women had lower hemoglobin concentrations during pregnancy. Older pregnant women tended to have higher hemoglobin concentration, with $p \leq 0.001$, 0.078(0.056, 0.101) in the second trimester and $p \leq 0.001$, 0.115(0.090, 0.140) in the third trimester. The hemoglobin level of multiparous women was significantly lower than that of primiparous women. Compared with normal pre-pregnancy BMI, the hemoglobin level of underweight pregnant women was significantly lower, and the hemoglobin level of obese and overweight pregnant women was significantly higher. Table 7 presented the associated factors with the anemia prevalence in each trimester. Pregnant women in western China had a higher risk of anemia (OR, 1.788 [$95\%$CI, 1.652–1.935]) than those in eastern China in the first trimester, but this trend reverse in the second (OR, 0.811 [$95\%$CI, 0.763–0.863]) and the third trimester (OR, 0.938 [$95\%$CI, 0.895–0.983]). Pregnant women residing in central China suffered higher risk than those in eastern China. Older pregnant women had a higher anemia prevalence in the first trimester (OR, 1.027 [$95\%$CI, 1.109–1.035]), while had a lower risk of anemia in the second (OR, 0.994 [$95\%$CI, 0.988–1.000]) and the third trimester (OR, 0.987 [$95\%$CI, 0.982–0.992]). The following factors were identified independently associated with a higher risk of anemia during the whole pregnancy: multiparity, pre-pregnancy underweight, and higher education level. ## 4.1. Summary This study innovatively demonstrated variations in hemoglobin levels and anemia prevalence by gestational age in 143,307 singleton pregnant women. Hemoglobin varied nonlinearly with gestational age, and the mean hemoglobin levels decreased from 125.75 g/L in the first trimester to 118.71 g/L in the third trimester. By analyzing hemoglobin levels with gestational age and pregnancy period, we proposed new criteria according to 5th percentile hemoglobin concentration in each trimester as a reference for anemia, with 108 g/L, 103 g/L, and 99 g/L, respectively. According to WHO’s criteria, the prevalence of anemia sustainably increased with gestational age, with $6.2\%$ ($\frac{4083}{65}$,691) in the first trimester, $11.5\%$ ($\frac{7974}{69}$,184) in the second trimester and $21.9\%$ (12,$\frac{295}{56}$,042) in the third trimester respectively while anemia prevalence was $4.8\%$ in the first trimester, $4.9\%$ in the second trimester and $4.4\%$ in the third trimester according to our new reference. We also depicted hemoglobin concentration levels in different trimesters and explored their associated factors, with non-urban residents, multiparity, and pre-pregnancy underweight associated with lower hemoglobin levels. ## 4.2. Comparisons and Applications In our study, we mainly found that hemoglobin levels demonstrated natural fluctuations in hemoglobin levels by trimester, due to fetal and maternal physiological demands. Generally, it is recognized that there is a normal 1.0 g/dL decrease in hemoglobin in 1st and 3rd trimesters, with hemoglobin concentrations diminishing an additional 0.5 g/dL in 2nd trimester of pregnancy [11]. In subgroup logistic analysis, we found that pregnant women in eastern China had higher serum hemoglobin concentrations during pregnancy than those in central China and western China in the first trimester. Considering that eastern *China is* more developed than other areas of China, differences in the 1st trimester of pregnancy which reflects the basic iron amount probably arise from different levels of local economic development, lifestyle, and diet [12]. As a reference to maternal anemia, according to WHO’s criteria, the prevalence of anemia was $6.2\%$, $11.5\%$, and $21.9\%$ in 1st, 2nd, and 3rd trimesters of pregnancy, respectively, this was similar to the prevalence of anemia in China reported earlier [9,12,13]. It is remarkable that mild anemia by WHO’s criteria refers to 100 to 109 g/L hemoglobin levels during pregnancy. However, in our new recommendation, the range of mild anemia by WHO mainly fell into a reference for non-anemia, similar to studies that proposed hemoglobin cutoff lower than 110 g/L to define anemia during pregnancy in other countries. In fact, our previous nationwide study [9] has already reported that mild anemia by WHO’s recommendations is associated with decreased risks of fetal growth restriction and stillbirth in Chinese pregnant women. This finding was similar to several previous studies [4,14,15,16,17,18,19]. Increasing evidence shows that the downregulation of hepcidin and upregulation of erythropoietin related to iron deficiency may have protective effects on the cardiovascular system and other organs [20,21]. A relatively low level of hemoglobin during pregnancy probably reflects benign plasma volume expansion, which in turn reduces blood viscosity, increases uteroplacental blood flow and uteroplacental perfusion, accompanied by cardiovascular changes including increased cardiac output and decreased peripheral resistance [22], thus benefiting maternal survival and facilitate fetal growth and development. Furthermore, previous studies have already reported that iron deficiency anemia was found to be associated with increased placental size and angiogenesis as well as upregulation of placental transfer systems, a physiological change serving to facilitate fetal growth and survival, in favor of fetal oxygen and nutrient supplies and ultimately [23,24]. In all, considering that mild anemia by WHO has protective effects on fetal outcomes, our study indicated that, for Chinese pregnant women, the existing WHO recommendations might need some supplementation. Moreover, pregnant women with normal hemoglobin levels were vulnerable to adverse effects of excessive interferences, as WHO recommends daily routine supplementation with 30–60 mg elemental Fe/d (plus 400 μg folic acid) throughout pregnancy. In fact, although most studies reported that supplementation of anemic women with iron reduces the rate of anemia at term [25], the adverse effect of overloaded iron and hemoglobin has already been reported [26], with higher risks of preeclampsia, prematurity, gestational diabetes (GDM) and fetal growth restriction among iron-replete pregnant women [10,27,28,29,30,31]. Astonishingly, we found that our new reference for pregnant anemia will reduce anemia, particularly excessive interference of more than $1.4\%$, $6.7\%$, and $17.5\%$ of pregnant women in China in the 1st, 2nd, and 3rd trimesters of pregnancy, respectively. Furthermore, although there did exist studies about maternal anemia in China, those studies only reported anemia prevalence, with little mention of precise hemoglobin levels. Therefore, this is the first to offer a pure perspective on anemia and hemoglobin levels of Chinese pregnant women, and its proposed progress might be further applied to or validate studies in other countries. It should be stressed that our study almost did not include moderate and severe anemia (Figure 2), so the new model has little influence on them. In fact, higher levels of anemia are associated with negative perinatal outcomes, including postpartum hemorrhage and hypovolemia [32]. We believe that interventions for moderate to severe anemia should be recommended and that monitoring and prevention of potential adverse outcomes are needed for pregnant females with anemia. Meantime, the lower threshold of anemia offers an opportunity for reducing unnecessary treatment and patients’ anxiety, better guarding the progress of a pregnancy. ## 4.3. Limitations It should be noted that due to certain reasons, the database of this study lacked accurate information on perinatal outcomes. Therefore, we could not evaluate relationships between hemoglobin levels and perinatal outcomes. However, our previous study might supplement this gap to some extent, offering a view of the relationships between anemia rates and perinatal outcomes [9]. Furthermore, from a statistical perspective, it seems that this study design is enough to offer a reliable threshold for hemoglobin levels based on five percent of all pregnant women. In a subsequent study, we will further this research and verify this result. Despite controlling for many covariates in the multivariable-adjusted analyses, we did not measure several important factors, especially iron supplementation and transfusions of blood products during pregnancy, which may have confounded the observed associations because of the retrospective nature of this study. Furthermore, hemoglobin levels were also influenced by dietary habits. The usage of iron supplements/drug information and dietary habits were not included in most previous research. We are aware of this and will fill this gap in subsequent single-center studies. In addition, we did not take specific residence into consideration information in data collection, therefore it would not be possible to adjust for hemoglobin levels in pregnant women at high altitudes. Most subjects lived in provinces with average altitudes lower than 1000 m, where there is no need to adjust hemoglobin levels according to WHO guidelines. In the following multi-center study, we will collect the specific residence of the subjects and adjust the hemoglobin level according to the altitude of the residence before analysis. Moreover, we could not ensure appropriate standardization of hemoglobin measurements across different hospitals and regions, which might bring bias to the results, but it should be stressed that there already has a growing tendency that clinical laboratory results will achieve inter-accreditation among different hospitals in China. ## 5. Conclusions This is the first to offer a pure perspective on anemia and hemoglobin levels of Chinese pregnant women, and its proposed progress might be further applied to or validate studies in other countries. In this study, we proposed new criteria according to 5th percentile hemoglobin concentration in each trimester as a reference for anemia, with 108 g/L, 103 g/L, and 99 g/L, respectively. 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--- title: 'Clinical Impact of Enteral Protein Nutritional Therapy on Patients with Obesity Scheduled for Bariatric Surgery: A Focus on Safety, Efficacy, and Pathophysiological Changes' authors: - Giuseppe Castaldo - Luigi Schiavo - Imma Pagano - Paola Molettieri - Aurelio Conte - Gerardo Sarno - Vincenzo Pilone - Luca Rastrelli journal: Nutrients year: 2023 pmcid: PMC10054434 doi: 10.3390/nu15061492 license: CC BY 4.0 --- # Clinical Impact of Enteral Protein Nutritional Therapy on Patients with Obesity Scheduled for Bariatric Surgery: A Focus on Safety, Efficacy, and Pathophysiological Changes ## Abstract Background: Ketogenic diet-induced weight loss before bariatric surgery (BS) has beneficial effects on the reduction in the liver volume, metabolic profile, and intra- and post-operative complications. However, these beneficial effects can be limited by poor dietary adherence. A potential solution in patients showing a poor adherence in following the prescribed diet could be represented by enteral nutrition strategies. To date, no studies describe the protocol to use for the efficacy and the safety of pre-operative enteral ketogenic nutrition-based dietary protocols in terms of weight reduction, metabolic efficacy, and safety in patients with obesity scheduled for BS. Aims and scope: To assess the clinical impact, efficacy, and safety of ketogenic nutrition enteral protein (NEP) vs. nutritional enteral hypocaloric (NEI) protocols on patients with obesity candidate to BS. Patients and methods: 31 NEP were compared to 29 NEI patients through a 1:1 randomization. The body weight (BW), body mass index (BMI), waist circumference (WC), hip circumference (HC), and neck circumference (NC) were assessed at the baseline and at the 4-week follow-up. Furthermore, clinical parameters were assessed by blood tests, and patients were asked daily to report any side effects, using a self-administered questionnaire. Results: Compared to the baseline, the BW, BMI, WC, HC, and NC were significantly reduced in both groups studied ($p \leq 0.001$). However, we did not find any significative difference between the NEP and NEI groups in terms of weight loss ($$p \leq 0.559$$), BMI ($$p \leq 0.383$$), WC ($$p \leq 0.779$$), and HC ($$p \leq 0.559$$), while a statistically significant difference was found in terms of the NC (NEP, −$7.1\%$ vs. NEI, −$4\%$, $$p \leq 0.011$$). Furthermore, we found a significant amelioration of the general clinical status in both groups. However, a statistically significant difference was found in terms of glycemia (NEP, −$16\%$ vs. NEI, −$8.5\%$, $p \leq 0.001$), insulin (NEP, −$49.6\%$ vs. NEI, −$17.8\%$, $p \leq 0.0028$), HOMA index (NEP, −$57.7\%$ vs. NEI, −$24.9\%$, $p \leq 0.001$), total cholesterol (NEP, −$24.3\%$ vs. NEI, −$2.8\%$, $p \leq 0.001$), low-density lipoprotein (NEP, −$30.9\%$ vs. NEI, $1.96\%$, $p \leq 0.001$), apolipoprotein A1 (NEP, −$24.2\%$ vs. NEI, −$7\%$, $p \leq 0.001$), and apolipoprotein B (NEP, −$23.1\%$ vs. NEI, −$2.3\%$, $p \leq 0.001$), whereas we did not find any significative difference between the NEP and NEI groups in terms of aortomesenteric fat thickness ($$p \leq 0.332$$), triglyceride levels ($$p \leq 0.534$$), degree of steatosis ($$p \leq 0.616$$), and left hepatic lobe volume ($$p \leq 0.264$$). Furthermore, the NEP and NEI treatments were well tolerated, and no major side effects were registered. Conclusions: Enteral feeding is an effective and safe treatment before BS, with NEP leading to better clinical results than NEI on the glycemic and lipid profiles. Further and larger randomized clinical trials are needed to confirm these preliminary data. ## 1. Introduction In patients with morbid obesity scheduled for bariatric surgery (BS), pre-operative moderate weight loss (~$10\%$) and liver volume and steatosis reduction are desirable [1,2,3,4,5]. Liver steatosis in patients suffering from morbid obesity undergoing BS increases the liver volume and may complicate the surgical procedure when the liver’s left lateral section is massively enlarged, limiting the access to the esophagogastric junction and increasing the risk of laceration of the soft fatty liver with consequent bleeding [6,7]. In turn, these difficulties may result in an increased operative time, suboptimal surgery, and an increased rate of conversion to open surgery [7]. With the aim to obtain moderate weight loss and liver volume and steatosis reduction before BS, several dietary protocols have been introduced over time, among them very low-calorie diets (VLCDs) and very low-calorie ketogenic diets (VLCKDs) are widely prescribed [8,9,10,11,12]. In particular Schiavo et al., have shown that a 4-week preoperative ketogenic diet is safe and effective at reducing body weight (−$10.3\%$, $p \leq 0.001$, in males; −$8.2\%$, $p \leq 0.001$, in females) and the left hepatic lobe volume (−$19.8\%$, $p \leq 0.001$) in patients with obesity scheduled for BS [13]. Furthermore, Albanese et al., aiming to compare surgical outcome and weight loss in two groups of patients who were offered two different pre-operative kinds of diet (VLCD and VLCKD), reported that VLCKDs showed better results than VLCDs on surgical outcome, influencing the drainage output, post-operative hemoglobin levels, and hospital stay [14]. Evidence suggests that VLCKDs can be effective tools for positively managing weight loss, glycemic control, and lipid profile changes [15,16]. However, these beneficial effects can be limited by poor dietary adherence. In particular, cultural, religious, and economic barriers pose unique challenges to achieving nutritional compliance with VLCKDs [15,17]. A potential solution is represented by the enteral nutrition strategies. Weight loss-based enteral nutrition strategies have been used in the treatment of obesity, showing promising results. In particular, Sukkar et al., assessing the feasibility of a protein-sparing modified diet delivered by naso-gastric tube enterally (with continuous feeding) in obesity treatment, showed that 10 days of enteral nutrition treatment followed by 20 days of a low-calorie diet was safe and effective at reducing total body weight and abdominal circumference, and in ameliorating the patients’ respiratory capacity without major complications and side effects [18]. Similarly, Castaldo et al. evaluated the effects of a carbohydrate-free diet delivered through enteral nutrition for t2 weeks, followed by an almost equivalent oral diet administered for a further 2 weeks in 112 patients, and reported a significant reduction in BMI and waist circumference with the amelioration of blood pressure values and insulin resistance without major complications [19]. Therefore, the enteral nutrition strategies could represent a possible alternative to other methodologies, in particular, when it is recommended to improve the patient’s adherence in following the prescribed diet before BS. However, to the best of our knowledge, there are no data concerning the use of enteral feeding approach in patients with obesity candidate to BS, neither on the dietary protocols to administer (e.g., hypocaloric or ketogenic), nor on how long to administer it before BS. Therefore, the aim of this study was to assess the clinical and metabolic impact, the efficacy, and the safety of ketogenic nutrition enteral protein (NEP) vs. nutritional enteral hypocaloric (NEI) protocols on patients with obesity candidate to BS. ## 2.1. Study Design and Characteristics of the Study Patients at Baseline The study was conducted at Azienda Ospedaliera “San Giuseppe Moscati”, Avellino, Italy, between 1 October 2016 and 1 October 2019. Consecutive participants were recruited from the Division of Dietetics and Clinical Nutrition and the Division of General Surgery. All patients fulfilled the criteria declared by the International Federation for Surgery of Obesity for surgical treatment for morbid obesity [20,21]. In total, 62 patients were screened, while 60 patients were recruited and completed the intervention study. The inclusion criteria were: patient scheduled for BS after multi-disciplinary pre-operative evaluation, availability to long-term post-operative follow-up, normal kidney function serum creatinine ≤1.2 mg/dL and glomerular filtration rate ≥90 mL/min, and normal liver function (aspartate amino-transferase and/or alanine amino-transferase and/or gamma glutamyl transferase <2 × N). The exclusion criteria were: serum creatinine >1.2 mg/dL, liver failure (Child-Pugh ≥ A), insulin-dependent diabetes mellitus, atrioventricular block with QT > 0.44 ms, cardiac arrhythmias, moderate-severe cardiac failure, hypokalemia, chronic diarrhea or vomitus, 12-month previous cardio-vascular disease, pregnancy and/or lactation, current/previous neoplastic disease, psychiatric disorders, gastro-intestinal diseases, moderate-severe hypo-albuminemia (<3.0 mg/dL), 6 month previous diet-induced weight loss, and intragastric balloon. The institutional ethics committee of Azienda Ospedaliera “San Giuseppe Moscati”, Avellino, Italy, approved the study protocol, which followed the Declaration of Helsinki, according to the International Guidelines of Good Clinical Practice and the regulations of clinical trials. Informed written consent was obtained from participants, after providing information about the nature, purpose, and procedures of the study (ClinicalTrials.gov Identifier: NCT02418975, 21 March 2017); Ethics Committee Approval CECN/132). The patients were randomized 1:1 in 2 groups to undergo NEP ($$n = 31$$) or NEI treatments ($$n = 29$$). The naso-gastric tube (an 8-French polyurethane nasogastric tube) was placed after an overnight fast according to best clinical practice in day-hospital procedure. During the first visit, all patients were educated about the pump use, its feeding control, and any potential side effects (vomitus, nausea, etc.), receiving technical information for home use. Its use was necessary due to the need for precision of the daily calorie and lipid quotas to be administered. ## 2.2. Study Assessment and Endpoints Assessments and measurements were performed at the baseline and after 4 weeks by the same nutritionist and radiologist in both groups. This study was blinded for the patient, surgical team, radiologist, and statistician. The endpoints were to assess the clinical impact, efficacy, and safety of NEP vs. NEI protocols on patients with obesity candidate to BS. The duration of both the pre-operative nutritional interventions was 4 weeks. Body weight (BW), body mass index (BMI), waist circumference (WC), hip circumference (HC), and neck circumference (NC) were assessed at the baseline and at the 4-week follow-up. Furthermore, clinical parameters were assessed by blood tests, and patients were asked daily to report any side effects, using a self-administered questionnaire. ## 2.3. Safety Patients were asked daily to report any side effects using a self-administered questionnaire in terms of asthenia, heartburn, nausea, vomiting, headache, dizziness, fainting, muscle cramps, hunger, orthostatic hypotension, palpitations, and constipation. ## 2.4. Dietary Interventions NEP: Nutritional Enteral Protein (NEP) intervention consists of the continuous administration by a nasogastric probe, with the aid of a peristaltic feeding pump, of a highly hypocaloric glucidic liquid mixture (~5 kcal/kg/day) by enteral route, 2000 mL/per day (1.39 mL/min), based on 1.2 g protein/kg ideal body weight per day (calculated by Lorentz equation). The formula was made up of a fixed amount of some amino acids and a variable quantity of high-quality proteins (whey proteins). The other elements were coenzyme Q10, L-carnitine, α-linolenic acid, vitamin B6, and zinc. NEP was also accompanied by the daily oral administration of a nutritional supplement (FOS, 5000 mg; calcium carbonate, 1500 mg; magnesium carbonate, 850 mg; potassium bicarbonate, 500 mg; bicarbonate sodium, 1500 mg; potassium citrate, 500 mg; vitamin C, 180 mg; vitamin E, 30 mg; selenium, 55 mg; molybdenum, 50 µg; manganese, 1 mg; vitamin D3, 5 µg; and vitamin A, 800 µg) containing: alkalizing salts to increase the reserves of buffer substances in the body, minerals to supply the nutritional essential elements for maintaining a perfect mineral reserve, vitamins and trace elements with antioxidant activity, and intestinal transit regulatory fibers with prebiotic activity in order to promote the development of a healthy bacterial flora growth. In addition to these components, alga wakame and some herbal extracts were employed (horsetail, nettle, hawthorn, orthosiphon, and thistle) for draining, diuretic, and detoxifying actions. All patients orally took a gastric protector (proton pump inhibitor) and ursodeoxycholic acid (900 mg per day and 450 mg per day for those with and without documented liver disease). The duration of the pre-operative nutritional intervention was 4 weeks. The patients had been trained to freely drink water or unsweetened beverages (not tea or coffee), with a recommended minimum intake of 2 L per day. In patients with a history of kidney stones, the recommended water amount was 3 L per day. At the beginning of the treatment, therapy with hypoglycemic and diuretic drugs had been suspended. Treatments with antihypertensive and lipid-lowering drugs remained unchanged. During the nutritional intervention, the use of purgatives was not allowed. NEI: NEI treatment consists of the continuous administration by a nasogastric probe, with the aid of a portable nutritional pump, of a liquid mixture with a balanced composition of macronutrients, low calorie (~20 kcal/kg/day), and normoproteins, based on 1 g protein/kg ideal body weight per day, and supplied with whey proteins. The infusion rate was 2000 mL/per day (1.39 mL/min). The duration of the pre-operative nutritional intervention was 4 weeks. NEI was also supplemented by the daily oral administration of a multivitamin-multimineral complex. All patients orally took a gastric protector (proton pump inhibitor) and ursodeoxycholic acid (900 mg per day and 450 mg per day for those with and without documented liver disease). The patients had been trained to freely drink water or unsweetened beverages (not tea or coffee), with a recommended minimum intake of 2 L per day. In patients with a history of kidney stones, the recommended water amount was 3 L per day. At the beginning of treatment, therapy with hypoglycemic and diuretic drugs have been suspended. The treatments with antihypertensive and lipid-lowering drugs remained unchanged. During the nutritional intervention, the use of purgatives was not allowed. ## 2.5. Anthropometric Evaluation of the Study Population All of the participants had their heights and body weights (BWs) measured by calibrated flat scales equipped with a telescopic vertical steel stadiometer (SECA 711, Hamburg, Germany). The body mass index (BMI) was calculated as the weight (kg) divided by the height squared (kg/m2). A flexible plastic tape was used to assess the waist, hip, and neck circumferences (WC, HC, and NC, respectively). ## 2.6. Blood Tests of the Study Population Blood samples were analyzed in the clinical laboratory using automated analyzers and available commercial kits. The following blood tests were performed: hemoglobin, hematocrit, glycated hemoglobin, glycemia, azotemia, creatinine, uricemia, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides, apolipoproteins Apo A1 and Apo B, serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma glutamyl transferase (γGT), sideremia, total proteins, transferrin, albumin, sodium, potassium, calcium, magnesium, phosphorus, insulin, homeostasis model assessment insulin resistance (HOMA index), and ferritin. ## 2.7. Ultrasound Measurement For the assessment of the aortomesenteric fat thickness (AMFT), steatosis grade, and left hepatic lobe volume, according to a previous method [22], ultrasound measurements were performed using an ultrasonographic system (Hitachi EUB-8500, Hitachi Medical Systems America, Inc., Twinsburg, OH, USA). ## 2.8. Statistical Analysis Data were analyzed by the retrospective analysis of a prospective database. The statistical analysis, data visualization, and predictive analysis were performed using Statgraphics software (Statgraphics Technologies, Inc., The Plains, VA, USA). The characteristics of the population included in this study were analyzed using descriptive techniques. The results were expressed as the average mean and standard deviation. The statistical analysis of the parametric data was carried out with the Student’s t test, comparing the data at the baseline and after 4 weeks within the groups and between the NEP and NEI groups using the Mann-Whitney U test. The values of $p \leq 0.05$ were considered statistically significant, with the relative confidence interval at $95\%$. Furthermore, any p-value less than 0.001 was conventionally stated merely as $p \leq 0.001.$ ## 3.1. Impact of NEP and NEI on BW, BMI, WC, HC, and NC As shown in Table 1, before surgery, the NEP and NEI groups were comparable in terms of age, BW, and BMI. As shown in Table 2, compared to the baseline, the BW, BMI, WC, HC, and NC were significantly reduced in both groups studied ($p \leq 0.001$). However, we did not find any significative differences between the NEP and NEI groups in terms of weight loss ($$p \leq 0.559$$), BMI ($$p \leq 0.383$$), WC ($$p \leq 0.779$$), and HC ($$p \leq 0.559$$), while a statistically significant difference was found in terms of the NC ($$p \leq 0.011$$). ## 3.2. Impact of NEP and NEI on Patient’s Clinical Parameters and Safety As reported in Table 3, we found a significant amelioration of the general clinical status in both groups studied. However, the NEP group showed a significant improvement in terms of glycemic and lipid profiles when compared with the NEI group. In particular, as shown in Figure 1A–C, a statistically significant difference was found in terms of glycemia (NEP, −$16\%$ vs. NEI, −$8.5\%$, $p \leq 0.001$), insulin (NEP, −$49.6\%$ vs. NEI, −$17.8\%$, $p \leq 0.0028$), and the HOMA index (NEP, −$57.7\%$ vs. NEI, −$24.9\%$, $p \leq 0.001$), respectively. Furthermore, as shown in Figure 2A–D, a statistically significant difference was additionally found in terms of the total cholesterol (NEP, −$24.3\%$ vs. NEI, −$2.8\%$, $p \leq 0.001$), low-density lipoprotein (NEP, −$30.9\%$ vs. NEI, $1.96\%$, $p \leq 0.001$), apolipoprotein A1 (NEP, −$24.2\%$ vs. NEI, −$7\%$, $p \leq 0.001$), and apolipoprotein B (NEP, −$23.1\%$ vs. NEI, −$2.3\%$, $p \leq 0.001$), respectively. Regarding safety, no important side effects were reported. The most frequent side effect was constipation $8\%$, followed by headache $7\%$ and nausea $2\%$, especially during the first days. ## 3.3. Impact of NEP and NEI on AMFT, Steatosis Grade, and Left Lobe Liver Volume As shown in Table 4, we did not find any significative differences between the NEP and NEI groups in terms of aortomesenteric fat thickness ($$p \leq 0.332$$), degree of steatosis ($$p \leq 0.616$$), and left hepatic lobe volume ($$p \leq 0.264$$). ## 4. Discussion The present study indicates that enteral feeding is an effective and safe treatment before BS, with NEP leading to better clinical results than NEI on glycemic and lipid profiles. The role of dietary therapies before BS is widely acknowledged not only for achieving weight loss and body metrics amelioration, but also in reducing the risk of intra- and peri-operative complications, improving patients’ metabolic profiles, cardiovascular and respiratory conditions, and reducing the inflammatory status [3,6,8,9,17]. The safety and the efficacy of enteral feeding in patients with obesity has been seldom investigated [18,19]. However, to the best of our knowledge, there are no data concerning the use of enteral feeding approach in patients with obesity candidate to BS, neither on the dietary protocol to administer (e.g., hypocaloric, or ketogenic), nor on how long to administer it before BS. The weight loss obtained in our study was similar to those reported in previous studies [10,23]. Furthermore, herein we found that, compared to the baseline, WC, HC, and NC were significantly reduced in both groups studied. However, we did not find any significative difference between the NEP and NEI groups in terms of weight loss, WC, and HC, while a statistically significant difference was found in terms of NC. The NC data are clinically significant in patients with obesity candidate to BS. In fact, today, most types of BS are performed laparoscopically. However, the key element in laparoscopic surgery is the creation of pneumoperitoneum and carbon dioxide is commonly used for insufflation. The various effects of induction of pneumoperitoneum can result in respiratory embarrassment and cardiovascular changes best managed by the use of general anesthesia with endotracheal intubation. As matter of fact, NC represents a predictor of difficult intubation and difficult mask ventilation in patients with morbid obesity [24]. Concerning patients’ clinical status, the NEP strategy showed a higher impact than NEI on several parameters, such as on glycemic and lipid profiles. This was in accordance with a recent meta-analysis of clinical trials conducted by Alarim et al. with the aim to look at the published literature and summarize the interventional trials that use the ketogenic diet for glycemic control and lipid profiles, concluding that the ketogenic diet is superior to other nutritional strategies in terms of glycemic control and lipid profile improvements [25]. It is well known that the ketogenic diet represents a nutritional strategy based on the reduction in dietary carbohydrates, which induces the body to produce the glucose necessary for survival and to increase the energy consumption of fats contained in adipose tissue. Therefore, in agreement with the literature, the significant amelioration in both the glycemic and lipid profiles is, at least in part, due to the reduction in carbohydrate intake, leading to reduced blood glucose and shifting the basic metabolism of energy from glucose to ketone bodies. Furthermore, in accordance with our data, this decrease in blood glucose leads to improved insulin resistance as well [26]. From a surgical point-of-view, liver steatosis in patients suffering from morbid obesity undergoing BS increases the liver volume and may complicate the surgical procedure when the liver’s left lateral section is massively enlarged, limiting the access to the esophagogastric junction and increasing the risk of laceration of the soft fatty liver with consequent bleeding [6,7]. In turn, these difficulties may result in an increased operative time, suboptimal surgery, and an increased rate of conversion to open surgery [8]. The present study indicates that both the NEP and NEI approach were effective at reducing left hepatic lobe volume, steatosis grade, and AMFT in patients with obesity scheduled for BS, with the NEP intervention allowing for a higher reduction in the left hepatic lobe volume (−31.4 vs. −$18.5\%$, respectively), steatosis grade (−20.8 vs. −$16.1\%$, respectively), and AMFT (−28.9 vs. −$17.3\%$, respectively) than NEI. This has a huge clinical value as AMFT values represent an important component and cause of metabolic syndrome and are associated with greater cardiometabolic risk [22]. In accordance with the studies of Castaldo et al. [ 27,28], in terms of patients’ adherence, NEP and NEI interventions were safe, feasible, and well-tolerated. Only one patient discontinued the study (NEI group). Therapeutic adherence includes patient adherence not only with respect to medication, but also regarding diet, exercise, or lifestyle changes. Thus, therapeutic nonadherence occurs when an individual’s health-seeking or maintenance behavior lacks congruence with the recommendations prescribed by a healthcare provider [29]. Herein, considering that both the NEP and NEI treatments were performed using the nasogastric tube technique in the hospitalization regimen, we did not need to indirectly measure the patients’ adherence by questionnaires. Regarding safety, no important side effects were reported. The main strengths of the present study are: This study has some limitations, including the small number of patients studied and the short-term follow-up that did not allow us to draw definitive conclusions. Furthermore, we did not include the total lymphocyte count nor the serum prealbumin concentration as laboratory markers of the patients‘ nutrition. However, concerning the total lymphocyte count, as suggested in the recent literature, it did not represent a specific and insensitive marker of the nutritional status [30]. Furthermore, as described in the American Society for Parenteral and Enteral Nutrition (ASPEN) position paper, despite serum albumin and prealbumin, well-known visceral proteins, being traditionally considered as useful biochemical laboratory values in a nutrition assessment, the recent literature disputes this contention. In particular, the ASPEN position paper clarifies that these proteins characterize inflammation rather than describe nutrition status or protein-energy malnutrition. Obesity is characterized by chronic low-grade inflammation and, as such, hepatic reprioritization of protein synthesis occurs, resulting in lower serum concentrations of albumin and prealbumin. In addition, the redistribution of serum proteins occurs because of an increase in capillary permeability. There is an association between inflammation and malnutrition, but not between malnutrition and visceral-protein levels. These proteins correlate well with patients’ risk for adverse outcomes rather than with protein-energy malnutrition. Therefore, serum albumin and prealbumin should not serve as proxy measures of the total body protein or total muscle mass and should not be used as nutrition markers [31,32]. ## 5. 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--- title: Proteomic Analysis of Female Synovial Fluid to Identify Novel Biomarkers for Osteoarthritis authors: - P. Robinson Muller - Tae Jin Lee - Wenbo Zhi - Sandeep Kumar - Sagar Vyavahare - Ashok Sharma - Vikas Kumar - Carlos M. Isales - Monte Hunter - Sadanand Fulzele journal: Life year: 2023 pmcid: PMC10054440 doi: 10.3390/life13030605 license: CC BY 4.0 --- # Proteomic Analysis of Female Synovial Fluid to Identify Novel Biomarkers for Osteoarthritis ## Abstract Osteoarthritis (OA) is a highly prevalent degenerative joint condition that disproportionately affects females. The pathophysiology of the disease is not well understood, which makes diagnosis and treatment difficult. Given the physical connection of synovial fluid (SF) with articular tissues, the SF’s composition can reflect relevant biological modifications, and has therefore been a focus of research. Previously, we demonstrated that extracellular vesicles isolated from the synovial fluid of OA patients carry different cargo (protein and miRNA) in a sex-specific manner. Given the increased prevalence and severity of OA in females, this study aims to identify differential protein content within the synovial fluid of female OA and non-osteoarthritic (non-OA) patients. We found that several proteins were differentially expressed in osteoarthritic females compared with age-matched controls. Presenilin, Coagulation Factor X, Lysine-Specific Demethylase 2B, Tenascin C, Leucine-Rich Repeat-Containing Protein 17 fragments, and T-Complex Protein 1 were negatively regulated in the OA group, with PGD Synthase, Tubulointerstitial Nephritis Antigen, and Nuclear Receptor Binding SET Domain Protein 1 positively regulated in the OA group. Database for Annotation, Visualization, and Integrated Discovery (DAVID) and QuickGO analyses established these proteins as significantly involved in many biological, cellular, and molecular processes. In conclusion, the protein content of female synovial fluid is altered in OA patients, which is likely to provide insights into gender-specific pathophysiology. ## 1. Introduction Osteoarthritis (OA) is a highly prevalent degenerative condition affecting synovial joints [1]. The disease is characterized by the loss of cartilage, thickening of the synovial capsule, and the presence of hypertrophic bone and subchondral bone sclerosis [2]. The knee is the most commonly affected joint, followed by the hand and the hip [3]. According to the National Health Interview Survey results, the number of individuals in the US with OA symptoms specifically affecting the knee joint is approximately 14 million [4]. OA tends to target certain populations, with the elderly comprising the largest age demographic of those with knee OA [5] and women more likely than men to develop the condition [6]. Women and men with knee OA present differently, as women report more severe pain and higher rates of disability [7]. Women have been found to demonstrate unique patterns of cartilage degradation compared with men [8]. OA of any joint places a significant burden on people and their quality of life. Individuals with OA have been reported to experience twice as much difficulty while walking compared with those without OA. Furthermore, the affected population is restricted by limitations in activities, such as moving objects or getting dressed [9]. In addition to the constraints placed on individuals by OA, the impact has been felt on a societal level. Out of all diseases associated with disability, OA is growing the 3rd fastest, trailing only diabetes and dementia [10]. Additionally, the economic burden of OA is vast, with approximately $27 billion in health care expenditures ascribed to knee OA alone every year [11]. There are also further expenses, with a 2007 study attributing three days of work absence each year to all forms of OA, indirectly accruing a cost to society of USD 11.6 billion per year [12]. Even with this enormous problem plaguing people worldwide, the root cause of OA is still not well understood. The existing knowledge gaps pertaining to the disease have made diagnosis and treatment difficult. Although there is no absolute cure, current first-line OA treatments consist of exercise, weight loss, education, non-steroidal anti-inflammatory drugs (NSAIDs), and pain management [3]. Refractory cases can be managed with steroid injections and Total Joint Arthroplasties (TJAs) [13]. Even though TJAs impart substantial benefit to patients overall, a significant group unpredictably experience inferior outcomes [14]. The effectiveness of therapeutic intervention, in general, is greatly dependent on stage. The diagnosis of OA is usually only made when patients present with pain, and when joint damage is identified on radiographs. At this point, the damage is irreversible, and the focus is on palliation and stopping the progression of the disease. Much of the current research is focused on identifying the disease at an earlier stage, when the pathological process can be potentially stopped or slowed down. A novel approach that is being considered is analyzing the metabolic changes in arthritic tissues and synovial fluid to identify novel biomarkers. Within the joint, synovial fluid (SF) is a viscous substance lubricating and cushioning the cartilage-lined cavity. Because of its physical connection with the articular tissues, the fluid’s composition can reflect relevant biologic alterations. Recently, we found that extracellular vesicles isolated from the synovial fluid of OA patients were differentially expressed in a sex-specific fashion [15,16]. Given the increased prevalence and severity of OA in females, we aimed to identify differential protein expression within the synovial fluid of female osteoarthritic (OA) and non-osteoarthritic (non-OA) patients. We collected age-matched synovial fluid of the two groups and analyzed them using mass spectrometry. We found several proteins were differentially expressed in the synovial fluid between the OA and non-OA female groups. Bioinformatic analyses revealed that these proteins as being involved in processes such as cell adhesion, cell differentiation, and locomotion, as well as playing a role in inflammation, tumorigenesis, and bone/cartilage formation. ## 2.1. Patient Samples All methods were approved by the ethical committee (Code: 657441-24), in accordance with the guidelines and regulations of Augusta University. The Augusta University Institutional Review Board (IRB) approved the studies. Synovial fluid waste samples from age-matched female human knee joints [non-OA ($$n = 13$$), mean age 50.84 (±10.0) and OA ($$n = 15$$) mean age 52.8 (±5.6) patients] were obtained and deidentified, and did not necessitate informed consent approval. The SF samples were acquired from women undergoing total knee arthroplasties or arthrocentesis. These samples were obtained from osteoarthritic and non-osteoarthritic knee joints, excluding those with severe comorbidities (e.g., diabetes, hypertension, HIV, etc.) or blood contamination. We used synovial fluid, which was clear/colorless or faintly yellow colored. We avoided synovial fluid contaminated with blood. We did not search for additional characteristics of synovial fluid, such as white blood cell count or calcium pyrophosphate crystals. The samples were transported to the laboratory after synovial fluid collection in the operating room. Synovial fluid was diluted (1:1) with phosphate-buffered saline (PBS) and centrifugation at 3000 rpm for 20 min to exclude particles and cell debris. The resultant supernatant was analyzed with mass spectrometry. ## 2.2. Protein Extraction, Digestion, and Liquid Chromatography with Tandem Mass Spectrometry (LC-MS-MS) LC-MS/MS Analysis Protein digestion and mass spectrometry were performed as per published methods [16]. Briefly, lyophilized samples were reconstituted with 100 µL of 50 mM ammonium bicarbonate buffer with $0.1\%$ (w/v) RapiGest SF Surfactant (Waters) and 10 mM dithiothreitol; the cysteines were reduced at 60 °C for 30 min. The samples were then alkylated by iodoacetamide for 30 min and digested using trypsin (Thermo Scientific #90057) for 16 h at 37 °C. Trifluoroacetic acid was then added into the sample tube to lower the pH to under 2. The samples were subsequently incubated at 37 °C for 40 min to cleavage the detergent, followed by centrifuging at 15,000× g for 5 min. The supernatants were then collected into sample vials for LC-MS analysis. The digested peptide samples were analyzed on an Orbitrap Fusion tribrid mass spectrometer (Thermo Scientific, New York, NY, USA), to which an Ultimate 3000 nano-UPLC system (Thermo Scientific) was connected. Next, 2 µL of peptide samples was injected and trapped on a Pepmap100 C18 peptide trap (5 µm, 0.3 × 5 mm) and washed for 10 min at 20 µL/min using $2\%$ acetonitrile with $0.1\%$ formic acid. The peptides were then eluted from the trap and further resolved on a Pepman 100 RSLC C18 column (2.0 µm, 75 µm × 150 mm) at 40 °C. A gradient of between $2\%$ and $40\%$ acetonitrile with $0.1\%$ formic acid was used over 120 min at a flow rate of 300 nL/min to separate the peptides. LC-MS/MS analysis was carried out by data-dependent acquisition (DDA) in positive mode, with the Orbitrap MS analyzer for precursor scans at 120,000 FWHM (full width at half maximum) from 300 to 1500 m/z, and the ion-trap MS analyzer for MS/MS scans at top-speed mode (3 s cycle time). Fragment of the precursor peptides was carried out using the collision-induced dissociation method, with a normalized energy level of $30\%$. Raw MS and MS/MS spectrum for individual samples were then processed with the Proteome Discoverer software by Thermo Scientific (v1.4), and subsequently submitted to the SequestHT search algorithm against the Uniprot human database (precursor ion mass tolerance: 10 ppm, product ion mass tolerance: 0.6 Da, static carbamidomethylation of cysteine (+57.021 Da), and dynamic oxidation of methionine (+15.995 Da). Peptide spectrum matching validation and false discovery rate estimation were performed using the built-in Percolator PSM validator algorithm. ## 2.3. Statistical and Bioinformatics Analyses Spectral counting quantification was performed to compare protein abundance in different samples. Each protein in a specific sample had the peptide spectrum match (PSM) count normalized. This was done using the PSM count sums for that specific sample to compensate for possible variations during the LC-MS analysis. Further, quantile normalization was performed using the preprocessCore R package, and the differences in protein expression between the two groups (OA and non-OA) were analyzed using the LIMMA R package. Proteins that were upregulated or downregulated using a p-value cutoff of 0.05 were classified as differentially expressed for further analysis. Gene ontology pathway analyses for differentially expressed proteins and genes were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and QuickGO. Uniprot Knowledgebase (UniProtKB) protein descriptions and gene products were introduced into DAVID and QuickGO for statistical analysis and GO term annotation based on integrated cellular, molecular, and biological pathways of the differentially expressed proteins. ## 3.1. Synovial Fluid Protein Content in Women Differs Significantly from OA Patients In previous studies, we demonstrated that extracellular vesicle protein and exosomal miRNA content are altered in OA patients in a sex-specific manner [15,16]. In the present study, we completed mass spectrometry profiling and analysis of proteins obtained from the synovial fluid of female non-OA ($$n = 13$$) and OA ($$n = 15$$) patients. The synovial fluid was acquired from the knee joints of women undergoing either arthrocentesis or total knee arthroplasty procedures. The mass spectrometry data indicated several proteins expressed differentially in the two patient populations. The principle component analysis (PCA) and heat map of female OA were clustered distinctly from the non-OA (control) group (Figure 1). We found a significant disparity in 29 proteins, with 26 downregulated and 3 upregulated in the OA group (Table 1). For example, Presenilin ($$p \leq 0.02$$), Coagulation Factor X ($$p \leq 0.02$$), Lysine-Specific Demethylase 2B ($$p \leq 0.02$$), Tenascin C ($$p \leq 0.03$$), Leucine-Rich Repeat-Containing Protein 17 fragments ($$p \leq 0.02$$), and T-Complex Protein 1 ($$p \leq 0.04$$) were negatively regulated in the OA group. PGD Synthase ($$p \leq 0.03$$), Tubulointerstitial Nephritis Antigen ($$p \leq 0.04$$), and Nuclear Receptor Binding SET Domain Protein 1 ($$p \leq 0.03$$) positively regulated in the OA group (Figure 2). These results indicate that protein expression within the synovial fluid of women is significantly affected by the osteoarthritis condition. ## 3.2. DAVID and QuickGO Analysis of Differentially Expressed Proteins Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Quick GO annotation analyses were completed to evaluate the regulatory functions of the differentially expressed proteins and their roles in biological, cellular, and molecular pathways. The analyses identified that these proteins are involved in processes such as cytoskeletal organization, molecule adhesion, nucleic acid binding, cell differentiation, and response to stress and wounding (Table 2). ## 4. Discussion OA does not affect all individuals uniformly, and females are disproportionately afflicted with high prevalence and morbidity compared with males. To understand the pathophysiology and to identify an early diagnosis of OA, we performed proteomic analysis on the synovial fluid of female OA patients. Synovial fluid (SF) is secreted from the tissues of the knee joint, and its composition can provide important information about the health of the articular joint. Several techniques, including ELISA, mass spectrometry, and 3D gel electrophoresis, were used to identify biomarkers in the synovial fluid. Although previous studies have analyzed protein content in osteoarthritic joints, they failed to do so in a sex-specific manner. Thus, these studies could not provide information about distinct pathophysiologic processes in males or females. In this study, we analyzed the protein content of synovial fluid using mass spectrometry in age-matched OA and non-OA females. Our study found several proteins differentially regulated in the OA group compared with age-matched controls. Some of these proteins are important in cartilage and bone biology. For example, in the present study, Presenilin (PSEN) and Tenascin C were downregulated in the OA group’s synovial fluid. Presenilin is a transmembrane protein that plays a vital role in regulating the cleavage of several proteins in age-related diseases. It has been previously demonstrated that presenilin-deficient mice display an osteoporotic phenotype [17] with elevated osteoblast-dependent osteoclastic activity [18]. In another study comparing female congenic mice, PSEN was determined as a candidate gene that regulates trabecular thickness in a gender-specific fashion [18]. Taken altogether, these findings indicate that a decrease in Presenilin levels might be involved in bone and cartilage metabolism in a female with OA. The glycoprotein, Tenascin C (TNC), is expressed in the extracellular matrix of several tissues during the development and progression of diseases. TNC has been revealed in past studies to be positively regulated in the synovial fluid of OA and RA patients, as well as in diseased synovium and cartilage [19]. Reports indicate that TNC levels fluctuate at different stages of disease progression and cartilage repair [19]. It has been established that TNC fragments containing certain domains endogenously induce articular cartilage catabolism and synovial inflammation, with the full-length protein protecting against OA progression and stimulating cartilage repair [19]. TNC levels have been found to surge in canine synovial fluid during the early phases of OA and subsequent cartilage repair, and decrease as the cartilage matures, thus serving as a helpful indicator of OA progression. Although TNC has previously been found in elevated amounts in knee OA synovial fluid samples, the negative regulation of TNC in our OA group may point to its involvement in female pathology, an area that has not previously been reported. Other differentially expressed proteins between the two study groups have been associated with OA pathophysiology, and their regulation within the synovial fluid may give further insight into their specific functions. In the OA group of patients, Tubulointerstitial Nephritis Antigen (TINAG) and PGD synthase (PGDS) were upregulated, while Lysine-Specific Demethylase 2B (KDM2B) was downregulated, with all three proteins previously associated with OA. The dysregulation of TINAG gene expression has previously been associated with hand OA [20]. Li et al. [ 21] report an alteration of KDM2B gene expression in the synovial membranes of OA patients, which has been identified as a key transcription factor in the pathophysiology of the disease. PGDS has also been linked to OA. In male mice, the gene deletion of PGDS worsened the progression of OA, including effects on subchondral bone, synovial inflammation, and cartilage damage [22]. PDGS-negative mice displayed joint space narrowing, meniscus mineralization, and osteophyte formation [23]. Subsequent overexpression of PGDS reversed these effects [22]. The elevation of PGDS may also be a physiological response to joint insult, as it catalyzes the production of PGD2, which is a major player in resolving inflammation [24]. These three proteins may be involved in pathological synovial joints in female OA patients. Other proteins that we identified as differentially regulated in the SF of the OA and non-OA female patients have not been previously implicated in OA, but have been linked to other pathological bone-related conditions. For example, Leucine-rich repeat-containing protein 17 (LRRC17) fragments and T-Complex Protein 1 (TCP1) were both downregulated in the OA group, while nuclear receptor binding SET domain protein 1 (NSD1) was upregulated. LRRC17 prevents the activation of RANK-L-dependent osteoclasts, thus protecting against osteoporotic phenotypes. In fact, the risk of postmenopausal women experiencing osteoporotic fractures was found to be $46\%$ higher in those with lower LRRC17 levels than those with higher levels [25]. The downregulation of the LRRC17 protein in OA synovial fluid may reflect an affected pathway that is shared by the pathology of osteoporosis. TCP1 is also involved in bone pathology, and specifically, Ankylosing Spondylitis (AS)-induced heterotopic ossification. The protein has been shown to be underexpressed in the bone marrow-derived mesenchymal stem cells of Ankylosing Spondylitis compared with controls [26]. NSD1 is yet another protein involved in bone pathology, but novel in the context of OA. A deficiency of this protein is the primary cause of Sotos syndrome, which is marked by advanced bone age [27]. The pathogenesis of this condition is unknown, but the potential metabolic role that NSD1 plays in both Sotos syndrome and OA should be studied. It has been reported that bone alterations are among the earliest changes seen in osteoarthritic joints, even occurring before cartilaginous damage [28]. The relationship between OA development and bone mineral density has been staunchly disputed, and study findings are often contradictory. This may be due to a variety of OA subtypes with separate mechanisms as well as bone mineral density (BMD) fluctuations in different joint locations and disease stages [29,30]. The complicated relationship between bone metabolism and the pathogenesis of OA should nevertheless be explored, beginning with the differential expression in female synovial fluid. Our study provides a strong foundation for future exploration of OA pathophysiology, especially in women. However, the study does have some limitations. First, the sample size was limited in the number of female synovial fluid samples analyzed, and a more extensive study would be an excellent next step. A study with SF samples from females with varying stages of OA would also be beneficial in identifying the correlation between disease severity and protein expression. Investigations with large groups of diverse patient populations of females are necessary as the disease is very heterogeneous. Our study primarily focused on identifying novel proteins in the fluid samples using a proteomic approach, but future studies are needed to identify their direct roles in the pathogenesis of articular cartilage. Additional functional studies using in vitro and in vivo models could be carried out to distinguish the functions of these differentially expressed proteins in OA. More insight on the biological effect of OA can also be gained by characterizing protein expression in other body fluids, such as urine or serum. ## References 1. Berenbaum F.. **Osteoarthritis as an inflammatory disease (osteoarthritis is not osteoarthrosis!)**. *Osteoarthr. Cartil.* (2013) **21** 16-21. 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--- title: Efficacy of Hydroxytyrosol-Rich Food Supplements on Reducing Lipid Oxidation in Humans authors: - Cecilia Bender - Ilaria Candi - Eva Rogel journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054451 doi: 10.3390/ijms24065521 license: CC BY 4.0 --- # Efficacy of Hydroxytyrosol-Rich Food Supplements on Reducing Lipid Oxidation in Humans ## Abstract In the present study we report the efficacy of two food supplements derived from olives in reducing lipid oxidation. To this end, 12 healthy volunteers received a single dose (25 mL) of olive phenolics, mainly hydroxytyrosol (HT), provided as a liquid dietary supplement (30.6 or 61.5 mg HT), followed by an investigation of two reliable markers of oxidative stress. Blood and urine samples were collected at baseline and at 0.5, 1, 1.5, 2, 4, and 12 h post-intake. Plasma-oxidized low-density lipoprotein (oxLDL) cholesterol levels were measured with ELISA using a monoclonal antibody, while F2-isoprostanes (F2-IsoPs) were quantified in urine with UHPLC-DAD-MS/MS. Despite the great variability observed between individuals, a tendency to reduce lipoxidation reactions was observed in the blood in response to a single intake of the food supplements. In addition, the subgroup of individuals with the highest baseline oxLDL level showed a significant ($p \leq 0.05$) decrease in F2-IsoPs at 0.5 and 12 h post-intervention. These promising results suggest that HT supplementation could be a useful aid in preventing lipoxidation. Additionally, people with a redox imbalance could benefit even more from supplementing with bioavailable HT. ## 1. Introduction An altered balance of free radicals, resulting in high levels of oxidative stress, is associated with many chronic human diseases such as cardiovascular diseases including atherosclerosis, which are a leading cause of global mortality [1,2,3]. The first biochemical event in atherosclerosis is the oxidation of LDL in the vascular wall, producing oxLDL [4], which is involved in the formation and progression of atherosclerotic plaque [5,6]. The oxidative process of the LDL consists of a chemical modification of the protein’s moiety through the myeloperoxidase-derived enzyme [7] or the oxidation of LDL’s polyunsaturated fatty acids (PUFA) [8]. Nutrition plays an important role in the prevention of atherosclerosis [9]; in particular, dietary antioxidants can protect LDL from oxidation [10,11]. The olive tree contains phenolic compounds such as HT, tyrosol (Tyr), and oleuropein (Ole) [12,13], which have key roles in plant physiology such as enhancing the resistance to insects and microorganisms [14]. The oil obtained from the pressing of olive fruits contains phenolic compounds that contribute to the protection of LDL from oxidation. Different qualities of olive oils are available on the market, from which only extra virgin olive oil (EVOO), the less-processed olive oil that is obtained from milling and cold pressing, may contain enough phenolics [15,16] to protect LDL from oxidation. In particular, HT, one of the main antioxidants in olives, is also believed to act in table olives and oil, and has received health claim approval in the EU [17]. Indeed, the European Food Safety Authority (EFSA) has confirmed that 20 g of olive oil containing at least 5 mg of HT and its derivatives (Tyr and Ole complexes) contribute to the protection of LDL from oxidation. Despite the belief that a diet rich in olive oil should guarantee an adequate intake of olive phenolics, which due to their antioxidant capacity would have a positive effect on the prevention of cardiovascular risks by preventing LDL oxidation, other evidence suggests that the daily intake of HT, Tyr, and phenolic compounds would be insufficient [18,19] to obtain the desired physiological effect. Because these compounds are present in the olive fruit, they are also found in olive derivatives such as olive oil and vegetation waters. And because many of these substances are hydrophilic, they are found to a greater extent in the aqueous fraction that results from pressing the olive fruit during oil production [20]. It seems that to ensure the minimum useful daily dose for the protection of LDL, it would be necessary to enrich the olive oil with HT; alternatively, the consumption of food supplements containing bioavailable HT would be a valid resource. In this context, we recently reported the cellular antioxidant properties of two dietary supplements produced using the vegetation water generated during olive oil production [20], one with the addition of $6\%$ lemon juice and the other with $70\%$ grape juice. The results derived from this preliminary study denoted an important antioxidant potential of both supplements in cellular models. More recently, in a randomized controlled clinical study, we showed that dietary HT provided with both food supplements is absorbed from the intestinal tract in variable amounts and is rapidly metabolized into phase I and phase II metabolites [21]. The main HT metabolites, which were not found in the fasting state, were rapidly cleared from the plasma in the postprandial phase (tmax 30 min, complete clearance 2–4 h) and excreted in the urine mainly as 3,4-dihydroxyphenylacetic acid, homovanillic acid, and hydroxytyrosol sulfate [21]. However, the effect of supplementation with olive phenolics on lipoxidation markers has been little considered in foods other than olive oil. Therefore, the aim of this study was to investigate the effect of commercially available olive-derived dietary supplements on lipoxidation markers in humans. We hypothesized that these food supplements rich in natural bioavailable HT may strengthen the antioxidant capacity in the postprandial phase; thus, we here report the secondary outcome of this clinical study by measuring the kinetic of two reliable markers of lipoxidation, oxLDL and F2-IsoPs. F2-IsoPs are prostaglandin-like lipid peroxidation products of arachidonic acid, the main PUFA present in human cells. Numerous studies have shown these molecules to be accurate markers for systemic oxidative damage in plasma or urine [22,23,24] and their decrease to indicate a lower in vivo peroxidation of lipids. Our data indicate that a single intake of HT through both dietary supplements tends to reduce the mean concentration of oxLDL in the blood. In addition, the F2-IsoPs measurement from subjects whose oxLDL levels were elevated at baseline shows that the intake of either food supplement significantly reduces the F2-IsoPs content in urine. Despite the small sample size, the results obtained here are promising, especially for the balance of redox status in the body. Quite interesting is the marked decrease of both biomarkers of oxidative stress as a result of taking these HT-rich food supplements, with the caveat that the effect depends on the individual’s baseline condition. People who have high starting levels of these markers will experience a higher benefit. ## 2.1. Characterization of the Food Supplements The efficacy of watery food supplements derived from olive vegetation water was investigated in relation to the modulation/reduction of lipid oxidation in humans. For this, a randomized, blind, crossover study was carried out with 12 healthy volunteers who received acute supplementation of Oliphenolia bitter (hereafter referred to as IP-1), which is composed of $94\%$ concentrated vegetation water and $6\%$ concentrated lemon juice, or Oliphenolia (hereinafter IP-2), which is composed of $30\%$ further concentrated vegetation water and $70\%$ concentrated grape juice. The administered dose (25 mL – 1 flask) of the food supplements contained HT as the main bioactive (Table 1) together with (poly)phenols naturally derived from olives and lemons or grapes for IP-1 and IP-2, respectively. One volunteer dropped out of the study after the completion of the first intervention period (IP-2) and was subsequently replaced. Considering the data from this subject, the sample size for the IP-2 group is 13. The overall intervention sample size is 25 (as the sum of IP-1 and IP-2). ## 2.2. Plasma oxLDL Figure 1 shows box plots representing the oxLDL content pre-intervention and up to 12 h after intake (as the sum of IP-1 and IP-2, $$n = 25$$). The baseline plasma oxLDL levels resulting were highly variable between subjects (125.5 ± 10.49 U/L), as well as highly intra-variable (data not shown). As shown in Figure 1, a downward trend in oxLDL levels was observed after ingestion for up to 12 h, although this trend reached statistical significance after 1 h only (108.0 ± 8.66 U/L, $p \leq 0.05$). The analysis of the average oxLDL of the independent interventions (IP-1 or IP-2) shows a trend toward the reduction of oxLDL post-intervention (Figure 2A,B); however, the small sample size and the wide inter-individual variation observed do not allow to show statistical significance. Interestingly, when the statistical analysis is stratified to include only the subjects with a high level of oxLDL pre-intervention (cut off 101 U/L) that is, basal mean values higher than reported for healthy subjects [25], the oxLDL level pre-intervention (155.89 ± 14.75 U/L, $$n = 9$$) was significantly reduced at 1 h (119.46 ± 14.62 U/L, $p \leq 0.01$) after intake of IP-1 only (Figure 2C), remaining significantly reduced ($p \leq 0.05$) at 2, 4, and 12 h post-intervention. ## 2.3. Urinary F2-IsoPs The degree of oxidative stress was further evaluated by quantifying the F2-IsoPs in the urine in those subjects showing high oxLDL levels at baseline (155.89 ± 14.74 U/L and 151.55 ± 16.54 U/L for IP-1 and IP-2, respectively). Three different F2-IsoPs isomers, namely 8-isoPGF2α, ent-PGF2α, and 2,3-dinor-8-isoPGF2α, were quantified at baseline and after the intake of the food supplements. In response to a single 25 mL intake of either of the food supplements a significant decrease ($p \leq 0.05$) in F2-IsoPs (as the sum of the three isomers) was shown at 0.5 and 12 h (Table 2). Quantitatively, the excreted amount of F2-IsoPs was higher at baseline compared with after the intake of the food supplements, being more pronounced for IP-2 compared with IP-1. The isomers 2,3-dinor-8-isoPGF2α and ent-PGF2α were the main ones in terms of absolute concentration in urine; for both, the downward trend was strongest with IP-2 (Figure 3). In contrast, IP-1 better counteracted 8-isoPGF2α levels, although its abundance was ~4 to ~6-fold lower than the isomers ent-PGF2α and 2,3-dinor-8-isoPGF2α, respectively. Notably, changes in the ent-PGF2α isomer exhibited a two-phase kinetic pattern, with a significant decrease early in the time course, followed by an increase between 1.5 and 2 h, then a significant decrease again at 4 and 12 h after intake of the food supplements (Figure 3A,D). A similar pattern was observed for 8-isoPGF2α (Figure 3B, E), where the pre-intervention level decreased significantly after 0.5 h post-intake ($p \leq 0.05$); for IP-1 only, the reduction was significantly sustained over time up to 2 h. On the other hand, the abundance of 2,3-dinor-8-isoPGF2α was significantly lower ($p \leq 0.01$) immediately after the intake of IP-2 only (Figure 3F), remaining significantly reduced until 4 h after the intake. ## 3. Discussion The objective of this crossover study was to verify whether the two watery food supplements, particularly rich in HT from olives, are effective in reducing lipid oxidation in humans. To this aim, plasma oxLDL and urinary F2-IsoPs were chosen as reliable biomarkers. While previous studies with foods containing olive phenolics supported their role in lowering oxLDL in vivo [26,27,28,29,30,31,32,33,34], these studies were performed mainly with HT delivered in oil and after short- or medium-term interventions; however, to the best of our knowledge, there are no previous reports showing that olive phenolics provided in a watery matrix can also reduce oxLDL in vivo after an acute intake. Our results show a significant reduction in plasma oxLDL as soon as 1 h after the intake of a single dose of the food supplements. We also observed a downward trend in the pre-intervention levels of oxLDL in both supplement groups, studied separately (although this trend did not reach statistical significance). Levels of oxLDL showed a large inter- and intra-variability at baseline, suggesting that baseline values may play a role in the effect of HT on this marker. Considering only subjects with high levels of oxLDL at baseline, a significant reduction in oxLDL was observed at 1, 2, 4, and 12 h after the administration of IP-1 (30.6 mg HT + 0.04 mg Ole). Under this condition the performance of IP-1 was superior to that of IP-2. Unlike what was reported in the literature [27,28,29,30,31] for olive oil intake, our results do not show a simple dose dependence for an oxLDL protective effect. In fact, IP-2, the food supplement containing the highest dose of olive phenolics (61.5 mg HT + 0.07 mg Ole), did not cause a higher oxLDL reduction than IP-1, which contains almost half the HT-dose together with the lemon juice concentrate. This result is in line with our pharmacokinetic study [21], which showed that the excreted percentage of total ingested HT (calculated as the sum of all quantifiable metabolites in 12-h urine) is higher for IP-1, followed by IP-2, and then HT-fortified EVOO to a lesser extent. This finding reinforces the importance of other dietary factors influencing both bioavailability and bioefficacy, such as positive or negative matrix effectors, water or fat content, differences in phenolics either by type or content, as well as synergistic or antagonistic interactions with other food components. Our results show that plasma oxLDL likely can be lowered in subjects whose level was high at baseline, suggesting that the HT is particularly effective in individuals who are experiencing an oxidative imbalance. This observation is supported by several human trials conducted in subjects with high oxidative stress conditions, in which a significant reduction of lipoxidation was documented using different biomarkers, such as plasma oxLDL or urinary IsoPs [34,35,36,37,38]. In particular, Sarapis [34] recently reported a significant decrease of oxLDL after consumption of a high dose of olive oil polyphenols, a reduction that became more pronounced in subjects with a high cardiometabolic risk. In 2011, the EFSA published a scientific opinion in which it stated that the daily consumption of at least 5 mg of HT and derivatives (Tyr and Ole) contained in 20 g of olive oil protects the LDL against oxidation [17]. Nevertheless, other researchers pointed out that the daily intake of HT, Tyr, and phenolic compounds through a typical Mediterranean diet would supply only around 2 mg [18]. Moreover, the intake of Tyr and HT from virgin olive oil would be between 88.5 and 237.4 µg daily [19]. These studies seem to indicate that the amount of HT and its derivatives ingested daily with the Mediterranean diet or with olive oil alone would be insufficient to reach the EFSA-stated minimum intake level of 5 mg. Therefore, it seems to be advisable to increase the intake of HT and its derivatives in order to obtain the effect protective of LDL. Such an increase can be better achieved by the consumption of bioavailable HT-containing supplements. In addition to plasma LDL oxidation, another important marker to consider for the prevention of oxidative processes in vivo is the F2-IsoPs. Few studies conducted with healthy volunteers have evaluated the IsoPs content after ingesting foods derived from olives. The results remain somewhat contradictory. On one hand, a reduction in urinary 8-iso-PGF2α was observed inversely proportional to the phenolic content of the olive oils (phenolic concentrations between 24.38 and 97.5 mg/dose) when administered in a single dose [39,40]. On the other hand, further short-term studies found no significant changes in F2-IsoPs excretion. In a crossover study with olive oil rich in phenolics conducted with 182–184 healthy volunteers, despite the high dose of phenolics tested (366 mg/kg, 25 mL daily, 21 days), the oxLDL decreased, but no such effect was observed in the IsoPs [30]. However, a significant decrease in the plasma IsoPs was observed in the above study when comparing only the baseline data and the endpoint data at the end of the crossover interventions [41]. Regarding the studies with dietary supplements, no changes in urinary levels of F2-IsoPs were recorded in young people after multiple doses of olive leaf supplements in liquid or capsule formats [42]. Although the human trials of the F2-IsoPs modulation from olive-derived foods have yielded contradictory results, it is noted that the trials above evaluated different doses, populations, timing and duration, and food matrices; in addition, different analytical methods and biological fluids were analyzed, all variables that affect the final outcome [43]. Furthermore, it is recognized that under normal conditions IsoPs appear in the plasma and urine, and their levels are only amplified by oxidative stress [44,45]. Indeed, several clinical studies that report a significant modulation of IsoPs levels after a specific treatment have been carried out in subjects showing an oxidative stress condition [36,38,46,47,48,49,50,51,52,53]; that is, the reduction of oxidative markers could be significant only if their levels are high at the beginning of the study. In contrast to this, antioxidant supplementation in subjects with a balanced redox state seems to be of little clinical relevance. In the present study we evaluated the degree of urinary excretion of F2-IsoPs pre-intervention and after taking the food supplements only in those subjects with a high level of oxLDL at baseline. Applying this criterion, we found that both dietary supplements significantly reduced the F2-IsoPs level as soon as 0.5 h after the intake ($p \leq 0.05$, mean of differences 1.93 and 2.64 for IP-1 and IP-2, respectively), thus suggesting that subjects with a redox imbalance may benefit from the food supplements’ integration to protect lipids from oxidation. Most of the studies that have evaluated the effects of the intake of olive phenols on the levels of oxLDL and/or F2-IsoPs have been carried out after interventions in the short to medium term. Our previous study [21] showed that HT administered with these watery food supplements is absorbed from the intestinal tract and is rapidly metabolized to phase I and phase II metabolites. The major metabolites of HT (i.e., homovanillic acid, hydroxytyrosol 3-O-sulfate, and 3,4-dihydroxyphenylacetic acid) peaked in the blood at 30 min after intake and were excreted in the urine as early as 30 min and up to 12 h post-intake [21]. We believe that the effects on oxLDL and F2-IsoPs may be directly linked to HT absorption, distribution, metabolism, and excretion. This concept is supported by previous data obtained on the bioavailability of HT administered with these supplements. In fact, the lipoxidation markers correlate with the metabolic products of HT over time. For example, in the blood the oxLDL correlates negatively with the levels of HT-3-glucuronide (significance level < 0.05), and urine levels of entPGF2α correlate negatively with HT-3-sulfate (significance level < 0.05). In addition, we here report for the first time lipoxidation-reducing effects in vivo as early as 30 and 60 min after intake of food supplements containing HT as the main bioactive. ## 4.1. Standards and Reagents Citric acid, phosphoric acid, L(+)-ascorbic acid, 1-butanol, and ethyl acetate were from Roth (Karlsruhe, Germany). Oxidized LDL ELISA kits (Cod: 10-1143-01) were from Mercodia (Uppsala, Sweden). The 9α,11α,15S-trihydroxy-prosta-5Z,13E-dien-1-oic-3,3,4,4-d4acid (PGF2α-d4, CAS 34210-11-2), 9β,11β,15R-trihydroxy-(8β,12α)-prosta-5Z,13E-dien-1-oic acid (ent-PGF2α, CAS 54483-31-7), 9α,11α,15S-trihydroxy-(8β)-prosta-5Z,13E-dien-1-oic acid (8-iso PGF2α, CAS 27415-26-5), and (3Z)-5-[(1S,2R,3R,5S)-3,5-dihydroxy-2-[(1E,3S)-3-hydroxy-1-octen-1-yl]cyclopentyl]-3-pentenoic acid (2,3-dinor-8-isoPGF2α, CAS 221664-05-7) were purchased from Cayman Chemical (Ann Arbor, MI, USA). Formic acid was from Merck (Darmstadt, Germany). LC-MS-grade water and methanol were purchased from VWR Chemicals (Darmstadt, Germany). ## 4.2. Investigational Products (IPs) The liquid food supplements were provided by Fattoria La Vialla S.A.S (Castiglion Fibocchi, Arezzo, Italy). They are derived from olive fruit (*Olea europaea* L.) vegetation water subjected to concentration, reverse osmosis, and filtration; commercial brands are Oliphenolia bitter (IP-1) and Oliphenolia (IP-2). IP-1 consists of a $94\%$ concentrated vegetation water and $6\%$ concentrated lemon juice (Citrus limon L. fructus). IP-2 is composed of $30\%$ further concentrated vegetation water and $70\%$ grape juice (*Vitis vinifera* L. fructus). Quantification of HT and derivatives in the IPs was conducted as previously described [20]. ## 4.3. Study Design The study protocol was approved by the Ethics Committee of the State Medical Association of Rheinland-Pfalz (Mainz, Germany). The clinical study was conducted as set out in the Code of Ethics of the World Medical Association (Declaration of Helsinki) by daacro GmbH & CO at the Science Park Trier (Germany) and is registered at ClinicalTrials.gov (identifier: NCT04876261). The results presented here are secondary outcomes of a study that investigated the bioavailability of HT after acute intake of IP-1 and IP-2 in healthy men, compared with EVOO [21]. The study design was single-blind, randomized, single-dose, three-way cross-over, in which volunteers ingested different concentrations of olive phenolics through a single dose of the corresponding IPs. IPs were orally administrated together with 200 mL of water after an overnight fast of at least 10 h. Water intake was allowed ad libitum, and a controlled basal diet was administered 2 h after intake. ## 4.4. Participants Twelve healthy male volunteers were recruited who met the inclusion and exclusion criteria (age 21–50, BMI > 18.5 < 29.9 kg/m2, nonsmokers, no eating disorder, no drug treatment in the previous or ongoing 2 weeks, no intake of food supplements, and no drug or alcohol abuse). Written informed consent was obtained from all participants prior to starting the trial. Diet indications included to avoid consuming olive-derived products as well as alcohol and supplements with HT, vitamins, minerals, and antioxidants 2–4 days before the first intake and during the whole study. Volunteers underwent a wash-out period of 6 days between the interventions to avoid interference between the IPs. In addition, three days prior to and at each intervention, volunteers avoided moderate or intense physical activity. ## 4.5. Sampling At each intervention visit, a baseline blood sample was collected immediately before the administration of the IP. Further six blood samples were collected 0.5, 1, 1.5, 2, 4, and 12 h after the intake. EDTA-plasma samples were obtained and stored at −80 °C until analysis. At each intervention visit, a baseline urine sample was collected from −240 to 0 min before the administration of the IP. Further six urine samples were collected after the intervention from 0 to 30 min, 30 min to 1 h, 1 to 1.5 h, 1.5 to 2 h, 2 to 4 h, and 4 to 12 h. The total volumes excreted were measured, stabilized with 1.88 g/L of ascorbic acid, and stored at −80 °C until analysis. ## 4.6. Analysis of Plasma oxLDL The plasma samples were thawed at room temperature and immediately quantified for oxLDL with a sandwich ELISA assay according to the manufacturer’s recommendations. Briefly, the sandwich assay uses two monoclonal antibodies against separate antigenic determinants of the oxidized apolipoprotein B molecule. During a first incubation the plasma oxLDL reacts with the capture antibody mAb-4E6. The next steps include incubation with the peroxidase-conjugated secondary anti-human apolipoprotein B antibody, which is detected spectrophotometrically by reaction with 3,3′, 5,5′-tetramethylbenzidine. The oxLDL concentration was recorded in duplicates in a Fluostar OPTIMA reader (BMG Labtech, Offenburg, Germany) and calculated with a five-parameter logistic (5PL) curve and automatic weighting using 1/Y2. The mean values of oxLDL, expressed in units per liter (U/L), were used for the statistical analysis. ## 4.7. Analysis of Urinary F2-IsoPs The isomers 8-isoPGF2α, ent-PGF2α, and 2,3-dinor-8-isoPGF2α were evaluated with UHPLC-DAD-MS/MS following an internal method based on unpublished work. In brief, urine samples were thawed and spiked with aqueous formic acid and PGF2α-d4. Extraction solvent ($5\%$ butanol in ethyl acetate) was added, mixed, and placed in an ice bath for 3 min, followed by centrifugation. The organic phase was collected and evaporated under nitrogen flow. The extraction step was repeated twice. The dry sample was resuspended with methanol and formic acid, filtered through 0.2 µm regenerated cellulose filters (Macherey Nagel, Düren, Germany), and transferred to a new vial. Measurement was conducted with an Acquity UPLC I-Class system coupled to a XEVO-TQS micro mass spectrometer (Waters, Milford, MA, USA) using standard substances as reference. The instrument consisted of a sample manager cooled to 10 °C, a binary pump, a column oven, and a diode array detector. The column oven temperature was set to 40 °C. Eluent A was acetonitrile with $0.1\%$ formic acid, eluent B was water with $0.1\%$ formic acid, and the flow was 0.4 mL/min on an Acquity BEH Shield RP18 column (150 mm × 2.1 mm, 1.7 µm particle size) combined with an Acquity BEH Shield RP18 precolumn (Acquity, 2.1 mm × 5 mm, 1.7 µm), both from Waters (Milford, MA, USA). The gradient started with $30\%$ A and was raised to $80\%$. The peaks were identified with MS/MS. All samples were run in duplicate. Data were acquired and processed using MassLynx 4.1 (Waters, Milford, MA, USA) and normalized by dividing the concentration by the urinary creatinine content in the sample. Mean values of F2-isoP isomers, expressed in µg/g, were used for the statistical analysis. ## 4.8. Data Analysis The average values of concentration for each of the samples were calculated in Microsoft Excel version 16.0. Average values were further processed using GraphPad version 5.00 (San Diego, CA, USA) software to represent in the graphs and table. For the raw statistics, classical statistical methods using median, mean, standard deviation, and confidence intervals were used. Data are expressed as mean ± standard error (SEM) unless otherwise indicated. Student’s paired t-test was performed to compare the results before and after intake of the IPs. ## 5. Conclusions The present study shows that the antioxidant effects of food supplements rich in olive phenolic compounds, and especially in bioavailable HT, are promising for the reduction of lipoxidation in vivo. The oxLDL values significantly decreased by 17.5 ± 1.83 U/L at 1 h after intake. Considering the intervention groups individually, an oxLDL reduction tendency was observed shortly after intake. *In* general, these results support the positive effect of olive phenolics in the reduction of lipoxidation. We further support the finding that antioxidant effects from foods high in antioxidants can be expected most in people with elevated oxidative stress. Indeed, by measuring the F2-IsoPs in urine we showed that in healthy subjects with high oxLDL levels at the beginning of the study, both food supplements significantly lowered the excretion of F2-IsoPs at 0.5 h post-intervention, remaining low until 12 h. Overall, the results obtained indicate the efficacy of both the food supplements to reduce the level of lipoxidation shortly after intake, which is a valuable aid to prevent and combat oxidative damage in the organism. Findings from the study warrant further research for the use of these HT-rich food supplements in personalized nutrition. ## References 1. 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--- title: 'The Prognostic Role of Spot Urinary Sodium and Chloride in a Cohort of Hospitalized Advanced Heart Failure Patients: A Pilot Study' authors: - Andrew Xanthopoulos - Charalambos Christofidis - Chris Pantsios - Dimitrios Magouliotis - Angeliki Bourazana - Ioannis Leventis - Niki Skopeliti - Evangelia Skoularigki - Alexandros Briasoulis - Grigorios Giamouzis - Filippos Triposkiadis - John Skoularigis journal: Life year: 2023 pmcid: PMC10054455 doi: 10.3390/life13030698 license: CC BY 4.0 --- # The Prognostic Role of Spot Urinary Sodium and Chloride in a Cohort of Hospitalized Advanced Heart Failure Patients: A Pilot Study ## Abstract Recent studies have demonstrated the prognostic value of spot urinary sodium (UNa+) in acutely decompensated chronic HF (ADCHF) patients. However, data on the prognostic role of UNa+ and spot urinary chloride (UCl−) in patients with advanced HF are limited. In the present prospective pilot study, we examined the predictive value of UNa+ and UCl− concentration at baseline, at 2 h and at 24 h after admission for all-cause mortality and HF rehospitalization up to 3 months post-discharge. Consecutive advanced HF patients ($$n = 30$$) admitted with ADCHF and aged > 18 years were included in the study. Loop diuretics were administered based on the natriuresis-guided algorithm recommended by the recent HF guidelines. Exclusion criteria were cardiogenic shock, acute coronary syndrome, estimated glomerular filtration rate < 15 mL/min/1.73 m2, severe hepatic dysfunction (Child–Pugh category C), and sepsis. UNa+ at baseline (Area Under the Curve (AUC) = 0.75, $95\%$ Confidence Interval (CI) (0.58–0.93), $$p \leq 0.019$$) and at 2 h after admission (AUC = 0.80, $95\%$ CI: 0.64–0.96, $$p \leq 0.005$$) showed good and excellent discrimination, respectively. UCl− at 2 h after admission (AUC = 0.75, $95\%$CI (0.57–0.93), $$p \leq 0.017$$) demonstrated good discrimination. In the multivariate logistic regression analysis, UNa+ at 2 h ($$p \leq 0.02$$) and dose of loop diuretics at admission ($$p \leq 0.03$$) were the only factors independently associated with the study outcome. In conclusion, UNa+ and UCl− may have a prognostic role in hospitalized advanced HF patients. ## 1. Introduction Acute heart failure (AHF) refers to the rapid or gradual onset of symptoms and/or signs of HF, severe enough for the patient to seek urgent medical intervention, leading to an unplanned hospital admission or an emergency department presentation [1]. Congestion, a typical finding in acute decompensated chronic HF (ADCHF), refers to signs and symptoms of extracellular fluid accumulation that result in increased cardiac filling pressures [2]. Since sodium (Na+) and water retention in the extracellular space are responsible for the increase in venous return and cardiac filling pressures, intravenous loop diuretics are used to ameliorate symptoms of fluid overload in patients with ADCHF [3,4]. In particular, loop diuretics inhibit the Na+-K+-2Cl− symporter at the ascending loop of Henle and have the most potent diuretic effect, promoting the excretion of Na+ and chloride (Cl−) [5,6]. Therefore, not surprisingly, loop diuretics form the backbone of diuretic therapy in ADCHF, being used in over $90\%$ of patients [7]. Traditionally, the estimation of decongestion is based on the findings from the clinical examination (symptoms and/or signs), urine output, weight loss, blood levels of natriuretic peptides and renal function (i.e., creatinine/urea), which is not optimal [8,9]. According to the latest guidelines, the dose of intravenous loop diuretics should be adjusted based on the spot urinary Na+ (UNa+) concentration (natriuresis-guided treatment) in order to be achieved timely and successful decongestion [1]. It has been reported that early treatment with intravenous loop diuretics is associated with lower in-hospital mortality in AHF [10]. In this regard, a number of recent studies have demonstrated the prognostic value of UNa+ concentration in patients presenting in the emergency department (ED) with ADCHF [9,11,12,13,14], while less is known about the spot urinary chloride (UCl−) [15,16]. Nevertheless, data on the role of UNa+ and UCl− concentration in advanced HF patients, a population of HF patients who exhibit frequent rehospitalizations and poor survival, are limited [17,18]. Furthermore, the appropriate use of diuretics in advanced HF remains challenging since those patients frequently have low blood pressure, deteriorating renal function, diuretic resistance and electrolyte disturbances. Starting from the idea that the early risk stratification of advanced HF patients may result in better classification of those patients, timely administration of decongestive therapies and improved outcomes, the present pilot study investigated the prognostic value of spot urinary electrolytes (Na+ and Cl−), at various time points (i.e., at admission before the administration of loop diuretics, at 2 and 24 h after the administration of diuretics) and their association with unfavorable clinical events in a small cohort of advanced HF patients hospitalized for ADCHF. ## 2.1. Study Population Consecutive patients hospitalized for ADCHF in a tertiary University Hospital from 15 September 2022 to 15 November 2022 and aged > 18 years were included in the study. Exclusion criteria were cardiogenic shock, acute coronary syndrome, estimated glomerular filtration rate < 15 mL/min/1.73 m2, severe hepatic dysfunction (Child–Pugh category C), and sepsis (Figure 1). All patients enrolled were on a natriuresis-guided algorithm recommended by the recent HF guidelines [1]. UNa+ and UCl− were collected at baseline (before the administration of loop diuretics) with the use of urine catheter, at 2 h after the loop diuretic administration (2 h after admission) and thereafter at various time points during hospitalization based on the abovementioned algorithm. The evaluation of the patients at admission included clinical assessment, laboratory blood and urine tests, as well as echocardiography. UNa+ and UCl− were measured with the use of the Roche Hitachi cobas 8000 (cobas ISE) on samples obtained at different time points of hospitalization. N-terminal pro-b-type natriuretic peptide (NT-proBNP) was measured with the use of Radiometer’s AQT90 FLEX immunoassay analyzer, while blood gas with GEM PREMIER 3000 Analyzer (Instrumentation Laboratory). Blood tests were measured with the use of the Roche Hitachi cobas 8000 (cobas c 702) on samples obtained for standard-of-care evaluation. Finally, echocardiography was performed within 1 h after admission in accordance with current recommendations, with the use of eSaote MyLabX6 echo machine [19]. The left ventricular ejection fraction (LVEF) was calculated with the use of two-dimensional echocardiography by implementing the biplane method of disks summation technique [19]. The loop diuretic used in the present study was furosemide. This study conformed to the principles outlined in the Declaration of Helsinki and was approved by the Ethics Committee of the University of Thessaly (protocol code: 349). All patients provided written informed consent. ## 2.2. Definitions Advanced HF was defined based on the following criteria despite optimal medical treatment [1]:Severe and persistent symptoms of HF [NYHA class III (advanced) or IV] within the last 6 months;LVEF ≤ $30\%$;Persistently high (or increasing) BNP or NT-proBNP values and severe left ventricular diastolic dysfunction or structural abnormalities;Episodes of pulmonary or systemic congestion requiring high-dose i.v. diuretics (or diuretic combinations) or episodes of low output requiring inotropes or vasoactive drugs or malignant arrhythmias causing >1 unplanned visit or hospitalization in the last 12 months. If chronic HF deteriorates, either suddenly or slowly, the episode may be described as ‘decompensated’ HF. This can result in hospital admission [1]. HF hospitalization was defined as a hospitalization requiring at least an overnight stay in hospital caused by onset or substantive worsening of HF symptoms and/or signs requiring the augmentation (an increase in the dose or frequency of administration) of oral medications or new administration of intravenous (IV) HF therapy, including inotropes, diuretics or vasodilators [20] ## 2.3. Outcomes The study outcome combined all-cause mortality and/or HF rehospitalization. The study follow-up was 3 months post-discharge. ## 2.4. Statistical Analysis The normality of the data was assessed using D’Agostino–Pearson test. A two-tailed unpaired t-test and Mann–Whitney U-test were performed for parametric and nonparametric continuous data, respectively. A chi-square test was performed for categorical variables. We assessed the discrimination (i.e., the ability to separate those who did from those who did not die/rehospitalized) of the urine electrolytes (Na+ and Cl−) at baseline, after 2 and 24 h. Discrimination was assessed by generating receiver-operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The AUC was determined by calculating the $95\%$ confidence intervals and compared using nonparametric paired tests, as described by DeLong et al. [ 21]. We defined poor, good and excellent model discrimination with the AUC of <0.70, 0.70–0.79 and 0.80–1.00, respectively [21]. Repeated measures analysis of variance (ANOVA) was conducted in order to explore the changes in Na and CL over the follow-up period. Bonferroni correction was used for the pairwise time comparisons. A logistic regression analysis was performed for the events. In order to find factors independently associated with prognosis, multiple logistic regression was conducted in a stepwise manner with all-cause mortality or HF rehospitalization at 3 months as dependent variable. Differences were considered significant (rejection of the null hypothesis) with a $p \leq 0.05.$ *All data* were analyzed using Microsoft® Excel 365 16.66.1 (Microsoft, Redmond, Washington, DC, USA) and Prism® Graphpad 9.5.0 for Mac (GraphPad Software, San Diego, CA, USA) as well as SPSS 28 (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY, USA: IBM Corp) ## 3.1. Baseline Characteristics The characteristics of the study population are presented in Table 1. The cohort consisted of elderly patients (mean age 73 years), whereas half of them ($$n = 15$$, $50\%$) were females. The majority ($70\%$) of patients were in New York Heart Association (NYHA) III, while the rest were in NYHA IV, and the mean NT-proBNP was approximately 13,320 pg/mL, mirroring the advanced stages of HF. Renal function was mildly to moderately impaired, whereas hematocrit, hemoglobin and blood electrolytes were within the normal range. The mean baseline left ventricular ejection fraction was low ($37.3\%$), and the inferior vena cava was dilated (24 mm). Regarding medical treatment, the majority of patients were on β-blockers and loop diuretics, whereas approximately half of them were on ACE inhibitors/ARBs, ARNis or MRAs. The box plots of UNa+ and UCl− and the urine output at various time points are depicted in Figure 2, Figure 3 and Figure S1, respectively. UNa+ and UCl− had significant changes over the follow-up period (PANOVA < 0.001). More specifically, after Bonferroni correction, it was found that at 2 h, both UNa+ and UCl− were higher compared to their values at admission ($p \leq 0.001$ and $p \leq 0.001$, respectively) and at 24 h ($$p \leq 0.020$$ and $$p \leq 0.050$$, respectively). ## 3.2. Study Outcomes The combined study outcome (all-cause death and HF rehospitalization) was met in 15 ($50\%$) patients during the study follow-up. UNa+ at baseline (area under the curve (AUC) = 0.75, $95\%$ Confidence Interval (CI) (0.58–0.93), $$p \leq 0.019$$) and at 2 h after loop diuretic administration (AUC = 0.80, $95\%$ CI (0.64–0.96), $$p \leq 0.005$$) showed good and excellent discrimination, respectively (Figure 4). On the contrary, UNa+ at 24 h was not of prognostic value (AUC 0.74, $95\%$CI (0.50–0.97), $$p \leq 0.056$$) (Figure S2). Interestingly, the optimal cut-off value for the admission UNa+ was ≤49 meq/L, with $73.3\%$ sensitivity and $66.7\%$ specificity. Patients with UNa+ ≤ 49 meq/L exhibited 5.5 times higher risk for the study outcome compared to those with UNa+ > 49 meq/L (Odds Ratio = 5.50, $95\%$ CI (1.15–26.41), $$p \leq 0.033$$). The optimal cut-off value for the UNa+ at 2 h was ≤95.5 meq/L, with $73.3\%$ sensitivity and $73.3\%$ specificity. Patients with UNa+ at 2 h ≤95.5 had 7.56 times higher risk of all-cause mortality or HF rehospitalization compared to those with UNa+ at 2 h >95.5 meq/L (Odds Ratio = 7.56, $95\%$ CI (1.50–38.15), $$p \leq 0.014$$). UCl− at 2 h after admission (AUC = 0.76, $95\%$CI (0.58–0.94), $$p \leq 0.017$$) demonstrated good discrimination (Figure 4). The optimal cut-off value for the UCl− at 2 h was ≤99.8 meq/L, with $86.7\%$ sensitivity and $66.7\%$ specificity. Patients with UCl− at 2 h ≤ 99.8 meq/L had 13 times higher odds for all-cause mortality or HF rehospitalization compared to those with UCl− at 2 h >99.8 meq/L (Odds Ratio = 13, $95\%$ CI (2.08–81.48), $$p \leq 0.006$$). On the contrary, UCl− at baseline (AUC 0.69, $95\%$ CI (0.49–0.89), $$p \leq 0.081$$) and at 24 h (AUC 0.66, $95\%$ CI (0.43–0.90), $$p \leq 0.193$$) was not of prognostic significance (Figure 4 and Figure S3). The homoscedasticity plots are shown in Figures S4 and S5. A univariate logistic regression analysis revealed the factors that were associated with the study outcome (Table 2). These were the UNa+ at admission ($$p \leq 0.02$$) and at 2 h ($$p \leq 0.01$$), the UCl− at 2 h ($$p \leq 0.02$$), urine output at 6 h ($$p \leq 0.01$$) and the dose of loop diuretic at admission ($$p \leq 0.01$$). The multivariate logistic regression analysis, in a stepwise manner, revealed that UNa+ at 2 h and loop diuretic dose at admission were the only independent factors for the study outcome (Table 3). ## 4. Discussion The current study is the first to provide concurrent insight into the predictive value of UNa+ and UCl− as a response to diuretic treatment in advanced decompensated hospitalized HF patients who were on the natriuresis-guided therapy algorithm. Main findings may include the following [1] UNa+ at baseline showed good discrimination, [2] UNa+ 2 h after admission demonstrated excellent discrimination and was independently associated with the study outcome, [3] UCl− at 2 h after admission demonstrated good discrimination for the combined outcome of all-cause mortality and rehospitalization during the follow up (3 months) for hospitalized patients with advanced HF, [4] UNa+ and UCl− at 2 h after the administration of iv loop diuretics were both significantly higher compared to their values at admission. There is increasing evidence that higher urinary Na+ concentration during treatment for acute HF is related to a better prognosis, higher possibility of achieving euvolemia and shorter hospitalizations [11,22]. However, few data are available for Na+ excretion during an acute decompensation of patients with advanced HF. The present study attempted to highlight the significance of electrolyte status and associated neurohormonal activation in the fragile advanced HF patient. In particular, it showed that the administration of high-dose loop diuretics at admission (mean dose of furosemide 118.0 mg) led to significant UNa+ and UCl− increase at 2 h, compared to their baseline values. Diuretic resistance (a failure to increase fluid and Na+ output sufficiently to relieve volume overload despite escalating doses of a loop diuretic) is a frequent finding among advanced HF patients and it is associated with poor prognosis [23,24]. Therefore, timely identification (with the use of spot urine electrolytes) of patients with the highest risk of HF rehospitalization and death may lead to earlier and more intense decongestive therapy and better outcomes. There is evidence that the assessment of UNa+ concentration in acute HF is a more accurate prognostic marker than urine output. Interestingly, in the present study, urine output collected at 6 and 24 h after admission was not associated independently with the study outcomes. So far, Testani et al. demonstrated that UNa+ at 1–2 h corresponds to the total Na+ concentration in a 6-h urine collection, allowing for a prompt assessment of response to diuretic treatment and individualized titration [25]. Similarly, Collins et al. underscored the predicting utility of early evaluation of natriuresis (total urine Na+), 1 h after diuretic administration, in correspondence to the clinical outcome of in-hospital worsening HF [12]. Our protocol included assessment of baseline urine Na+ (at admission) as well as evaluation at the predetermined point of 2 h after the loading dose of diuretics. It is one of few studies to evaluate baseline levels of urinary Na+ as well as early Na+ excretion, both demonstrating efficacy as discriminating factors. The good prognostic ability of low levels of baseline urinary Na+ comes in agreement with a previous study by Martens et al. that underscored low levels of urinary Na+ in chronic HF patients as a means of foreseeing acute decompensation [26]. To our concern, so far, only one prospective study concerning UNa+ and response to diuretic treatment in advanced HF was conducted, however, including only ambulatory HF patients in a short surveillance time. Spot urine samples were obtained at first voided urine after loading dose of diuretics and compared to total urine output at three hours, and the values were correlated to 30-day hospitalization or emergency department visit. Specifically, a cut-off of 65 mmol/h and a urine output of less than 1200 mL were associated with $69\%$ rate of hospitalization in 30 days [17]. Our study included patients with decompensated advanced HF, and urinary Na+ was evaluated at admission and at 2 h and 24 h after administration of loop diuretics. Insertion of the urinary catheter at all patients at admission in our protocol and subsequent evaluation of UNa+ at 2 h excluded the possibility of pre-diuretic residual urine, yet differentiating it from the aforementioned study. It could be anticipated that linear UNa+ excretion in advanced HF patients, who typically come up with longer hospitalizations, would correlate to clinical outcome, duration of efficient decongestion and mortality. Nevertheless, UNa+ at 24 h failed to demonstrate a further discrimination value (AUC = 0.74, $$p \leq 0.056$$), reinforcing the position that timely and tailored administration of loop diuretics is of utmost importance regarding all-cause mortality and rehospitalizations for advanced HF patients. This observation fills a knowledge gap, as data on advanced HF natriuresis is scarce due to a lack of studies, and emphasizes the value of prompt optimal dosing. Interestingly, UNa+ at 2 h and initial diuretic dose administration were the only independent factors for the study outcome. The evaluation of UNa+ as a biomarker of response to HF treatment has been gaining ground in the last few years [4]. In the present study, we attempted to evaluate the excretion of electrolytes in a critically ill patient with advanced HF. Taking into consideration that conventional markers such as glomerular filtration rate (GFR) or NT-proBNP have failed to correspond to acute HF outcome, we purposely attempted to incorporate a biomarker that correlates to water and extracellular volume handling without being affected by glomerular function, which may be variously aggravated in advanced HF patients. In the present study, both markers of renal function (i.e., urea and creatinine), as well as NT-proBNP, were not associated with the study outcome. While longitudinal profiles of UNa+ in hospitalized HF patients have been evaluated, little is currently known concerning the prognostic significance of UCl− [14,27]. Cl− is among the key electrolytes that participate in fluid homeostasis. Although so far neglected, Cl− is the main regulator of the macula densa, the region of renal juxtaglomerular apparatus that senses NaCl and fluid status [28,29]. It should be emphasized that the action of Cl− on the lately detected with-no-lysine (K)- WNK protein kinase evolves in enhanced water and electrolytes reabsorption via upregulation of the Na+-K+-Cl− cotransporter, possibly elucidating a mechanism of diuretic resistance in HF [30]. Our study shows for the first time that UCl− derived soon after loop diuretic administration can discriminate patients with advanced HF at high risk for ominous clinical outcomes. Specifically, a cut-off value of ≤99.8 meq/L distinguished patients with 13 times higher odds of all-cause mortality or HF rehospitalization in 3 months. Our findings are in agreement with a recent small study highlighting serum and urine Cl− indices as an even better estimator of neurohormonal activation than Na+ indices in acute HF, correlating firmly to plasma renin activity [31]. Sodium–glucose co-transporter-2 inhibitors (SGLT-2) inhibitors, a novel drug class, inhibit the SGLT-2 receptors predominantly expressed in the proximal tubule of the nephron; thus, they induce glycosuria and natriuresis and have been shown to reduce the combined endpoint of all-cause mortality and HF rehospitalization in chronic HF patients irrespective of the LVEF [32,33,34,35,36]. However, recent studies revealed that these drugs might also be beneficial in hospitalized HF patients. In particular, the EMPA-RESPONSE-AHF study showed that the SGLT-2 inhibitor empagliflozin was safe, increased urinary output and reduced a combined endpoint of worsening HF, rehospitalization for HF or death at 60 days, compared to placebo [37]. Furthermore, the randomized EMPULSE demonstrated that more patients treated with empagliflozin had a clinical benefit compared with placebo (stratified win ratio, 1.36; $$p \leq 0.0054$$), meeting the primary endpoint (a hierarchical composite of all-cause death, number of HF events and time to first HF event, or a 5 point or greater difference in change from baseline in the Kansas City Cardiomyopathy Questionnaire Total Symptom Score at 90 days) [38]. Nevertheless, an interesting recent meta-analysis of two observational and six randomized studies reported conflicting results concerning the true efficacy of SGLT-2 inhibitors in acute HF patients, including “hard” surrogate endpoints [32]. Whether the UNa+ can be used as a prognostic marker and its potential cut-off values in patients already receiving SGLT-2 inhibitors needs to be investigated in future studies. Interestingly, in the present pilot study, $16.7\%$ of patients were on SGLT-2 inhibitors at admission. All patients enrolled in the present study were on a natriuresis-guided therapy algorithm. In other words, the administration of loop diuretics, as well as their dosage, was based on the UNa+ values [1,5]. Interestingly, the pragmatic urinary sodium-based treatment algoritHm in acute heart failure (PUSH-AHF) trial will reveal whether natriuresis-guided therapy, using a pre-specified stepwise diuretic treatment approach, improves natriuresis and clinical outcomes in patients with acute HF [39]. From the perspective of the clinician, a two-dimensional, contemporaneous assessment with two biomarkers (UNa+ and UCl−) that both demonstrate a good discriminatory ability can minimize the possibility of a random finding while being timesaving and easily obtainable. Patients with advanced HF have different characteristics from those of the ADCHF population [40,41,42]. For example, an analysis from the Acute Decompensated Heart Failure National Registry (ADHERE) revealed that patients with advanced HF tended to be younger (69.6 vs. 72.8 years), were more often males ($65\%$ vs. $49\%$) and were more likely to have hyperlipidemia/dyslipidemia ($65\%$ vs. $41\%$) and coronary artery disease ($73\%$ vs. $57\%$) compared to those with ADCHF [40]. Furthermore, in patients with advanced HF, symptoms appear to be more related to fatigue and less to fluid status/volume overload than in patients with ADCHF [40]. Lastly, a patient with advanced HF may often exhibit episodes of ADCHF, but not all patients with ADCHF have advanced HF. ## 5. Study Limitations This study has some limitations: (a) The present work was a non-randomized, single-center study, and therefore, the risk of bias and confounding cannot be excluded, despite multiple adjustments. However, the current study was prospective in nature, and the main advantage of prospective over retrospective cohort and case-control studies is that baseline exposure status is correctly assessed, not only recalled, reducing the risk of selection bias [43]. Furthermore, all patients were on the same natriuresis-guided therapy. ( b) The number of patients enrolled was relatively small; however, the present was a pilot study, patients were closely monitored, and none was lost during follow-up. ( c) Currently, there is no universal definition of advanced HF [44]. In the present work, advanced HF was defined based on recent guidelines [1]. Lastly, only $16.7\%$ of patients were on SGLT-2 inhibitors at admission, mirroring the currently low global prescription rate of this drug category in HF populations [45,46,47]. ## 6. Conclusions Recent studies have reported the prognostic value of UNa+ in ADCHF patients, while less is known about the role of UCl− in the same population of patients. The present pilot work adds to the existing literature by demonstrating that UNa+ and UCl− may predict the combined short-term outcome of all-cause mortality and HF rehospitalization in a small cohort of hospitalized advanced HF patients who followed the same loop diuretic treatment algorithm. UNa+ at 2 h after admission was associated independently with prognosis. Whether early risk stratification of advanced HF patients with the use of UNa+ and UCl− leads to better outcomes needs to be elucidated in the future. Larger studies are urgently needed. ## References 1. McDonagh T.A., Metra M., Adamo M., Gardner R.S., Baumbach A., Bohm M., Burri H., Butler J., Celutkiene J., Chioncel O.. **2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure**. *Eur. Heart J.* (2021) **42** 3599-3726. DOI: 10.1093/eurheartj/ehab368 2. Martens P., Nijst P., Mullens W.. **Current Approach to Decongestive Therapy in Acute Heart Failure**. *Curr. 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--- title: Continuous Production of Dietetic Structured Lipids Using Crude Acidic Olive Pomace Oils authors: - Joana Souza-Gonçalves - Arsénio Fialho - Cleide M. F. Soares - Natália M. Osório - Suzana Ferreira-Dias journal: Molecules year: 2023 pmcid: PMC10054457 doi: 10.3390/molecules28062637 license: CC BY 4.0 --- # Continuous Production of Dietetic Structured Lipids Using Crude Acidic Olive Pomace Oils ## Abstract Crude olive pomace oil (OPO) is a by-product of olive oil extraction. In this study, low-calorie structured triacylglycerols (TAGs) were produced by acidolysis of crude OPO with medium-chain fatty acids (caprylic, C8:0; capric, C10:0) or interesterification with their ethyl ester forms (C8EE, C10EE). These new TAGs present long-chain fatty acids (L) at position sn-2 and medium-chain fatty acids (M) at positions sn-1,3 (MLM). Crude OPO exhibited a high acidity (12.05–$28.75\%$ free fatty acids), and high contents of chlorophylls and oxidation products. Reactions were carried out continuously in a packed-bed bioreactor for 70 h, using sn-1,3 regioselective commercial immobilized lipases (*Thermomyces lanuginosus* lipase, Lipozyme TL IM; and Rhizomucor miehei lipase, Lipozyme RM IM), in solvent-free media at 40 °C. Lipozyme RM IM presented a higher affinity for C10:0 and C10EE. Lipozyme TL IM preferred C10:0 over C8:0 but C8EE over C10EE. Both biocatalysts showed a high activity and operational stability and were not affected by OPO acidity. The New TAG yields ranged 30–60 and the specific productivity ranged 0.96–1.87 g NewTAG/h.g biocatalyst. Lipozyme RM IM cost is more than seven-fold the Lipozyme TL IM cost. Therefore, using Lipozyme TL IM and crude acidic OPO in a continuous bioreactor will contribute to process sustainability for structured lipid production by lowering the cost of the biocatalyst and avoiding oil refining. ## 1. Introduction Lipids are considered to be the main source of energy, essential fatty acids, vitamins and antioxidants. Some of them can be classified as functional foods, as is the case of virgin olive oil. Olive oil is recognized as one of the major fat sources in the Mediterranean diet. According to the data from the International Olive Council (IOC), the world production of olive oil reached 3099 kton in the crop year $\frac{2021}{2022}$ (provisional values), $64\%$ of it produced in the European Union (1983 ktons), with Portugal being the fourth producer and consumer in Europe [1]. Unexploited agro-industrial residues are a worldwide major concern in terms of environmental problems. Therefore, valorizing the by-products that result from olive processing is important. The olive pomace is obtained after olive oil extraction by mechanical processes. This residue still contains about 3–$4.5\%$ (wet basis) of residual oil, known as olive pomace oil, with a composition similar to that of olive oil [2]. From the most recent world statistics on olive oil, ca. 4.716 billion tons of dry olive pomace containing 282.960 kton of crude olive pomace oil are estimated to be obtained every year. Oils obtained from agro-food residues and waste (e.g., grapeseed, olive pomace, and spent coffee grounds oils) can be used as raw materials to produce structured lipids (SLs) [3,4,5]. The direct use of crude oils is a viable option because the sustainability of the process will greatly increase since the refining process of the oil is not needed. SLs are modified lipids (fats and/or oils) that do not exist in nature, presenting improved technological, functional, and/or pharmaceutical properties. SLs are currently defined as triacylglycerols (TAGs) or phospholipids that have been (i) modified by the incorporation of new fatty acids (FAs), (ii) restructured to change the positions of FAs or the fatty acid (FA) profile, from the natural state, or (iii) synthesized to yield novel TAGs (or phospholipids), either chemically or enzymatically [6,7,8]. Functionality, physical properties, metabolic fate, and health benefits associated with lipids depend on FA composition of TAGs and FA distribution on the TAG glycerol backbone. Different types of SLs, namely, modified fat blends to obtain adequate rheological properties for margarine and shortening manufacture, oils enriched in omega-3 polyunsaturated fatty acids (omega-3 PUFA), cocoa butter equivalents, human milk fat substitutes and dietetic SLs, and respective properties have been described in several reviews [6,7,8,9,10,11,12]. In the food industry (e.g., margarine and shortenings plants), plastic fats have been obtained by interesterification of fat blends currently carried out using non-regioselective chemical catalysts, acting under reduced pressure, and at temperatures up to 270 °C. The equilibrium is achieved in less than 2 h of reaction [13]. The enzymatic interesterification of fat blends has also been performed, batch-wise or in continuous packed-bed or fluidized-bed bioreactors, to obtain modified trans-free fat blends for margarine and shortenings, rich in specific fatty acids [14,15,16,17,18,19,20,21]. Xie and Zang performed the enzymatic modification of the following vegetable oils to produce trans-free plastic fats: (i) soybean oil by interesterification with lard [17] and with methyl stearate or palm stearin [18], and (ii) rice bran oil, by interesterification with palm stearin [19]. When non-regioselective lipases are used, they act at random in the TAG backbone and the obtained products present a similar composition to those obtained by chemical interesterification [14,17,18,19]. The enzymatic interesterification using non-regioselective biocatalysts is a low energy consumption process because a lower reaction temperature is used. The use of methyl esters [18] as acyl donors should be avoided since methanol will be released in the reaction. Methanol is not allowed in food products and may inactivate the lipase during the reactions [22]. The interesterification of palm olein alone [20] or with lard [21] was carried out in a solvent-free stirred tank or a packed-bed bioreactor, respectively, using immobilized sn-1,3 regioselective *Thermomyces lanuginosus* lipase (Lipozyme TL IM) as a catalyst. The use of sn-1,3 regioselective lipases will allow the maintenance of long-chain mono- or polyunsaturated fatty acids at position sn-2 in TAGs. This is of utmost nutritional importance since long-chain unsaturated fatty acids, namely, the essential fatty acids, are better absorbed by the human body in the form of sn-2 monoacylglycerols [23]. Among SLs, dietetic structured lipids, also known as low-calorie TAGs, are a type of lipid containing a specific combination of medium-chain fatty acids (M) at positions sn-1 and sn-3, and a long-chain fatty acid (L) at position sn-2 (MLM). In vegetable oils, mono- and polyunsaturated long-chain fatty acids, namely, essential FAs, are preferentially located at position sn-2. Medium-chain fatty acids have lower caloric value than long-chain FAs and are metabolized in the liver like glucose, and not accumulated as fat in the human body. Therefore, MLM SLs will provide the essential FAs for the humans and, at the same time, will contribute to obesity control due to their lower caloric value than that of natural fats (ca 5 kcal/g against 9 kcal/g natural fats) [11,12]. These properties make MLM useful for reducing the possibility of obesity and promoting proper body function. There are several lipids in the market, containing medium-chain FAs, for nutritional and pharmaceutical purposes. The company Stepan Lipid Nutrition commercializes medium-chain TAGs as energy source for people with malabsorption syndrome and for several food and pharmaceutical applications, due to their low-calorie content [24]. These products (with the trade name NEOBEE) are obtained by the esterification of glycerol with mixtures of caprylic and capric acids, obtained by fractionation of palm kernel and coconut fats. Similar products (CAPTEX 300 and CAPTEX 355) are commercialized by ABITEC Company [25]. However, these TAG products do not have long-chain FAs, which are very important for human nutrition. To overcome this problem, other TAGs containing medium- and long-chain FAs are already in the market. For example, in 2003, Benefat (or Salatrim: abbreviation of “Short- and long-chain acyl triglyceride molecule”) was approved by the EU as a low-calorie alternative to natural oils and fats. This product, consisting of blends of TAGs containing medium- and long-chain fatty acids, was launched by Danisco and is used in confectionery, bakery, and dairy products [26]. Interesterification and acidolysis are the most common methods used for the production of low-calorie SLs, characterized by the use of ethyl/methyl esters or free fatty acids (FFA) as acyl donors in the reaction, respectively. Since the use of chemical catalysts does not allow a specific action, their replacement by biocatalysts has been increasing. In this sense, the use of sn-1, 3 regioselective lipases is mandatory since they cut FAs only at positions sn-1 and sn-3 of TAGs and produce lipids with unique structures and characteristics. The synthesis of SLs by immobilized enzymes in solid carriers can be performed in batch or in continuous bioreactors, either in the presence of an organic solvent or in solvent-free media. At laboratory scale, batch stirred tank reactors (BSTR) have been currently used. BSTR can be a good option if the support particles are not damaged by shear forces. This configuration is adequate to situations of substrate inhibition. However, for process implementation in continuous mode, packed (PBR) or fluidized-bed (FBR) tubular bioreactors are preferred to completely stirred tank reactors. Continuous PBR are the most adequate reactors to repress acyl-migration, due to shorter residence times needed [15,27,28]. Fluidized-bed reactors allow for high mass transfer rates and low shear stress for the immobilized biocatalyst particles [14,29]. Lipozyme TL IM (immobilized lipase from Thermomyces lanuginosus) and Lipozyme RM IM (immobilized lipase from Rhizomucor miehei) are examples of commercial enzymes immobilized on silica gel and microporous anion exchange resin, respectively. Given the lack of mechanical resistance to stirring usually applied to batch mode, easy desorption, or enzyme leakage from the support during batch reuse, Lipozyme TL IM is not adequate for use in this type of bioreactor [30]. Apart from the reuse in batch mode, this type of bioreactor has lower costs, although it is difficult to control heat transfer. In continuous bioreactors, it is possible to decrease the costs associated with enzymatic processes. Several oils rich in long-chain FAs have been used to produce low-calorie structured lipids either by acidolysis or interesterification reaction, in batch stirred bioreactors (e.g., olive, olive pomace, linseed, spent coffee grains, grapeseed, avocado, or microbial oils), catalyzed by sn-1,3-regioselective lipases [3,4,5,31,32,33,34,35,36]. A batch packed-bed reactor of Lipozyme TL IM, working under continuous recirculation mode, was successfully used to obtain oil blends rich in medium- and long-chain TAGs by interesterification of soybean oil with TAGs rich in caprylic and capric acids [37]. The implementation of enzymatic synthesis of MLM in continuous PBR with commercial immobilized Rizomucor miehei lipase (Lipozyme IM) was carried out by Xu et al. [ 28]. In this study, SLs were obtained by the (i) acidolysis of refined rapeseed oil with capric acid or safflower oil with caprylic acid or (ii) interesterification between medium-chain TAGs and oleic acid, in a solvent-free system. In continuous mode, the biocatalyst maintained $60\%$ of the initial activity after a 4-week continuous operation. Lipozyme TL IM was also used in a continuous PBR for the interesterification between medium-chain TAGs and fish oil, in the absence of organic solvent [28]. In this system, the activity of Lipozyme TL IM was maintained along a 2-week operation. Previous studies were performed by our group to valorize crude OPO as feedstock for the production of SLs, by batch interesterification of crude acidic olive pomace oils with caprylic and capric acids, or their ethyl esters, in solvent-free media. In these studies, *Rhizopus oryzae* lipase immobilized in magnetic nanoparticles or commercial immobilized lipases (Lipozyme RM IM and Lipozyme TL IM) were used as biocatalysts [4,38]. However, according to our knowledge, the production of these SLs with crude olive pomace oil, in continuous bioreactors, has not been studied yet. Therefore, the aim of the present study was to implement the lipase-catalyzed production of structured lipids with low calorie value, in continuous packed-bed bioreactor, with known advantages in terms of process scale-up, using crude OPO. The direct use of crude high acidic oil, instead of refined oil, will be an important contribution to decrease production costs and make the process economically feasible. Moreover, due to the low mechanical resistance of Lipozyme TL IM, its use in a continuous packed-bed reactor may be an option to preserve biocatalyst integrity. Acidolysis reactions with capric and caprylic acid or interesterification with the respective ethyl esters were performed. Studies related to specific productivities and costs based on experimental data can promote the possibility of developing scale-up activities and their application in bioindustries. ## 2.1. Crude Olive Pomace Oil Characterization All crude olive pomace oil (OPO) samples were centrifuged to remove most of the impurities prior to analysis and their use as a reaction substrate. Table 1 shows the chemical characterization of OPO samples, namely, acidity, UV absorbance (K232 and K270), chlorophyll pigments, and fatty acid composition. In terms of oil quality, the acidity consists of the amount of FFA released by the hydrolysis of TAGs. All crude oil samples presented high acidity: $12.05\%$ (OPO-1), $15.06\%$ (OPO-2), and $28.75\%$ (OPO-3). The oxidation products are also related with the quality of oils. Each absorbance at 232 nm and 270 nm are provided by the specific extinction coefficient (K232: indicator of the presence of initial products of oxidation; K270: indicator of the presence of final oxidation products) [39]. The results for all OPO are considered high (about $K = 5$), which suggests a high oxidation stage. The increase in acidity and K values, from OPO-1 to OPO-3, may be related to the storage conditions of olive pomace before oil extraction, promoting hydrolysis and oxidation processes of TAGs. In fact, in this study, the OPO oils were solvent-extracted from olive pomaces obtained in two-phase continuous olive oil decanters. These pomaces are very rich in water (ca. $70\%$). Along olive oil extraction (Autumn/Winter; October–December in the northern hemisphere), the pomaces are currently discarded in large open-air ponds, where they can stay for months until the oil is extracted. These conditions promote the hydrolysis and oxidation of the oil, among other degradation reactions. The presence of oxidation products in the oils has been related to an inhibitory effect on lipase activity [15]. Chlorophyll pigments are responsible for the green color intensity of olives. There is no defined limit for the measurement of chlorophyll pigments in OPO. Chlorophyll pigment values varied from 367.0 to 447.5 mg of pheophytin a per kg of OPO. The high content of chlorophyll pigments in OPO, compared with the content in virgin olive oils, are a result of solvent extraction of crude oils. These pigments have pro-oxidant activity, which means they will catalyze the oxidation reaction, contributing for the quality decrease of the oils [40]. Moreover, OPO-2 shows higher contents of chlorophyll pigments than OPO-1 and OPO-3. The differences might be due to changes in olive cultivars and stages of fruit development [41]. Regarding the fatty acid (FA) composition, all OPO samples had a similar composition which was similar to FA composition of olive oil, as reported by the Commission Regulation (EEC) Nr. $\frac{2568}{91}$ [39] for both oils: oleic acid (C18:1) is present in the largest amount (69–$71\%$), followed by palmitic acid (C16:0) ($14\%$), and linoleic acid (C18:2) (10–$11\%$). Stearic acid (C18:0) accounted for 2.11–$2.23\%$, whereas palmitoleic acid (C16:1) contributed to 1.32–$1.46\%$ (Table 1). It shows that the OPO has good nutritional quality. Moreover, it is a good source of oleic and linoleic acids, mainly esterified at position sn-2 in TAGs, which is important in the prevention of cardiovascular diseases. ## 2.2. SL Synthesis OPO acidolysis and interesterification were carried out in solvent-free media, catalyzed by Lipozyme TL IM or Lipozyme RM IM, in a packed-bed continuous bioreactor, at 40 °C. The acidolysis reactions of OPO were developed with C8:0 or C10:0, while in interesterification, C8EE and C10EE were used as acyl donors. Three different OPO samples were used to perform the reactions. OPO-1 ($12.05\%$ FFA) was used in the experiments with C10EE using Lipozyme TL IM or Lipozyme RM IM, and in the acidolysis with C10:0 using Lipozyme TL IM. OPO-2 ($15.06\%$ FFA) was used in the acidolysis with C10:0 catalyzed by Lipozyme RM IM. OPO-3 ($28.75\%$ FFA) was employed in interesterification with C8EE and acidolysis with C8:0, either with Lipozyme TL IM or Lipozyme RM IM. In both types of reaction, the original FA at positions sn-1 and sn-3 of the TAG molecules will be replaced by caprylic or capric acid, in the presence of a sn-1,3 regioselective lipase, with the formation of novel TAGs. The new TAG yield, TAG conversion and FFA (or FA ethyl esters) conversion were determined. Figure 1 and Figure 2 show TAG conversion and New TAG yield along 70 h continuous acidolysis or interesterification reactions catalyzed by Lipozyme TL IM (Figure 1) and Lipozyme RM IM (Figure 2). In continuous mode, the reactions can be considered as steady state. However, in two reactions (C8EE + Lipozyme TL IM and C10EE + Lipozyme RM IM), the time to attain the steady state took longer to achieve. This phenomenon might be due to a lack of uniformity in the enzyme bed, making mass transfer more difficult (Figure 1 and Figure 2) [42]. Both biocatalysts presented a high activity along all the continuous 70 h reactions. The behavior of the biocatalysts along the reactions seemed not to be affected by the acidity value of OPO used which varied from ca. 12 to $29\%$ (Table 1). Similar behavior was previously observed for Lipozyme RM IM in batch acidolysis of crude pomace oils with acidity ranging from 3.4 to $20\%$ and caprylic or capric acids [38]. It is worth mentioning that the acidity of OPO is due to long-chain FFA in the reaction media, mainly oleic acid (Table 1). Conversion values of TAGs were approximately constant along the 70 h operation of the bioreactor. The values were greater than $70\%$ when using both lipases, either in acidolysis or interesterification (Figure 1 and Figure 2). Values of around $80\%$ TAG conversion were attained in acidolysis with capric acid or caprylic acid, catalyzed by Lipozyme RM IM, and in all interesterification systems. The novel TAG molecules generated might be of MLL or MLM type, depending on the FA substitution achieved with the acyl donor involved (one or two substitutions of a long-chain FA by caprylic or capric acid, at positions sn-1,3, respectively) [8]. Due to acyl migration, the formation of TAGs containing caprylic or capric acid at position sn-2 (MML, LML or MMM) may also occur, but in a lesser extent [20]. Since these reactions create intermediate molecules (monoacylglycerols, MAGs, and diacylglycerols, DAGs), the conversion values of TAGs are always higher than the yield of new TAGs along the reactions. With respect to the initial yields of new TAGs, values around 50–$60\%$ were observed for the interesterification reactions with C8EE or C10EE and acidolysis with capric acid catalyzed by both biocatalysts. When caprylic acid was used, new TAG yields were only around $30\%$ (Figure 1 and Figure 2). As expected, new TAG yields were lower than TAG conversion values. The differences between TAG conversion and yield values were about 25–$30\%$ for all systems, except for the acidolysis with caprylic acid (C8:0). Either with Lipozyme TL IM or Lipozyme RM IM, this difference was about $40\%$. This shows that ca. $40\%$ of the original TAGs were converted into partial acylglycerols and not into New TAGs of MLM or MLL type, when C8:0 was used as the acyl donor. This behavior shows the lower affinity of both enzymes for C8:0. Moreover, the new TAG yield observed in the system with C8EE and Lipozyme RM IM decreased to $25\%$ after 70 h continuous operation of the bioreactor (Figure 2). The observed behavior for both biocatalysts is characteristic of lipases which present a higher affinity for longer-chain fatty acids than for medium- or short-chain fatty acids, conversely to esterases [43]. Therefore, a higher activity is expected with increasing fatty acid chain-length. The observed results can be also explained by the concept of Log P (Hansch parameter) applied to the acyl donors used in each reaction system. Laane et al. [ 44] proposed for the first time, the use of Log P to assess the biocompatibility of organic solvents: solvents with Log P lower than 2 are harmful for the biocatalysts because they are very hydrophilic and remove the essential water layer of the biocatalysts; between 2 and 4, their behavior is unpredictable, and values higher than 4 indicate that no inactivation of the biocatalyst will occur. From data published by PubChem [45], the Log P values are as follows: Log P C8:0 = 3.05; Log P C10:0 = 4.09; Log P C8EE = 3.842; and Log P C10EE = 4.861. Both capric acid and ethyl decanoate have Log P values higher than 4. When Lipozyme RM IM was used, the highest productivities in SLs were obtained in the presence of these acyl donors. Lipozyme TL IM seemed not to be so much affected with more hydrophilic molecules since it showed similar results also in the presence of C8EE, with a Log P value slightly lower than 4.0. Either for Lipozyme TL IM or for Lipozyme RM IM, the lowest productivities in SLs were obtained in the presence of caprylic acid, which has a Log P value of 3.05. Thus, a possible inactivation of the biocatalysts caused by the more hydrophilic acyl donors may explain the observed results. In batch bioreactors, Heinzl et al. [ 38] observed that Lipozyme RM IM achieved similar new TAG yields (47.8–$53.4\%$), either in the acidolysis of crude olive pomace oil with C8:0 or C10:0 or in the interesterification with the respective ethyl esters. Conversely, Lipozyme TL IM showed a better performance in batch interesterification than in acidolysis, and the reaction rates were always lower than with Lipozyme RM IM. Moreover, Lipozyme TL IM showed higher affinity for C10EE over C8EE [38]. When crude spent coffee ground oil was used, both Lipozyme RM IM and Lipozyme TL IM showed a higher affinity for C10EE over C8EE, in batch interesterification [5]. However, Lipozyme RM IM produced higher yields in new TAGs by acidolysis than by interesterification. As observed with crude OPO, Lipozyme TL IM showed a higher activity in interesterification than in acidolysis. Other oils have been used as feedstock in SL production, with reactions catalyzed by Lipozyme RM IM or Lipozyme TL IM, such as grape seed oil [3] ($34.53\%$ C10:0 incorporation) or roasted crude sesame oil, rich in oleic acid [46] (C8:0 incorporation of $42.5\%$). In several studies, Lipozyme RM IM exhibited a higher degree of incorporation than Lipozyme TL IM [38,47,48,49]. In the present study, Lipozyme TL IM in continuous PBR showed a better performance than previously in batch mode. This may be explained by (i) the low mechanical resistance of this biocatalyst to magnetic stirring used in batch bioreactors, which might be responsible for the destruction of some particles promoting enzyme inactivation in contact with the impurities of crude OPO, and/or (ii) by a high enzyme load in the bioreactor bed, which will compensate the slower reaction rates of this biocatalyst compared to Lipozyme RM IM. ## 2.3. Operational Stability of Biocatalysts The results concerning TAG conversion and new TAG yields over 70 h continuous PBR operation (Figure 1 and Figure 2) show that for the majority of the systems, the values were almost constant during this time. Deactivation was only observed for Lipozyme TL IM in the presence of C10:0, and for Lipozyme RM IM in the interesterification with C8EE (Figure 3; Table 2). The observed New TAG yield was considered as $100\%$ activity, when the steady state was reached. As the reaction progressed, the residual activity of the biocatalyst at time t was calculated as the ratio between the observed yield at time t, and the initial yield ($100\%$ activity). The following models, where *Actt is* the residual activity at time t, were fitted: Linear deactivation model (Lipozyme TL IM + C10:0) [1]Actt=−0.224t+101.0 First-order deactivation model (Lipozyme RM IM + C8EE) [2]Actt=95.41e(−0.01t) These model Equations [1] and [2] were used to estimate the half-life time for each biocatalyst in these systems [42]. Thus, the half-life of Lipozyme TL IM in the presence of capric acid and OPO with $12\%$ acidity was estimated as 228 h. For Lipozyme RM IM, in the interesterification of ethyl caprylate with OPO containing $28.75\%$ acidity, the half-life time was lower and equal to 74 h, and the deactivation coefficient was 0.01 h−1. Table 2 shows that the operational stability of both biocatalysts seems not be affected by the acidity of OPO used. Most of the studies reported in the literature used batch reactors to conduct MLM structured lipids production. Consistent with our findings in a continuous bioreactor, high operational stability has been reported for lipases used in batch mode, even in the presence of olive pomace oil with high acidity [38]. López-Fernández et al. [ 50] observed that long-chain free fatty acids had a positive effect on the stability of a recombinant *Rhizopus oryzae* lipase immobilized on a resin, when used in batch transesterification of crude acidic olive pomace oil ($19\%$ acidity) or other crude oils with ethanol or methanol, for biofuel production. They concluded that the operational stability of the biocatalyst depended more on the oil type utilized than on its acidity. Studies on batch acidolysis of coffee ground crude oil with caprylic or capric acids have also shown lower half-lives for Lipozyme RM IM (47 h and 54 h, respectively), compared to our work [4]. In Nunes et al. [ 31] and Mota et al. [ 4], a loss of activity of the biocatalyst Lipozyme TM IM was verified in the acidolysis of virgin olive oil or OPO, respectively. Previous studies in continuous mode, with the same type of bioreactor (PBR), have been used to produce SLs. Lipozyme TL IM was used in a continuous PBR to produce low-calorie SLs by interesterification of refined fish oil with medium-chain TAG blend rich in caprylic and capric acids, at 60 °C, in solvent-free system [28]. This immobilized lipase was stable during 2-week continuous operation. During the acidolysis of grapeseed oil with C10:0, using Lipozyme RM IM in a continuous PBR, a half-life of 209.6 h and a deactivation coefficient of 0.0061 h-1 were estimated [51]. These results are similar to our results with the same acyl donor for Lipozyme TL IM (228.3 h), but our results were superior when Lipozyme RM IM was used in the same system. In the acidolysis of roasted sesame oil and caprylic acid in a continuous PBR, Lipozyme RM IM showed a high stability with a half-life of 19.2 days [46]. Lipozyme TL IM and Lipozyme RM IM were also used in the interesterification of blends of olive oil, palm stearin, and palm kernel oil implemented in a continuous PBR [16]. Both biocatalysts followed a first-order deactivation profile showing half-lives of 88 h and 60 h, for Lipozyme TL IM and Lipozyme RM IM, respectively. These results strongly suggest that the operational stability of immobilized enzymes relies on the type of bioreactor operation (batch or continuous), on the reaction and on the reaction medium composition. In batch mode, mechanical agitation comes into direct contact with the enzyme. In continuous mode, the enzyme is placed in the packed-bed column without agitation, or in a fluidized-bed, helping the integrity of the enzyme. In this sense, further research into the continuous mode, using OPO as a raw material and immobilized lipases, is required. The results of the present study are very promising, with regard to the advantage of using continuous bioreactors. Many variables, such as reagent molar ratio, substrate composition, and bioreactor operating parameters have an impact on product yield and quality [51]. ## 2.4. Productivity and Biocatalyst Costs To evaluate the economic feasibility of the enzymatic reactions, the cost associated with each biocatalyst used was determined. The price for each biocatalyst was provided by Novozymes A/S: Lipozyme TL IM—110 EUR /Kg; Lipozyme RM IM—923 EUR /Kg (information given in September 2022). The specific productivity of New TAGs (g/h.g biocatalyst) was calculated using the measured flow rate (Q), the operation time (70 h), the average production of new TAGs during the operation, and the mass of enzyme bed (10 g). Table 3 shows the specific productivities for the synthesis of novel TAGs in each system and the biocatalyst cost to obtain 1 kg of structured lipids. Comparing specific productivities, similar values were obtained with both biocatalysts in the presence of caprylic acid or capric acid and C10EE, being higher when the acidolysis was carried out with capric acid or C10EE. Lipozyme RM IM showed a clear affinity towards capric acid or its ethyl ester. Lipozyme TL IM showed a higher affinity to capric acid over caprylic acid but promoted higher productivities when ethyl caprylate (C8EE) was used instead of ethyl caprate (C10EE). The cost of Lipozyme TL IM was always lower than EUR 1 per kg of new TAGs, except for the system with caprylic acid, where the specific productivity was almost half the values observed for the other acyl donors. With respect to the cost of Lipozyme RM IM, it varied between EUR 7.06 and 12.73 to produce 1 kg of structured lipids. The highest costs were observed for the interesterification of OPO with C8:0 (EUR 12.73) and C8EE (EUR 11.68), catalyzed by Lipozyme RM IM, where a low yield in New TAGs and considerable deactivation were observed, respectively (Figure 2 and Figure 3, Table 2) When biocatalyst costs are compared, the use of Lipozyme TL IM is preferred, since Lipozyme RM IM cost varies from 7.3- to 13.4-fold the value for Lipozyme TM IM. Having a similar catalytic behavior and operational stability to Lipozyme RM IM, Lipozyme TL IM showed to be the preferred biocatalyst for the continuous production of dietetic SL from acidic OPO, in a PBR and solvent-free medium, due to its lower price. ## 3.1. Materials Crude OPO samples were kindly donated by UCASUL—União de Cooperativas Agrícolas do Sul, Alvito, Beja, Portugal. The commercial immobilized sn-1,3 regioselective lipases Lipozyme TL IM (*Thermomyces lanuginosus* lipase immobilized on a non-compressible silica gel carrier; density = 0.40; 250 IUN/g) and Lipozyme RM IM (Rhizomucor miehei lipase immobilized on a resin carrier; density = 0.33; 275 IUN/g) were a gift from Novozymes A/S, Denmark. Caprylic acid (C8:0; >$98\%$ purity), capric acid (C10:0; >$98\%$ purity), ethyl caprylate (C8EE; >$98\%$ purity), and ethyl caprate (C10EE; >$98\%$ purity) were provided by TCI Europe N.V., Belgium. All reagents used were analytical grade. ## 3.2. Olive Pomace Oil Characterization To remove the majority of impurities, the OPO was firstly centrifuged (10,000 rpm/30 min, at 40 °C). Three different crude OPO samples were characterized with respect to the following properties: acidity, oxidation products, and chlorophyll pigments and fatty acid (FA) composition (Table 1). Both oil acidity and oxidation products were determined in accordance with Commission Regulation EEC, No $\frac{2568}{91}$ [1991], in relation to the properties of olive and olive pomace oils and associated analysis procedures [39]. The acidity of the samples was measured based on the amount of free fatty acids (FFA) present in OPO, expressed as oleic acid. Absorbances at 232 and 270 nm were used to analyze oxidation products (K232: presence of initial products of oxidation; K270: presence of final oxidation products). Both were determined using a UV/Vis spectrophotometer (Agilent Technologies Cary series 100 UV-Vis). The color characterization was determined according to Pokorny et al. [ 40] by measuring the absorbance at 630, 670, and 710 nm against air to quantify chlorophyll pigments on the samples. Green pigment contents were expressed as pheophytin a (mg/kg). Furthermore, the fatty acid composition was evaluated by gas chromatography, after their conversion into fatty acid methyl esters (FAME) using a Perkin Elmer Autosystem 9000 gas chromatograph (GC), equipped with a FID and a fused silica capillary column Supelco SPTM—2380 (60 m × 0.25 mm × 0.2 μm film thickness). The injector and FID were set at 250 and 260 °C, respectively. The column temperature was set at 165 °C for 45 min, increasing at a rate of 7.5 °C/min up to 230 °C, holding for 25 min at this temperature. Helium was used as carrier at a pressure of 20.0 Psig. FAME standards (GLC-10 FAME mix, 1891-1AMP, from Sigma-Aldrich, St. Louis, MA, USA), analyzed under the same conditions, were used for fatty acid identification. ## 3.3. Continuous Bioreactor Systems for Acidolysis and Interesterification Reactions Interesterification and acidolysis reactions were carried out in solvent-free media, using a continuous packed-bed bioreactor. It consisted of a glass column with an internal diameter of 2 cm and a height of 20 cm, with a double jacket for water circulation and temperature maintenance, and a glass sieve (G0) on the bottom to retain the biocatalyst. For each experiment, 10 g of immobilized lipase was used at its original water activity: 0.152 for Lipozyme TL IM and 0.585 for Lipozyme RM IM, at 20 °C. Reaction media were pumped upwards with a peristaltic pump, to avoid bed clogging and channeling, through silicone tubing from a conical flask placed in a water bath at 40 °C, under magnetic stirring. Reaction media consisted of blends of crude OPO with capric acid ethyl ester (C10EE) or caprylic acid ethyl ester (C8EE) in interesterification reactions, or with the acid forms (C10:0 and C8:0, respectively) in the acidolysis reactions. A 1:2 molar ratio of oil/acyl donor, corresponding to the stoichiometric ratio, was used. The bioreactor operated for 70 h, with a pause during the night. Periodically, along the continuous reactions, 5 mL samples were taken. The collected samples were then frozen at −18 °C for subsequent analysis. For each packed-bed reactor system, the flow rate (Q) was calculated as the ratio of the recovered volume (V, mL) of reaction media to the time (t, min). The residence time (τ) for each system was estimated using the following equation (Equation [3]), described as the ratio between the product of the volume of the enzyme bed (Venzyme bed) by its porosity (ε) and the flow rate [27]. [ 3]τ=Venzyme bed∗εQ Table 4 shows the flow rate (Q, mL/min), enzyme bed volume (V, mL), void fraction (ε), and residence time (τ, min) values for each continuous packed-bed bioreactor working with Lipozyme TL IM or Lipozyme RM IM. The bed volume with 10 g Lipozyme TL IM was 19.2 mL, while with 10 g Lipozyme RM IM, it was 30.8 mL. The observed flow rate in both cases was 0.6 mL/min. The void fraction was estimated by volume displacement, according to the methodology presented by Xu et al. [ 27]. For Lipozyme TL IM, the void fraction was 0.34 and the residence time was 11 min. The void fraction for Lipozyme RM IM was 0.39, and the predicted residence time was 20 min, which is about twice the value for Lipozyme TL IM. The differences in residence time may be explained by differences in column packaging originating different bed volumes. Xu et al. [ 27] obtained different values of void fraction in a packed-bed column filled twice with Lipozyme RM IM (0.44 ± 0.01 and 0.47 ± 0.02). For Lipozyme TL IM in a packed-bed reactor, a void fraction of 0.51 ± 0.1 was estimated by Xu et al. [ 28]. The starting operation time was considered when the steady state was attained, i.e., the time equal to four residence times (around 44 min and 80 min when Lipozyme TL IM or Lipozyme RM IM were used, respectively). ## 3.4. Reaction Product Analysis by Gas Chromatography The different compounds present in the samples, namely the original TAGs and FFA or ethyl esters, novel TAGs, diacylglycerols (DAGs), monoacylglycerols (MAGs) and FFA, were identified and quantified by GC in accordance with European Standard EN 14105 [52] with some modifications. Before GC analysis, all samples needed to be derivatized, following the following steps: (i) 0.05 g of each sample was weighed in a 10 mL volumetric flask and then filled with hexane; (ii) 0.5 mL of the previous mixture was added to a pear-shaped flask; (iii) the solvent was evaporated by rotavapor equipment (<120 mbar, 30–35 °C, 10 min); (iv) 400 μL of internal standard (IS) solution (0.05 g of monononadecanoine in 25 mL of tetrahydrofuran), 200 μL of pyridine, and 200 μL of N-methyl-N-trimethyl-silyl-triflouracetamide were added to the dried sample. After 15 min, (v) 4 mL of heptane was added to the flask under stirring. The sample was transferred to 1 mL vials for gas chromatography analysis. A gas chromatograph Agilent Technologies 7820 A, equipped with an on-column injector, one Agilent J&W DB5-HT capillary column (15 m × 0.320 mm ID × 0.10 μm film), and a flame ionization detector was used. Helium gas was used as a carrier. The gases were delivered at a flow rate of 30 mL/min (helium, hydrogen, and nitrogen) and 300 mL/min for compressed air. The following oven temperature program was followed: an initial temperature of 50 °C rising at a rate of 15 °C/min to 180 °C. Following this, the temperature increased at a rate of 7 °C/min until 230 °C. Finally, the temperature increased to 365 °C over 12 min at a final rate of 10 °C/min. Each peak in the chromatograms was identified by comparing it to pure compound standards and with the chromatograms presented in the European Standard EN 14105 [52]. Figure 4 shows an example of two chromatograms obtained for the initial reaction medium (OPO and C8EE) and at a steady state of continuous interesterification, catalyzed by Lipozyme TL IM. In each chromatogram, the area of each peak was divided by the area of the peak of the internal standard (IS). The amounts of initial TAGs were proportional to the sum of the areas of all TAG peaks (Ainitial TAG) divided by the area of the peak of the IS (AIS), in the initial fat blend. Along bioreactor operation, the same procedure was used to quantify the new TAGs that appear as new peaks in the TAG region of the chromatogram (Anew TAG) (Figure 4). Therefore, the New TAG yield (Y,%) was calculated as follows (Equation [4]), where the numerator corresponds to the peaks of the chromatogram at time t, and the denominator corresponds to the peaks of the chromatogram of the initial blend:[4]Y=(∑Anew TAGAIS∑ApeaksAIS)(∑Ainitial TAGAIS∑ApeaksAIS)×100 TAG, FFA, or ethyl esters conversions were calculated as the ratio between the amount of TAG (ethyl ester or FFA) consumed and the corresponding initial quantities (in terms of peak areas divided by the area of the IS peak, as explained for New TAG yield). ## 3.5. Assessment of Continuous Operational Stability of Biocatalysts Along the continuous bioreactor operation, the activity of the biocatalysts was evaluated as the yield of new TAGs, formed by the incorporation of medium-chain FAs in the TAGs of OPO, either by acidolysis with caprylic or capric acids, or interesterification with their ethyl esters. The residual activity along continuous operation was determined as the ratio between New TAG yield at time t and the New TAG yield, observed at time 0, i.e., when the steady state was attained. The activity at time zero was considered as $100\%$. When biocatalyst deactivation was observed along the operation, deactivation kinetic models were fitted by the “Solver” add-in in Excel to estimate the operational half-life time (operation time needed to reduce the original activity to $50\%$) [38]. ## 4. Conclusions This is the first work on the lipase-catalyzed continuous production of low-calorie SLs in a packed-bed reactor, using crude acidic (12–$29\%$ acidity) OPO in solvent-free media. Both immobilized lipases used (Lipozyme TL IM and Lipozyme RM IM) presented a high activity either in acidolysis with caprylic or capric acid or in interesterification with their ethyl esters. The SLs were new TAGs where a medium-chain fatty acid was esterified at one of the positions sn-1 or sn-3 or in both (MLL or MLM molecules). Yields of new TAGs of around 50–$60\%$ were observed for the interesterification reactions with C8EE or C10EE and acidolysis with capric acid, catalyzed by both biocatalysts. In the acidolysis with caprylic acid, new TAG yields were only around $30\%$. The biocatalysts maintained the activity along the 70 h continuous reactions except Lipozyme TL IM in the presence of capric acid (half-life time of 228 h) and Lipozyme RM IM in the interesterification with C8EE (half-life time of 74 h). The acidity value of OPO used (12 to $29\%$ free fatty acids) did not affect the activity and stability of the biocatalysts. Comparing specific productivities in new TAGs, similar values were obtained in the presence of caprylic acid (0.96 vs. 1.04 g/h.g biocatalyst), capric acid (1.65 vs. 1.79 g/h.g biocatalyst), or C10EE (1.62 vs. 1.87 g/h.g biocatalyst), with Lipozyme TL IM or Lipozyme RM IM, respectively. Higher affinity for C8EE was observed for Lipozyme TL IM, when compared with Lipozyme RM IM, resulting in specific productivities of 1.80 and 1.13 g of new TAGs/h.g biocatalyst, respectively. Lipozyme TL IM, which is very prone to mechanical damage in batch stirred reactors, maintained its activity over 70 h operation in a packed-bed reactor. Therefore, this biocatalyst is adequate for continuous processes. Moreover, due to its high productivity, stability, and lower cost, Lipozyme TL IM demonstrated to be more promising than Lipozyme RM IM for MLM synthesis in continuous bioreactors. 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--- title: 'A New Perspective for Vineyard Terroir Identity: Looking for Microbial Indicator Species by Long Read Nanopore Sequencing' authors: - Ana Cruz-Silva - Gonçalo Laureano - Marcelo Pereira - Ricardo Dias - José Moreira da Silva - Nuno Oliveira - Catarina Gouveia - Cristina Cruz - Margarida Gama-Carvalho - Fiammetta Alagna - Bernardo Duarte - Andreia Figueiredo journal: Microorganisms year: 2023 pmcid: PMC10054463 doi: 10.3390/microorganisms11030672 license: CC BY 4.0 --- # A New Perspective for Vineyard Terroir Identity: Looking for Microbial Indicator Species by Long Read Nanopore Sequencing ## Abstract Grapevine is one of the most important fruit crops worldwide, being Portugal one of the top wine producers. It is well established that wine sensory characteristics from a particular region are defined by the physiological responses of the grapevine to its environment and thus, the concept of terroir in viticulture was established. Among all the factors that contribute to terroir definition, soil microorganisms play a major role from nutrient recycling to a drastic influence on plant fitness (growth and protection) and of course wine production. Soil microbiome from four different terroirs in Quinta dos Murças vineyard was analysed through long-read Oxford Nanopore sequencing. We have developed an analytical pipeline that allows the identification of function, ecologies, and indicator species based on long read sequencing data. The Douro vineyard was used as a case study, and we were able to establish microbiome signatures of each terroir. ## 1. Introduction Grapevine is one of the most important fruit crops worldwide. In 2021, 7.3 million hectares of the word cultivated area were dedicated to viticulture to produce table grapes and wine. Portugal is one of the top 5 producers with 194 thousand hectares of vineyards and 7.3 million of hectolitres of wine production [1]. Wine can be distinguished as branded wine and terroir wine. Branded wine is produced by blending grapes from various regions, while terroir wine is made exclusively from grapes from a specific region that comprises singular characteristics [2]. It is well established that wine sensory characteristics from a particular region are defined by the physiological responses of the grapevine to its environment and thus, the concept of terroir in viticulture was established to define the physical (e.g., climate, soil) and biological (e.g., soil microbiota, grape variety, fauna) characteristics, as well as the viticulture and oenological techniques of a particular geographical location [2]. In 2010, the International Organization of Vine and Wine published an official definition of terroir: “ Vitivinicultural “terroir”, is a concept which refers to an area in which collective knowledge of the interactions between the identifiable physical and biological environment and applied Viti vinicultural practices develops, providing distinctive characteristics for the products originating from this area. “ Terroir” includes specific soil, topography, climate, landscape characteristics and biodiversity features”, highlighting its complexity. Among all the factors that contribute to terroir definition, soil microorganisms play a major role. Soil microbiota are a very important aspect of the ecosystem, their contribution going beyond nutrient recycling to a drastic influence on plant fitness (growth and protection). Vineyard microbiota can greatly influence the productivity of agricultural systems forming complex and dynamic associations, which can range from mutualistic to commensal to pathogenic [3,4,5,6,7]. Several examples of this have already been described for grapevine, from plant inoculation with growth-promoting bacteria leading to increase in growth and bunch production per plant [4]; to protection against pathogens such as *Botrytis cinerea* [5,6] and *Plasmopara viticola* [6,7] with natural antagonists. Also, microbial activity has a special influence on wine production and quality [8,9]. Studies of grape and must microbiomes highlight differences in fungal and bacterial communities of different regions [10,11]. Considering that soil is a reservoir of microbial communities in the vineyard [12], terroir-associated microbiota will certainly influence not only both grapevine plants’ ability to cope with stress and its fitness, but also ultimately terroir wine sensory characteristics. Moreover, soil could represent an important source of grapevine pathogens inoculum [13], so understanding the potential differences between their abundances in soil could help in the definition the viticulture management practices. In this study, we aimed at defining microbiome signatures and indicator species for different terroirs based on long-read Oxford Nanopore sequencing. Quinta dos Murças, an organic vineyard located in the demarcated wine region of the Douro Valley, was chosen as a case study has it presents a unique topography and exposure, and different terroirs were previously identified. ## 2.1. Vineyard Location and Sampling Soil samples were collected at Quinta dos Murças, belonging to the wine company Esporão, located at Alto Douro Wine Region, right bank of the Douro River (41°09′11.9″ N 7°41′17.3″ W), Portugal (Figure 1). These vineyards are managed by a single owner, minimizing differences in viticulture management, and an organic viticulture approach is followed. Soil is derived from metasedimentary rocks and granitoids, being the vineyard’s soils of schistose origin. As the soil in vineyards has been strongly affected by human activities it can be classified as an anthropology [14]. Different terroirs have been defined in this vineyard, according to soil and edaphoclimatic conditions. Four terroirs were selected for this study (Table 1), bulk soil samples were collected in 2018, during grapevine season (July and mid-September) at a depth of 5–20 cm under the canopy of adult grapevine plants (namely from the cultivar Touriga nacional—evenly represented in all the terroirs). Phytosanitary status of the vineyard was consistently monitored throughout the seasons and years. To avoid differences in soil composition, soil samples were taken between grapevine plants in the same row and fifteen sites were sampled per terroir. Soil samples were taken and mixed to obtain a homogeneous sample of about 5 kg. Homogenized soil was immediately passed through a 2-mm-pore-size sieve, and five subsamples of 100 g each were randomly selected and stored in sterile bags on dry ice at the time of sampling. Samples were then kept at −80 °C until processing. ## 2.2. Determination of Soil Physicochemical Characteristics For each terroir, several soil parameters were evaluated, namely: pH, water content, organic matter (OM), nitrate (NO3-), total phosphate and inorganic soluble phosphate (PO4−). Five soil samples taken in mid-September were used per terroir. A 1:10 soil water extract was prepared as described in Dias et al. [ 15] and used to determine soil pH by means of a selective electrode; nitrate concentration by vanadium trichloride (VCl3) Griess reaction [16]; and inorganic soluble phosphate (PO4−) by malachite green reaction [17]. Soil organic matter was determined by loss of ignition according to Schulte and Hopkins [18]. To determine the total soil phosphate concentration, the soil ashes obtained after ignition of the organic matter were resuspended in 1 M KCl and subsequently analysed using the malachite green reaction [17]. The concentrations of NO3-, total PO4- and inorganic soluble PO4- were expressed as mg or µg per gram of dry soil. Soil dry weight was obtained by drying soil samples at 45 °C until constant weight. Organic matter (OM) concentrations were also expressed as % of dry soil. The Kruskal-Wallis test coupled with post hoc Fisher’s and a Bonferroni correction adjustment method was used to define the statistical significance of all physiological parameters between the terroirs. Statistical analysis was performed with the agricolae R package [19]. ## 2.3. DNA Extraction From each terroir soil sample, total DNA extraction was performed using the DNeasy® PowerMax® Soil Kit (Qiagen, MD, USA), with slight changes to the manufacturer protocol. The protocol’s input material and lysis steps were adapted to fit different soil textures (for drier soils, 5 g of input soil were used instead of 10 g and an additional heating step was performed during lysis). DNA quality and concentration were assessed by NanoDropTM One and QubitTM 4 Flourometer analysis. Three biological replicates for each terroir were obtained and used as independent samples. ## 2.4. Metagenomic Sequencing by Long-Read Nanopore Quantification steps were performed using the dsDNA HS assay for Qubit. DNA was end-repaired (New England BioLabs, MA, USA), cleaned with Agencourt AMPure XP Beads (Beckman Coulter, High Wycombe, UK) and dA-tailed (New England BioLabs, MA, USA). The library was prepared from 1400 ng input DNA using the SQK-LSK109 kit (Oxford Nanopore Technologies, Oxford, UK) in accordance with the manufacturer’s protocol. The library was quantified and prepared for GridION sequencing, using FLO-MIN106 flowcells, MinKNOW v18.12.4, standard 48-h run script with active channel selection enabled, until 2.5 Gb of data was collected from each sample. The mean read length of the sequenced reads was 3944 bps and the mean quality score was 10.45. ## 2.5. Bioinformatic Analysis After removing the low-quality gDNA reads, the remaining reads were filtered for size and quality keeping reads with lengths higher than 300 bps and phred score ≥ 7, using Prinseq-lite version 0.20.4 [20]. A customized in-house analytical pipeline for long-read Nanopore sequencing was used to obtain high-accuracy taxonomical classification. The used approach had been validated through ZymoBIOMICSTM Microbial Community Standard (Zymo Research Corp., Irvine, CA, USA). Taxonomic classification was performed using Kraken2 (version 2.1.2), running on default options and using a reference database including the NCBI Refseq reference genomes of Archaea, Bacteria, Viruses and the NCBI Genbank reference and representative genomes of Fungi [21]. Rarefaction curve to assess the sequencing depth (R package vegan; Figure S1) followed by a sample rarefaction to the lowest number of reads was performed (R package phylosep; 711 seed). Alpha diversity of microbiota community was assessed by calculating the Chao1 richness [22], Shannon diversity [23,24] and Pielou evenness [25] indexes using the microbiome R package [26] and compared between terroir with a Kruskal-Wallis test coupled with post hoc criterium Fisher’s least significant difference with Bonferroni correction adjustment method using agricolae R package [19]. Chao1 index considers the number of species in the community. Shannon considers the number of species and their relative abundance, measuring the uncertainty about the identity of an unknown individual. Pielou evenness index tell us if the number of individuals of each species is even or not in an area. Taxonomical relative abundance analyses were performed using the microbiome R package [26] and compared between terroirs by Kruskal-Wallis test coupled with post hoc criterium Fisher’s least significant difference with Bonferroni correction adjustment methods [19]. Phylum relative abundance was calculated based on phylum absolute abundance and class relative abundance was calculated based on class absolute abundance. Functional analysis was performed with the microeco [27] R package using the procaryotes database FAPROTAX [28] and FungalTraits for fungi [29]. Tables S1 and S2 show the functions and ecologies associated with species. For the identification of potential terroir-associated indicator species and functions, taxonomic reconstruction species had to meet three criteria: [1] Correlation indices analysis based on point biserial correlation coefficient must present a significant ($p \leq 0.05$) association to a given Terroir. This analysis was performed using the R package “indicspecies” [30], results were visualised as network generated using Cytoscape (version 3.9.1) with the edge-weighted spring-embedded layout and terroirs were defined as source nodes, the associated species as nodes and the association strength as edges. [ 2] Variable Importance for Projection Partial Least-Squares Discriminant Analysis (VIP-PLS-DA) must present a VIP score > 1. VIP-PLS-DA analyses were made using the R package DiscriMiner [31]. [ 3] relative abundance of the identified species must be significantly ($p \leq 0.05$) higher in the terroirs. This analysis was performed using by Kruskal-Wallis test coupled with post hoc criterium Fisher’s least significant difference with Bonferroni correction adjustment methods [19]. All R analysis were performed in R-studio version 1.4.1717. ## 3.1. Physicochemical Characterization of Quinta dos Murças Terroirs Six physicochemical characteristics (pH, organic matter content (OM), water content, inorganic soluble and total phosphate, and nitrate content) were analysed. All terroirs presented a slightly acidic pH, with Assobio and Margem covering the less acidic soils, and Vinhas Velhas the most (Table 2). Though the difference in pH is less than 1, this can greatly affect the bioavailability of nutrients [32]. Reserva shows significantly lower OM than the other terroirs. From all the terroirs analysed, Vinhas Velhas presented the highest total phosphate contents, followed by Margem. Reserva soil presented the lowest amount of total and available phosphate. Considering inorganic soluble phosphate, Margem soil presented the highest content. Nitrate was more abundant in Margem and Assobio, being significantly higher than in the Vinhas Velhas and Reserva terroirs. ## 3.2. Global Terroir Microbiome Analysis Terroir-associated microbiome was assessed by long-read Oxford Nanopore sequencing technology. A total of 12.56 million reads were obtained. Reads with ≥300 bps and quality score ≥7 were considered for taxonomic analysis. A total of 9.19 million reads were used for taxonomic reconstruction analysis. An in-house pipeline based on k-mers taxonomic classification was used, leading to the identification of 2.73 million reads. After rarefaction (Figure S1), 9670 different microbial taxa were identified, 8558 of those at species level (Table S3). The taxa were further classified as Bacteria [5792], Viruses [313], Archaea [274] and Fungi/Oomycete [3291]. Overall, 67 Phyla, 149 Classes, 351 Orders, 841 Families and 2633 Genera were identified. Looking at the overall representation of the identified taxa, Bacteria was the most represented kingdom followed by Eukaryota (considering fungi and oomycete only) while Archaea and Virus kingdoms were the less represented (Figure S2A). Considering Phyla, seven *Archaea phyla* (Figure S2B) were found and of these, Euryarchaeota presented the higher relative abundances (>0.7). Candidatus *Korarchaeota is* the less represented phylum. Whitin Eukaryota, Ascomycota presented higher relative abundances followed by Basidiomycota, Oomycota and Mucoromycota (Figure S2C), while Sanchytriomycota presented the lower relative abundances. Considering virus, Uroviricota (virus that infect bacteria and archaea) were the more abundant, while Cossaviricota were the less abundant (Figure S2D). When looking at the *Bacteria phyla* (Figure S2E), Proteobacteria and Actinobacteria were the phyla with higher relative abundances, both above 0.3. The remaining phyla showed relative abundances lower than 0.1, being Balneolaeota the phylum with lowest relative abundance. Alpha diversity, that determines microorganisms’ diversity within each terroir, was analysed based on the Chao1 richness, Shannon diversity and Pielou evenness indexes (Figure 2). Through both Shannon and Chao1 indexes, no significant differences were detected between the terroirs (Figure 2A,B). The Pielou evenness index, however, showed that Margem terroir presents a significant higher diversity than Reserva terroir (Figure 2C). Next, the most abundant phyla on the different terroirs were assessed. Within Bacteria kingdom, Proteobacteria, Plantomycetes, Firmicutes, Bacteroidetes, Actinobacteria and Acidobacteria were the more abundant phyla (Figure 3). The Bacteroidetes and *Acidobacteria phyla* were the only that presented statistical significances between terroirs (Figure 3A). Bacteroidetes relative abundance was significantly higher in Margem samples when compared to Reserva soil. Acidobacteria relative abundance is also significantly higher in Reserva terroir when compared to Assobio and Margem terroirs (Figure 3A). Margem is the terroir that presents the lower abundance of Acidobacteria. At class level, Deltaproteobacteria, Betaproteobacteria, Alphaproteobacteria, and Acidobacteriia abundances were significantly different between the four terroirs (Figure 3B). Alphaproteobacteria presented a higher abundance in Assobio soil when compared to Reserva soil. The terroirs Margem and Assobio presented a higher abundance of Betaproteobacteria when compared to Reserva and Vinhas Velhas. Also, the Vinhas Velhas terroir presented lowest Betaproteobacteria relative abundance. The Margem terroir showed significantly higher relative abundance of Deltaproteobacteria class when compared to all the terroirs. Considering Eukaryota, Plantomycetes, Oomycota, Basidiomycota and Ascomycota showed no significant differences between the terroirs. Mucoromycota presents significant lower relative abundance in Vinhas Velhas soil samples when compared to the other terroirs (Figure 3A). At Class level, Eurotiomycetes and Sordariomycetes presented no significant differences between the terroirs. Dothideomycetes relative abundance is significantly higher in Assobio and Margem soils when compared to Reserva soils (Figure 3B). Agaricomycetes abundance is significantly higher in Assobio samples comparatively to Reserva samples. ## 3.3. Functional Analysis Functional analysis was done considering the identified species, to assess metabolic or other ecologically relevant functions of the different terroir’s microbiome. Bacterial and fungal ecological functions present a very similar distribution/representation across all terroirs, globally maintaining the same relative abundances, with some subtle differences that specifically differentiate them. A cluster analysis allowed the discrimination of two groups, one including Reserva and Vinhas Velhas terroir samples and other including Assobio and Margem terroir samples, for both prokaryotic function (Figure S3) and fungi ecology (Figure S4). Although being the prevalent bacterial function identified across all terroirs, “nitrogen fixation” occurs at much higher abundances in the Assobio and Vinhas Velhas terroirs and allowed the discrimination between Assobio and Margem (Figure 4A). “ Xylanolysis” appears as the second function with higher relative abundance allowing the discrimination of Reserva terroir samples from the other terroirs. Though being a less abundant function, “nitrification” also allows the discrimination between Margem and Vinhas Velhas samples. Regarding fungi associated functions, the Reserva terroir present significant alterations in the relative contribution of “decay substrate” the function with higher relative abundance from those that present statistical significances (Figure 4B). The second higher relative abundance fungi function, “endophytic interaction capability—foliar endophyte” presented significant differences between the Margem and Reserva (Figure 4B). “ Root associated” classification present the lowest abundance of in Vinhas Velhas terroir when compared to other terroirs, as well as “Endophytic interaction capability—root endophyte”. Considering mycorrhiza associated guilds, “arbuscular mycorrhizal—secondary lifestyle” and “ectomycorrhizal” present statistical differences between Reserva and Vinhas Velhas terroir samples. “ Arbuscular mycorrhizal—primary lifestyle” is also significantly different in present Vinhas Velhas when comparing to the other terroirs, presenting the lowest abundance (Figure 4B). Considering “Foliar endophytes”, Margem and Reserva terroir samples were statistically different with Margem presenting a higher abundance when compared to Reserva. ## 3.4. Identification of Indicator Species and Functions for Each Terroir To depict possible indicator species responsible for terroir discrimination, a point biserial correlation analysis and a Variable Importance for Projection Partial Least-Squares Discriminant Analysis (VIP-PLS-DA) were conducted. The point biserial correlation analysis enabled the identification of 344 indicator species with significant association to the terroirs (Figure 5). Margem presented the highest number of indicator species [124], comprised in 21 different Phyla, the majority belonging to Proteobacteria [36], Ascomycota [30], Basidiomycota [18] and Actinobacteria [11]. Assobio presented 100 indicator species belonging to 12 different phyla, with a predominance of Proteobacteria [36], followed by Ascomycota [22], Basidiomycota [12] and Bacteroidetes [11]. Vinhas Velhas presented 75 indicator species, 35 belonging to Actinobacteria and 12 to Proteobacteria, the more represented phyla. Reserva is the terroir with the lowest number of indicator species, mostly represented in Actinobacteria [17] and Proteobacteria [12] phyla. We were able to identify also potential indicator functions and fungal ecology for each terroir based on Prokaryotic and Eukaryotic species. Considering the prokaryotic function, *Assobio is* the terroirs with higher number [7], followed by Margem [3] and Reserva [1]. Vinhas Velhas had no indicator function identified. Based on fungal ecology Margem was the terroirs with higher number of potential indicators [10], followed by Assobio with 4 indicator fungal ecology. Reserva and Vinhas Velhas had the same number on fungal indicator ecologies [2]. For visualisation purposes PLS-DA biplots were produced to better visualize the sample dispersion and grouping at microbiome (Figure 6A), prokaryotic function (Figure 6B) and fungal ecology levels (Figure 6C). Considering the terroir microbiome (Figure 6A), 3278 species presented a VIP score >1, thus contributing to PLS-DA model terroir separation. The PLS-DA biplot shows a clear spatial pattern, with the samples organized in clusters according to the collection area (terroir), resulting in $100\%$ accuracy in correctly classifying the terroir samples according to the species abundance dataset (Figure 7). The VIP-PLS-DA projection for prokaryotic functional and fungal ecology is shown in Figure 6B,C. The PLS-DA biplot shows function organization in clusters according to the collection area (terroir), resulting in $77.78\%$ accuracy in correctly classifying the prokaryotic functions to the terroirs and $88.89\%$ accuracy in correctly classifying the fungal ecology indicators to the terroirs (Figure 7). Reserva and Vinhas Velhas were the terroirs with the lowest model accuracy considering indicator functions, while Margem was the terroirs with the lowest model accuracy considering fungal ecology indicators (Figure 7). When comparing both approaches (VIP-PLS-DA and point biserial correlation analysis) 313 species, 11 prokaryotic function and 16 fungi ecologies were commonly identified as terroir-associated indicators. Of the species, 37 presented statistically different relative abundances in their specific terroir (Figure 8), while only 1 prokaryotic function and two fungi ecologies presented statistical differences. Assobio was the terroir with higher number of indicators taxa [14], being most of them low abundance taxa, with exception of Paraburkholderia species that were highly represented. Five of these species were exclusive to Assobio terroir samples while seven others were also present in other terroirs with different abundances (Figure S5). These indicator species belong to six different phyla (Bacteroidetes, Proteobacteria, Actinobacteria, Ascomycota, Basidiomycota, Firmicutes), being the Genus Paraburkholderia the only with two species. Assobio was also the only terroir with identified indicator function (dark iron oxidation) and fungi ecologies (“litter saprotroph” as primary lifestyle and “gills” Hymenium type). Twelve indicator species were identified for Margem terroir samples, six were exclusively present in this terroir (Figure S5). Margem indicator species belong to nine different phyla (Synergistetes, Actinobacteria, Thaumarchaeota, Verrucomicrobia, Ascomycota, Proteobacteria, Nitrospirae, Firmicutes, Deinococcus-Thermus), all with different Genus. Vinhas Velhas terroir samples revealed to have seven indicator species, with only one being exclusive to this terroir. Vinhas Velhas samples indicator species belonging to two phyla, Bacteroidetes and Actinobacteria, with six of these indicator species belong to the Genus Mycobacterium. Reserva terroir revealed the lower number of indicator species, four species belonging to tree different phyla, Actinobacteria, Ascomycota and Acidobacteria. ## 3.5. Grapevine Pathogens Grapevine pathogens were also found in the terroir soil samples; their relative abundance was rather low. Despite this low abundance, the identification of grapevine pathogens is important when considering management strategies. Plasmopara viticola, the etiological agents of downy mildew, were identified in all terroirs while *Botrytis cinerea* (the etiological agent of gray mold), was not present in Margem and Vinhas Velhas (Table S4). Erysiphe necator, the etiological agent of powdery mildew, was only present in Vinhas Velhas terroirs (Table S4). Several pathogens associated with grapevine truck diseases (GTD) were found, namely: Eutypa lata, *Lasiodiplodia theobromae* and Neofusicoccum parvum. These were the Four pathogens that presented higher abundance, particularly in Margem. Other GTD associated pathogens were found, Fomitiporia mediterranea, present in all terroirs and Botryosphaeria dothidea, present in Margem terroirs only. Fungi associated with esca syndrome development, Phaeomoniella chlamydospore and Phaeoacremonium minimum, were also found with higher abundances in Margem terroirs (Table S4). ## 4. Discussion Microbial communities associated with the vineyard play an important role in soil and plant productivity and fitness. Soil is the main microbiota reservoir and the specific (non-random) association between microorganisms and a particular geographical region reveals the potential applied impact of microbial terroirs [33]. The definition of microbial terroirs as well as the understanding of global patterns in the microbial community composition of specific vineyard soils may prompt the definition of adequate strategies (either agricultural or biotechnological) for productivity, disease resistance and wine sensorial traits. Also, information on the presence of grapevine pathogens may also pinpoint targets for monitoring throughout the crop season or enable the reduction of chemical treatments and definition of eradication strategies. Previous studies of vineyard soil microbiome were conducted by focusing on bacteria and fungi communities through Illumina sequencing [33,34,35]. To the authors knowledge this is the first metagenomic study of terroirs soil microbiome utilizing the long-reads Oxford nanopores sequencing technique. This technique was selected based on its ability to sequence whole genome without the amplification bias (especially important for discrimination between different samples) and allowing the discrimination of closed related species. This study also allowed for the identification of indicator species and function specific for each terror. Previous study also identified species that contributed for soil distinction but at a global scale [33]. Reserva was the terroir with lower organic matter values, which is coherent with the lower abundance of wood decay fungi such as Agaricomycetes [36]. This is also reflected when analysing the fungi ecology guilds that, apart from exception of “Arbuscular mycorrhizal fungi”, and “other root-associated fungi”, showed lower relative abundances. On the other hand, this higher presence of arbuscular mycorrhizal may result from lower concentration of phosphate and nitrate present in Reserva soil, as a strategy for improved nutrient uptake by the plants (review by [37]). Considering indicator species, Reserva was the terroir where a lower number of indicator species were identified, however its indicator species present roles in nitrogen and phosphate cycles, as well as biomass degradation. This is the case of Tetrasphaera sp. HKS02, a genus Tetrasphaera well known for its denitrification activity and Phosphorus (P) uptake ([38], reviewed in [39]). Moreover, Sinomonas atrocyanea, also identified as a Reserva terroir indicator species displays nitrate reduction and urease activities [40,41] as well as indole acetic acid production, and phosphate solubilization capacity [42]. These functions follow the same trend than Phosphate and nitrogen values found on this terroir. Vinhas Velhas was the terroir most similar to Reserva, considering soil physic-chemical characteristics, namely lower pH values and nitrate concentration. Total and soluble inorganic phosphate concentrations were high in Vinhas Velhas, similarly to Margem. Even though some soil characteristics were mostly similar to Reserva, Vinhas Velhas presented a higher microbial abundance. Several taxa may relate to the soil properties, namely the lower abundance of Mucoromycota, which may associate with the lower pH and higher Phosphate concentration found [43], and the lower relative abundance of Betaproteobacteria, which may also be associated with the pH and lower nitrate concentration [44]. Of the eight Vinhas Velhas indicator species, six belong to the genus Mycobacterium. When analysing deeper this genus, from all Mycobacteria species found (genus Mycobacterium, Mycolicibacterium, Mycolicibacter, and Mycobacteroides), $70\%$ of these presented higher read counts in the Vinhas Velhas terroirs them in other terroirs. Mycobacteria are ubiquitous bacteria present in a broad type of soils and environments; however high abundances of these bacteria are found in more acidic soils [45]. Although *Mycobacterium are* mainly studied as human and animal pathogens, previous studies indicate that the same species can act as root nodule endophytes, promoting soil nutrient turnover and/or being plant beneficial agents [46,47,48,49,50,51]. Assobio and Margem terroirs revealed to be the most similar, when considering the studied parameters. Only their inorganic phosphate concentration was significantly different, with Margem presenting a ten times higher concentration. These were also the terroirs with the highest relative abundance in most of the analysed taxa. Assobio and Margem showed higher aerobic nitrite oxidation and nitrification function, which may be associated with the higher nitrate values found, being this a highly important microbial function while oxidizing ammonia and nitrite to nitrate, the preferred N uptake form for plants [52]. At the class level, Margem terroir presented the highest abundance of Deltaproteobacteria. This class is characterized by sulphate and sulphur reduction bacteria [53,54,55], dissimilative iron reducers [56] and bacterial predators [57]. Margem soil’s higher nitrate concentration may impact nitrogen fixation bacteria abundance since high reactive nitrogen (nitrate, ammonium, or organic nitrogen) concentrations may inhibit the nitrogenase complex [58,59] and decrease the adaptative advantage of the diazotrophic function. Interestingly, one of the Margem indicator species belongs to a genus associated to nitrogen fixation, Mesorhizobium (reviewed in [60], [61,62]). Other indicator species for Margem, are also involved in the nitrogen metabolic cycle (*Nitrospira moscoviensis* [63]; *Neisseria cinerea* [64]; Candidatus *Nitrososphaera gargensis* [65]). The presence of microorganisms able to oxidize ammonia and nitrite, as well as nitrogen fixation may reflect the high nitrate concentration present is this terroir. Assobio is the terroir that presents the highest number of indicator functions and fungi ecological guilds with significantly higher abundances when compared to other terroirs. Some Assobio indicator species may present biocontrol roles (Collimonas fungivorans [66,67]), other less explored/known functions (*Suhomyces canberraensis* [68], *Flaviflexus ciconiae* [69], *Hygrocybe conica* [70]), and a high number of plant growth promoting species (*Paraburkholderia graminis* [71,72], Paraburkholderia phytofirmans [73,74], *Sphingobacterium multivorum* [75], *Oidiodendron maius* [76], Enterobacter sp. [ 77,78], *Talaromyces islandicus* [79]). These plant-growth promoting microbes are the main group of indicator species found in Assobio terroir. Of those, P. graminis has been shown to increase the nitrogen content of plants through an abundance increase of high-affinity nitrate transporter NAR2 and its activator, as well as increase in ammonium-inducible transporter [72]. Paraburkholderia phytofirmans colonised tomato plants showed an increase in photosynthesis and photosystem II activity even in higher temperatures [73], and P. phytofirmans volatile organic compound conferred tolerance to salinity and increased Arabidopsis growth [74]. Sphingobacterium multivorum growth promoting mechanisms are mostly indole-3-acetic acid (IAA) and siderophore production, 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity and phosphate solubilization [75]. Oidiodendron maius is an ericoid mycorrhizal fungus, with plant growth promoting activity through increased nitrogen uptake [76]. Enterobacter spp. are able to promote plant growth by aiding nitrogen fixation [77], IAA production [78] and by heavy metal removal from soil through siderophore production [77]. Talaromyces islandicus displays phosphorus solubilization activity improving maise growth and phosphorus uptake [79]. When looking at the potential indicator functions, dark iron oxidation was appointed to Assobio, a terroir with more neutral pH and high concentration of nitrate, which may explain this indicator. Some of the species identified as being able to perform iron oxidation are neutrophilic, aerobic iron-oxidizing proteobacteria or neutrophilic iron-oxidizing proteobacteria, all of which use nitrate as respiratory substrates [80]. Also, in Assobio terroir, two species of yeast were identified as indicator species. Not much is known about the species Kazachstania kunashirensis, however other species from this genus were previously reported as conferring positive aroma attributes to wine in the presence of *Saccharomyces cerevisiae* [81,82]. Suhomyces species seem to be able to convert glucose and trehalose to alcohol by fermentation, thus aiding the wine-making process [68]. In our study, several grapevine pathogens were identified, Margem soil may constitute a reservoir for grapevine trunk diseases (Eutypa lata, Lasiodiplodia theobromae, *Neofusicoccum parvum* and Botryosphaeria dothidea) and esca syndrome pathogens (Phaeomoniella chlamydospore and Phaeoacremonium minimum) based on pathogens abundance and higher mortality rate of grapevine in this terroir in the last years, further corroborating that soil may be an important source of GTD inoculum [13]. Additionally, an uncharacterized Fusarium sp. S$\frac{18}{39}$ species was found to be an indicator species for Margem terroir soils. Although many Fusarium species are grapevine pathogens [83,84], some may also have a biocontrol action against other diseases [85,86,87], thus further studies on this particular species are needed to enlighten its role within grapevine interaction. Overall, the studied microbiomes reflect the different terroirs, with the possibility to identity indicator species and function/ecologies to each terroir. In the future, taking into account that the soil is considered a plant reservoir of microorganisms, a microbiome study of the must will be interesting to better understand the microorganisms that reflect the differences in wine quality of each terroir. ## 5. Conclusions We have used a long-read sequencing approach to trace and define “microbial terroirs” at an organic vineyard at the Douro region. Our results demonstrated that the soil microbiome constitutes a terroir signature. 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--- title: Design, Synthesis, and Antiviral Activities of New Benzotriazole-Based Derivatives authors: - Roberta Ibba - Paola Corona - Francesca Nonne - Paola Caria - Gabriele Serreli - Vanessa Palmas - Federico Riu - Simona Sestito - Maria Nieddu - Roberta Loddo - Giuseppina Sanna - Sandra Piras - Antonio Carta journal: Pharmaceuticals year: 2023 pmcid: PMC10054465 doi: 10.3390/ph16030429 license: CC BY 4.0 --- # Design, Synthesis, and Antiviral Activities of New Benzotriazole-Based Derivatives ## Abstract Several human diseases are caused by enteroviruses and are currently clinically untreatable, pushing the research to identify new antivirals. A notable number of benzo[d][1,2,3]triazol-1[2]-yl derivatives were designed, synthesized, and in vitro evaluated for cytotoxicity and antiviral activity against a wide spectrum of RNA positive- and negative-sense viruses. Five of them (11b, 18e, 41a, 43a, 99b) emerged for their selective antiviral activity against Coxsackievirus B5, a human enteroviruses member among the Picornaviridae family. The EC50 values ranged between 6 and 18.5 μM. Among all derivatives, compounds 18e and 43a were interestingly active against CVB5 and were selected to better define the safety profile on cell monolayers by transepithelial resistance test (TEER). Results indicated compound 18e as the hit compound to investigate the potential mechanism of action by apoptosis assay, virucidal activity test, and the time of addition assay. CVB5 is known to be cytotoxic by inducing apoptosis in infected cells; in this study, compound 18e was proved to protect cells from viral infection. Notably, cells were mostly protected when pre-treated with derivative 18e, which had, however, no virucidal activity. From the performed biological assays, compound 18e turned out to be non-cytotoxic as well as cell protective against CVB5 infection, with a mechanism of action ascribable to an interaction on the early phase of infection, by hijacking the viral attachment process. ## 1. Introduction For centuries, infectious diseases have been the leading cause of death. Unfortunately, this sad record is still upheld today, primarily in the poorest countries; however, it was sadly proved that the pandemic risk was not negligible even in the most advanced countries and viral diseases must be considered a threat that we should not underestimate. Within the past century, multiple viruses caused pandemics across the word. It is worth mentioning the Spanish flu [1918-19], which was due to the H1N1 virus, which caused 50 million deaths [1], the Asian flu [1957], caused by the H2N2 virus [2,3], and the Hong Kong avian flu [1968], which originated from the H3N2 virus [4]. In recent history, HIV infection, causing AIDS, was arguably the most important huge viral infection, that claimed more than 36 million deaths, according to the World Health Organization (WHO) [5]. In the twenty-first century, SARS (severe acute respiratory syndrome), an atypical and particularly severe form of pneumonia, appeared in 2003 across a Chinese region and registered several cases in eight months, with a lethality rate of $10\%$; it was caused by SARS-CoV [6]. Later, in 2009, swine flu occurred across the American continent, caused by a H1N1 strain [7]. In 2012, another coronavirus, MERS-CoV, was identified as the cause of Middle East respiratory syndrome (MERS) [8]. Two years later, the *Ebola virus* was responsible for a new epidemic wave with a death rate of 50–$90\%$ [9]. Lastly, in 2019, SARS-CoV-2 circulated across the world causing the current COVID-19 pandemic [10], the effects of which we still experience. Even though the World Health Organization (WHO) undertook specific control and research programs for the most known viral infections (AIDS, hepatitis C, avian flu and Dengue fever) and their impact in terms of morbidity and mortality was significantly reduced compared to the past, they still remain important global public health challenges [11]. Numerous other infections caused by emerging viruses (Chikungunya, Zika) are considered very threatening by the WHO and, therefore, some of them were placed under observation, while some others were indicated as future risks for epidemics. Unfortunately, for most human pathogenic viruses, no vaccines or specific drugs are available, and the existing treatments are essentially symptomatic. In a few cases, targeted therapies are available (e.g., HIV, HCV), allowing access to acute and chronic treatments. Among the currently untreatable viruses, the enteroviruses family includes seven species: human enterovirus A–D (referred to as poliovirus, Coxsackievirus A, Coxsackievirus B, echovirus and enterovirus in the previous taxonomy) and rhinovirus A–C. These viruses can trigger numerous diseases such as common cold, non-differentiated febrile diseases, hand, foot, and mouth syndrome, epidemic pleurodynia, herpangina, poliomyelitis, aseptic meningitis, myocarditis, and various respiratory infections [12]. A benign prognosis was observed in most cases, but severe respiratory disturbances [12] or other serious complications, such as dilated cardiomyopathy or flaccid myelitis frequently occur in infants or immuno-compromised adults [13,14,15]. Due to their high diffusion in many states [16,17,18], surveillance programs for diseases caused by enteroviruses are active, confirming their significant incidence in both pediatric and adult populations. Recently, many studies also reported a peculiar correlation between enterovirus infections and celiac disease or diabetes [19,20], and therefore, they undergo specific surveillance [21,22,23]. With the worrying spread of enterovirus infections and the lack of targeted therapies and preventive vaccines, except for poliovirus and two inactivated enterovirus A71 only approved in China for the prevention of hand, foot, and mouth human disease [24], the search for therapeutic agents able to tackle or heal enteroviruses-caused infections is of great relevance and usefulness. Although, in recent years, many synthetic compounds showed good antiviral activity against enteroviruses, they failed to enter the clinic. For instance, pleconaril was rejected by the FDA due to a set of adverse effects, while vapendavir failed a phase IIb trial due to insufficient efficacy [25,26,27]. Hence, basic antiviral drug discovery programs still represent a valid contribution to the development of new antiviral compounds. Under such circumstances, the present study investigated the antiviral activities of newly synthesized benzotriazole derivatives on a panel of selected viruses. ## Rationale Nitrogen-based heterocycles represent a precious source of scaffolds for the development of therapeutic agents in medicinal chemistry. Most of the FDA-approved drugs possess the N-heterocycle skeleton [28], which can be differently functionalized to obtain different compounds endowed with biological properties and, therefore, various pharmacological applications [29]. A wide number of nitrogen-containing heterocyclic derivatives were recognized to exhibit a broad range of pharmacological effects [30,31,32,33,34] and were widely reported in the literature to show intriguing biological activities for these types of compounds [35,36,37]. Benzo[d][1,2,3]triazole (benzotriazole, BTZ) nucleus is a bicyclic scaffold frequently used in drug design for its proved endowment with a wide range of biological properties [38], including antibacterial and antiprotozoal [39], antimycotic [40], antimycobacterial [41,42], antitumor [43,44,45], and antiviral [46,47,48,49,50] activities, as reported in Figure 1. We previously reported different generations of BTZ-based compounds variously functionalized to exert in turn selective or wide-spectrum antiviral activity [51,52,53,54]. By screening the synthesized compounds on a panel of viruses, including representative pathogens of the Flaviviridae, Picornaviridae, Reoviridae, Rhabdoviridae, Paramyxoviridae, Poxviridae, and Herpesviridae families, we identified a number of hit compounds, whose general structures are active against three viral strains, as depicted in Figure 2: Coxsackievirus B (CVB) [51,53], respiratory syncytial virus (RSV) [54] and Orthohantavirus (HTNV) [52]. Aiming to expand the structure-analysis knowledge on these types of molecules, in this work, we present new derivatives obtained through the manipulation of our previously developed hit compounds. Notably, we previously observed that the introduction of a methylene spacer on the not active N1,N4-bis(4-(5,6-dichloro-1H-benzo[d][1,2,3]triazol-1-yl)phenyl)succinimide derivative (A, Figure 3) successfully led to N1,N4-bis(4-((5,6-dichloro-1H-benzo[d][1,2,3]triazol-1-yl)methyl)phenyl)succinimide derivative (B, Figure 3), which was active on CVB at micromolar concentration (EC50 = 23 μM) [43]. Therefore, the structural modifications were mainly focused on a) the introduction of a methylene spacer between the benzotriazole moiety and the para-substituted benzene ring and b) the position variation of the substitution on the aromatic ring, as exemplified in Figure 4. The structural manipulations were rationally designed to allow a greater degree of molecule flexibility to evaluate the effects induced by different molecular conformations. ## 2. Results Three series of derivatives were obtained starting from the plain benzotriazole scaffold, substituted in position 4, or disubstituted in positions 5 and 6 with methyl groups or halogens. Then, a 3′ or 4′ benzylamine moiety was inserted on N1 or N2 of the triazole ring. The subsequent N-functionalization of the benzylamine portion led to aliphatic amides (15e-18e, 23b, 24b, 35a, 36a, 37b, 38b, 75b-78b, 79c, 80c, 81d, 82d), aromatic amides (19e–22e, 25b-29b, 39a-48a, 49b-57b, 83b, 84b, 85c-88c, 89d-94d), and urea-derivatives (30b-34b, 58a-62a, 63b-74b, 95a-98a, 99b, 100b, 101c-103c, 104d-107d). ## 2.1. Chemistry To obtain the desired compounds, firstly, the amine intermediates were synthesized via the two-steps synthetic routes reported in Scheme 1, which yielded the uniquely aniline derivatives 5b, 6a,b, 11b, 12a–e. The appropriate benzotriazoles 1a–e were condensed with 3- or 4-nitrochlorobenzyl (2, 7, respectively) in a basic environment for Cs2CO3. The obtained products 3a,b, 4a,b, 8a–e, 9a–e, and 10e were always obtained as a mixture of isomers, which were separated by flash chromatography. Each of them was subjected to a reduction reaction with methylhydrazine in autoclave in the case of chlorinated derivatives 4a, 8a, 9a, while in all other cases, hydrated hydrazine with palladium on activated charcoal was used, refluxed in ethanol. Not all reductions were successful; the gained amines (5b, 6a,b, 11a,b,d, 12a–e) were obtained in fair to good yields. Final derivatives 23b–34b, 75b, and 76b were synthesized as reported in Scheme 2, while the remaining are presented in Scheme 3. Benzotriazol-1ylphenylamino (Scheme 3) and 2-ylphenylamino (Scheme 2) intermediates (5b, 6a,b, 11b, 12a–e) were, respectively, condensed with: i. The proper anhydride I (acetic anhydride, propionic anhydride, butyric anhydride and pivalic anhydride) at room temperature or for 1–72 h. The crude products were in turn obtained pure or required purification by flash chromatography; ii. The required benzoyl chloride derivatives II in N,N-dimethylacetamide (DMA) or N,N-dimethylformamide (DMF) at 80 °C from 3 h to 7 days. The purification of the compounds was carried out by recrystallization from ethanol or by flash chromatography; iii. The appropriate isocyanate R2N=C=O III in DMF, stirring the mixture at 100 °C from 2 to 9 days. The crude products were triturated with diethyl ether to obtain solids that were purified through recrystallization from ethanol or by flash chromatography. ## 2.2.1. Antiviral Assay All the newly synthesized compounds were tested against representative members of several RNA and DNA viruses in cell-based assays. In detail: ssRNA- viruses: vesicular stomatitis virus (VSV) (Rhabdoviridae) and respiratory syncytial virus (RSV) (Pneumoviridae); ssRNA+ viruses: BVDV and YFV (Flaviviridae) and two Picornaviridae: human enterovirus B (coxsackievirus B5, CVB5), human enterovirus C (poliovirus type-1, Sb-1); dsRNA viruses: reovirus type-1 (Reo-1) (Reoviridae); DNA virus: human herpesvirus 1 (herpes simplex type-1, HSV-1) (Herpesviridae), and *Vaccinia virus* (VV) (Poxviridae). 2’-C-methylcytidine (NM 107), 2′-C-methyl-guanosine (NM108), ribavirin, 6-azauridine, acycloguanosine (ACG), and pleconaril were used as reference compounds. Furthermore, the cytotoxicity of all compounds was also evaluated in parallel with the antiviral activity, results are reported in Table 1. Among the whole series of synthesized compounds, only about $15\%$ of which showed antiviral activity, and they were the sole reported in Table 1. The non-active compounds were withheld to simplify the table readability. Most of the appealing compounds (6a, 11b, 11d, 18e, 25b, 41a, 43a, 99b, 100b) were found selectively active against CVB5 with EC50 values ranging between 6 and 52 µM, when non-inhibitory activity against the remaining virus replication was detected. Non-substituted benzotriazole-based compound 86c was selectively active against BVDV (EC50 = 3 µM), while compound 21e preferentially inhibited RSV (EC50 = 20 µM). Overall, the most promising and effective derivatives are 18e and 43a, whose EC50 values were 12.4 and 9 µM, respectively, when tested against CVB5. To further outline the structure–activity relationships (SARs), Figure 5 reported the structures of the most active compounds together with precursors and the corresponding EC50 values. Favorable chemical manipulations are indicated with a blue arrow, while unfavorable modifications are indicated with a red one. The intermediate 6a, bearing the side chain on position C-3′, presented moderate activity towards CVB5, with an EC50 of 52 µM. Notably, the substitution of the amine group with 3,4,5-trimethoxybenzoyl or p-chlorobenzoyl groups increased the antiviral activity against the same virus, with EC50 values decreased to 18.5 and 9 µM for compounds 41a and 43a, respectively. The latter compounds bore two chlorine atoms on C-4 and C-5 of the benzotriazole scaffold (in Figure 5A). The chlorine atoms seemed to be responsible for the greater activity, since their replacement with methyl groups led to inactive derivatives 51b and 53b (data not shown). Aliphatic amides (35a and 36a) and urea derivatives (58a–62a) obtained from chlorinated intermediate 6a showed no antiviral activity (data not shown). Aromatic amide moiety is allegedly required for anti-CVB5 activity. Concerning the C-4′-aminobenzyl derivatives, dimethyl benzotriazole-based aliphatic-urea compounds 99b and 100b showed a moderate anti-CVB5 activity resulting in EC50 values of 16 and 50 µM, while corresponding aliphatic amides 77b and 78b were revealed to be inactive (in Figure 5B, data not shown). When aliphatic-urea steric hindrance was increased from 99b to 100b, activity decreased. A remarkable SAR analysis may be described when compound 21e is compared with 18e derivative. The former was active against RSV, while the latter inhibited the CVB5 viral replication. The two derivatives both shared the 4-F benzotriazole intermediate 12e, but derivative 21e carried on a trimethoxy-phenyl amide moiety, while 18e was the simplest pivalamide (in Figure 5C). Among all derivatives, we selected compounds 18e and 43a for their interesting activity against CVB5, with comparable CC50 and EC50 values, and further experiment were performed to better define the safety profile on cell monolayers by transepithelial resistance test and deeply analyze the mechanism of anti-CVB5 action. ## 2.2.2. Transepithelial–Transendothelial Electrical Resistance (TEER) Test In parallel with the low cytotoxic profile shown by our derivatives against evaluated cell lines, compounds 18e and 43a were selected to ascertain their potential toxic effect on human cells. We tested this on differentiated intestinal Caco-2 monolayers, commonly used to simulate the gut epithelium and to evaluate changes in intestinal permeability. Cells were treated with the bacterial endotoxin lipopolysaccharide (LPS) as a negative control, and it was observed that it caused permeability imbalance and a significant alteration of the cell monolayer integrity with time (Figure 6), starting from 18 h of incubation, when the TEER value was about $80\%$ of the level of the untreated cells. TEER values measured in monolayers treated with compounds 18e and 43a (20 µM), which did not significantly differ from control values throughout all the time points, showing no enhancement of cell monolayer permeability. ## 2.2.3. Protective Effect of 18e on Vero-76 Cell from CVB5 Infection Among the two interesting derivatives active against CVB5 and based on the described results, we selected compound 18e to verify whether it could hinder CVB5-induced apoptosis and preserve the monolayers viability. Vero-76 cells, growing in 12-well plates, were infected with CVB5 or left untreated. After adsorption, the cells were incubated in the absence or presence of 20 µM of compound 18e. The cells were incubated for 48 h and then stained with Annexin-V-fluorescein and propidium iodide and, subsequently, subjected to flow cytometry analysis. Figure 7 shows that CVB5 infection induced cell death mainly by apoptosis ($27.05\%$ ± 3.19 and 6.87 ± 0.29, early and late apoptotic cells, respectively), whereas in non-infected cells treated with 20 µM of compound 18e, a minimal number of early, late apoptotic and necrotic cells was detected, confirming the absence of cytotoxicity of the tested compound. In CVB5-infected cells, the administration of 18e at 20 µM concentration elicited a significant decrease in apoptotic cells (from $27.05\%$ ± 3.19 in untreated infected cells versus $6.35\%$ ± 1.47 in treated infected cells; $$p \leq 0.002$$). These results confirmed that CVB5 virus induces cell death by apoptosis and that compound 18e protects the cells from infection. ## 2.2.4. Virucidal Activity To determine whether compound 18e acts directly on the viral particle leading to infectivity inactivation, a virucidal assay against CVB5 virions was conducted. As shown in Figure 8, any virucidal effect was detected testing 18e at the concentration of 20 µM at either 4 °C or 37 °C, since no difference between the titers of CVB5 treated at the two different temperatures was recorded. These results suggested that the inhibitions detected by the plaque reduction assay, reported in Table 1, may result from the interference with a CVB5 replication cycle stage. ## 2.2.5. Time of Addition (ToA) In order to investigate the potential inhibitory mechanism for derivative 18e, a cell pre-treatment and a time course assay were performed on Vero-76 monolayers. For cell pre-treatment test, Vero cells were incubated with an active and not cytotoxic concentration of compound 18e (20 µM) for 2 h. The unbound compound was then removed, the cells infected with CVB5 for 2 h at room temperature and then washed, overlayed with new media and incubated to 37 °C for 3 days. The yield of viral particles was then determined by plaque assay and results are reported in Figure 9. Under the described experimental conditions, a decrease in viral load from 3 × 105 PFU/mL (not treated control) to 7× 104 (18e-treated) was detected. The antiviral effect was kept even in the time of addition assay when the compound 18e was added during the infection period. No titer reduction was observed adding 18e during subsequent steps of the replication cycle. These findings prompted us to hypothesize a possible inhibition during an early phase of infection, by reducing the viral attachment process to the host cell. ## 3.1. Chemistry Melting points were carried out with a Köfler hot stage or Digital Electrothermal melting point apparatus. Nuclear magnetic resonance (1H NMR and 13C NMR-APT) spectra were determined in CDCl3 or DMSO-d6 and were recorded with a Bruker Avance III 400 NanoBay. Chemical shifts are reported in parts per million (ppm) downfield from tetramethylsilane (TMS) used as the internal standard. Splitting patterns were designated as follows: s, singlet; d, doublet; t, triplet; q, quadruplet; quin, quintet; sext, sextet; sept, septet; m, multiplet; br s, broad singlet; dd, doublet of doublets. Mass spectra (MS) were performed on combined Liquid Chromatograph-Agilent 1100 series Mass Selective Detector (MSD). Analytical thin-layer chromatography (TLC) was performed on *Merck silica* gel F-254 plates. Pure compounds showed a single spot in TLC. For flash chromatography, *Merck silica* gel 60 was used with particle sizes 0.040 and 0.063 mm (230 and 400 mesh ASTM). ## 3.1.1. Starting Material and Known Intermediates Benzotriazole, 4,5-dimethylbenzotriazole, 4,5-dichloro-o-phenylendiamine, 3-nitrobenzylchloride, 4-nitrobenzylchloride, isocyanates, anhydrides, benzoyl derivatives, and inorganic compounds are commercially available. The key intermediates 3-fluorobenzene-1,2-diamine, 4-fluorobenzotriazole [41], 5,6-dichlorobenzotriazole [55], 5,6-difluorobenzotriazole [44], 3-fluorobenzene-1,2-diamine [56,57] were prepared according to the procedures described in the literature. ##### 9a–e and 10e) To a mixture of proper 5,6-dicholobenzotriazole (1a), 5,6-dimethylbenzotriazole (1b), benzotriazole (1c), 5,6-difluorobenzotriazole (1d) or 4-fluorobenzotriazole (1e) (6.79 mmol) in N,N- dimethylformamide anhydrous (DMF) or N,N-dimethylacetamide (DMA) (for 1e) (40 mL), and Cs2CO3 (6,79 mmol), a solution of 3-nitro- or 4-nitrobenzylchloride (13.6 mmol) in 10 mL of DMF or DMA was added. The mixture was stirred and heated to 70 °C for 7 days (3a, b; 4a, b), for 27 h (8a, c; 9a, c), or for 96 h (8b; 9b), 60 °C for 6 days (8d; 9d), and to 50 °C for 3 h (8e, 9e, 10e). After cooling to room temperature, the solution was filtered off in vacuo to remove the Cs2CO3 and the mothers were diluted with water until complete precipitation of the products. The filtered solid was in all cases a 1:3 mixture of two isomers (3a and 4a; 3b and 4b; 8a and 9a; 8b and 9b; 8c and 9c; 8d and 9d) or three isomers (8e, 9e, 10e). The pairs of isomers were separated and purified by flash chromatography using a mixture of petroleum ether and ethyl acetate in $\frac{8}{2}$ or $\frac{7}{3}$ (for 8a, 9a and 8e, 9e, 10e) ratio. For all pairs of isomers, the first isomer to be eluted was the N-2 derivative. ## 3.1.3. General Procedure to Obtain 4-((5,6-R-1H-benzo[d][1,2,3]triazol-1-yl)methyl)aniline 5b, 6b, 11b, 11d, 12b, 12c, 12e To a mixture of proper nitrobenzyl-benzotriazole 3b, 4b, 8b, 8d, 9b, 9c, and 9e (1.77 mmol) in ethanol (20–30 mL), and hydrated hydrazine in ratio 1:10 (17.7 mmol), $10\%$ Palladium on activated charcoal was added. The mixture was stirred and heated at 80 °C for: 15 min (6b, 11d), 1h (5b, 11b, 12b, 12c) and at 90 °C for 1.5 h (12e). After removal of palladium on carbon by filtration, in the case of 12b, 12c, the mothers obtained were concentrated into half volume. By cooling down, the resulting solid was filtered and washed twice with diethyl ether (20 mL) and, subsequently, crystallized from ethanol. In all other cases, the filtered mothers were evaporated under vacuum to obtain: the amine 5b, 6b, and 11b as unit products, while the products 11d and 12e were purified by flash chromatography using dichloromethane/ethyl acetate 8:2 (12e) or petroleum ether/ ethyl acetate 7:3 (11d) as eluting system. ## 3.1.4. General Procedure to Obtain 4(3)-((5,6-dichloro-1(2)H-Benzo[d][1,2,3]Triazol-1(2)-yl)methyl)aniline 6a, 11a, 12a, and 12d Derivatives 4a, 8a, 9a, and 9d, (3.09 mmol) were solubilized in ethanol (100 mL) and reduced with methylhydrazine in $\frac{1}{10}$ molar ratio, at 100 °C in autoclave for 48 h. The solution was concentrated under vacuum to half the volume and cooled in the freezer to separate compound 6a as a pure solid. In the case of 11a, 12a, and 12d, mother liquors were evaporated under reduced pressure and the crude products were purified by flash chromatography using an $\frac{8}{2}$ mixture of petroleum ether/ethyl acetate. From derivative 3a, it was not possible to obtain the corresponding amine 5a which was debenzylated in each tested reaction condition. ## 3.1.5. General Procedure for the Preparation of Amides 15e–18e, 23b, 24b, 35a, 36a, 37b, 38b, 75b–78b, 79c, 80c, 81d, 82d A total of 1.2 mmol of appropriate benzylamine (5b, 6a, 6b, 11b, 12b, 12c, 12d, and 12e) were dissolved in 3 mL of the required anhydride I (acetic anhydride, propionic anhydride, butyric anhydride and pivalic anhydride). The resulting mixture was stirred at room temperature for 1 h (15e-17e) or for 24 h (18e), at 50 °C for 2 h (37b, 38b), at 100 °C for 1 h (75b, 77b, 78b, 79c, 81d), for 24 h (23b, 24b, 35a, 36a, 76b, 80c), or for 72 h (82d). Then, it was cooled to room temperature and rushed ice was added. The solid obtained in each reaction was filtered under vacuum to furnish the amide derivatives. Some products were obtained pure (16e, 17e, 24b, 36a, 37b, 38b, 75b-78b, 79c, 80c, 81d, 82d), while others required purification by flash chromatography using an appropriate eluting system as specified below: a 7:3 mixture of dichloromethane/ethyl acetate (15e), mixture of petroleum ether/ethyl acetate 7:3 (18e), $\frac{8}{2}$ (35a), $\frac{6}{4}$ (23b, 78b). ## 3.1.6. General Procedure for the Preparation of Amides 19e–22e, 25b–29b, 39a–48a, 49b–57b, 83b, 84b, 85c–88c, 89d–94d To a solution of appropriate anilines (5b, 6a, 6b, 12b, 12c, 12d, 12e), (1.19 mmol) in N,N-dimethylacetamide (DMA) or N,N-dimethylformamide (DMF) (5–7 mL) was added by dripping an equimolar amount (19e-22e) or an excess of $20\%$ in all other cases of the required benzoyl chloride derivatives II in 3 mL of DMF. The solution was stirred at 80 °C for different times as reported below: 3 h (20e, 21e, 22e), 24 h (19e, 26b, 27b, 29b, 39a-46a, 49b, 52b, 54b, 57b, 87c, 88c, 92d), 48 h (50b, 57b, 90d, 93d), 72 h (25b, 28b, 53b, 56b, 91d), 96 h (84b, 85c), 120 h (47a, 86c), 7 days (55b, 83b, 89d, 94d). Then, it was cooled to room temperature and rushed ice was added. The solid obtained in each reaction was filtered under vacuum. The purification of the compounds was carried out by crystallization from ethanol (27b-29b, 39a, 40a, 44a-47a, 51b, 53b) or by flash chromatography using as eluting system a mixture of petroleum ether/ ethyl acetate $\frac{6}{4}$ (20e, 83b, 84b) $\frac{4}{6}$ (85c, 87c) $\frac{7}{3}$ (25b, 26b, 41a-43a, 49b, 50b, 52, 54b-57b, 86c, 88c, 92d–94d); dichloromethane/ethyl acetate $\frac{9}{1}$ (19e, 21e, 22e); chloroform/methanol $\frac{9}{1}$ (90d, 91d). ## 3.1.7. General Procedure for the Preparation of Urea-Derivatives 30b–34b, 58a–62a, 63b–74b, 95a–98a, 99b–100b, 101c–103c, 104d–107d To a stirred solution of corresponding amines 5b, 6a, 6b, and 12a-d (1.18 mmol) in anhydrous N,N-dimethylformamide (DMF) (7 mL), the required isocyanate III (ratio 1:2 + $20\%$) dissolved in DMF (3 mL) was added. The mixture was stirred at 100 °C for a variable time from 2 to 9 days: 2 (67b, 104d), 3 (34b, 95a, 105d), 4 (33b, 63b, 65b, 66b, 68b-74b, 96b-98b), 5 (59a, 61a, 99b, 100b, 101c-103c), 6 (31b, 32b, 64b, 106d), 7 (58a, 107d), 9 (30b, 60a, 62a). The reaction mixtures were evaporated to dryness. The crude products were triturated with diethyl ether to obtain solids that were purified through recrystallization from ethanol or, in some cases by flash chromatography using a mixture of diethyl ether and light petroleum as eluents, in ratio v/v of $\frac{7}{3}$ (99b, 100b), $\frac{8}{2}$ (101c, 102c), $\frac{1}{1}$ (103c), or light petroleum and ethyl acetate $\frac{6}{4}$ (62a, 68b, 97a, 104d). ## 3.2.1. Cells and Viruses Cell lines were purchased from American Type Culture Collection (ATCC). The absence of mycoplasma contamination was determined periodically by the Hoechst staining method. Cell lines supporting the multiplication of RNA and DNA viruses were the following: Madin Darby Bovine Kidney (MDBK) [ATCC CCL 22 (NBL-1) Bos Taurus]; Baby Hamster Kidney (BHK-21) [ATCC CCL 10 (C-13) Mesocricetus auratus]; Monkey kidney (Vero-76) [ATCC CRL 1587 Cercopithecus Aethiops]. Viruses were purchased from American Type Culture Collection (ATCC), with the exception of yellow gever virus (YFV). Viruses representative of positive-sense, single-stranded RNAs (ssRNA+) were: (i) Flaviviridae: yellow fever virus (YFV) [strain 17-D vaccine (Stamaril Pasteur J07B01)] and bovine viral diarrhea virus (BVDV) [strain NADL (ATCC VR-534)]; (ii) Picornaviridae: human enterovirus B [coxsackie type B5 (CVB5), strain Faulkner (ATCC VR-185)], and human enterovirus C [poliovirus type-1 (Sb-1), Sabin strain Chat (ATCC VR-1562)]. Viruses representative of negative-sense, single-stranded RNAs (ssRNA-) were: (iii) Pneumoviridae: human respiratory syncytial virus (RSV) strain A2 (ATCC VR-1540); (iv) Rhabdoviridae: vesicular stomatitis virus (VSV) [lab strain Indiana (ATCC VR 1540)]. The virus representative of double-stranded RNAs (dsRNA) was: (v) Reoviridae Reovirus type-1 (Reo-1) [simian virus 12, strain 3651 (ATCC VR-214)]. DNA virus representatives were: (vi) Poxviridae: *Vaccinia virus* (VV) [vaccine strain Elstree-Lister (ATCC VR-1549)]; (vii) Herpesviridae: human herpes 1 (HSV-1) [strain KOS (ATCC VR-1493)]. Viruses were maintained in our laboratory and propagated in appropriate cell lines. All viruses were stored in small aliquots at −80 °C until use. ## 3.2.2. Cytotoxicity Assay MDBK and BHK-21 cells were seeded at an initial density of 6 × 105 and 1 × 106 cells/mL, respectively, in 96-well plates containing minimum essential medium with Earle’s salts (MEM-E), l-glutamine, 1 mM sodium pyruvate and 25 mg/L kanamycin, supplemented with $10\%$ horse serum (MDBK) or $10\%$ fetal bovine serum, FBS (BHK-21). Vero-76 cells were seeded at an initial density of 5 × 105 cells/mL in 96-well plates containing in Dulbecco’s modified eagle medium (D-MEM) with l-glutamine and 25 mg/L kanamycin, supplemented with $10\%$ FBS. Cell cultures were then incubated at 37 °C in a humidified, $5\%$ CO2 atmosphere, in the absence or presence of serial dilutions of test compounds. The test medium used for cytotoxic and antiviral assay contained $1\%$ of the appropriate serum. Cell viability was determined after 72 or 96 h at 37 °C by the MTT method for MDBK, BHK-21 and Vero-76 cells [58]. ## 3.2.3. Transepithelial Electrical Resistance (TEER) Assay The cytotoxicity of the compounds 18e and 43a was tested on intestinal epithelial cell by estimating the TEER (Transepithelial Electrical Resistance) values as a measure of cell monolayer integrity. Caco-2 cells (ECACC Salisbury, Wiltshire UK) were cultured in Dulbecco’s modified eagle’s medium (DMEM), supplemented with $10\%$ heat-inactivated bovine serum, 100 U/mL penicillin, 2 mM l-glutamine, $1\%$ non-essential amino acids, and 100 mg/mL streptomycin at 37 °C in a humidified atmosphere of $5\%$ CO2, replacing the medium twice a week [59]. All cell culture materials were purchased from Euroclone (Milan, Italy). Caco-2 cells (5 × 104 cells/well), at passage 31–40, were grown in 12 mm i.d. Transwell inserts (polycarbonate membrane, 0.4 µm pore size) (Corning Costar Corp., New York, NY, USA) and culture medium was dispensed both in the apical (0.5 mL) and in the basolateral (1.5 mL) compartment of each well. Resistance was assessed using Millicell–ERS voltohmmeter (Millicell-ERS system, Millipore, Bedford, MA, USA). After cell differentiation (>14 days), only cell monolayers in inserts with TEER values >300 Ω/cm2 were considered for the experiment [60]. Then, the compounds 18e and 43a (final concentration 30 µM) and, as a proinflammatory agent, the Gram-negative endotoxin lipopolysaccharide (LPS, 100 µg/mL) were added in the culture medium and TEER values were measured at intervals of 3, 18, 24, 36, 48, 60, and 72 h and reported as percentage of the corresponding TEER value at time zero ($T = 0$). ## 3.2.4. Apoptosis Assay To evaluate the levels of apoptosis following 18e derivative treatment, a flow cytometric analysis, using the cell apoptosis kit Annexin V/Propidium Iodide (PI) double staining uptake (Invitrogen, Life Technologies, Italy), was used. Vero-76 cells, at the density of 3 × 105 cells/mL, were seeded in 12-well plates (Corning, New York, NY, USA) with complete medium (described in the cell culture section). After CV-B5 viral adsorption, the cells were incubated in the absence or presence of different concentrations of 18e for 48 h, until the cytopathic effect CPE of the virus control reached 70–$80\%$. Cells were then washed once with PBS 1 X and re-suspended in 100 μL of Annexin binding buffer plus 1 μL of Annexin V and 1 μL of PI. Then, the reaction was performed in the dark for 15 minutes at room temperature. Stained cells were then analyzed by flow cytometry, measuring the fluorescence emission at 530 and 620 nm using a 488 nm excitation laser (MoFloAstrios EQ, Beckman Coulter, Pasadena, CA). Cell apoptosis was analyzed using the software Summit Version 6.3.1.1, Beckman Coulter. ## 3.2.5. Antiviral Assay Compound’s activity against YFV and Reo-1 was based on inhibition of virus-induced cytopathogenicity in BHK-21 cells acutely infected with a m.o.i. of 0.01. Compound’s activity against BVDV was based on inhibition of virus-induced cytopathogenicity in MDBK cells acutely infected with a m.o.i. of 0.01. After a 3- or 4-day incubation at 37 °C, cell viability was determined by the MTT method, as described by Pauwels et al. [ 1988]. The compound’s activity against CVB5, Sb-1, VSV, VV, RSV A2, and HSV-1 was determined by plaque reduction assays in infected cell monolayers, as described by Sanna et al. [ 61]. ## 3.2.6. Virucidal Activity Assay Benzotriazole derivatives (20 µM) were incubated with 1 × 105 PFU/mL of CVB5, at either 4 or 37 °C for 1 h. The mix without test sample was employed as a control. After incubation period, samples were serially diluted in media and titers were determined on Vero-76 cells CVB5 at high dilutions, at which the derivative was not active. Titers were then determined by plaque assay in Vero-76 cells. ## 3.2.7. Cell Pre-Treatment Assay The monolayers of Vero-76 cell seeded in 24-well plates were incubated with 20 µM concentration of compound 18e for 2 h. After the removal of the test compound and two washes, the cells were infected with CVB5. After the adsorption of the virus to the cells, the inoculum was removed and the monolayers were overlaid with fresh medium, incubated for 3 days at 37 °C, and then virus titers were determined by plaque assay. ## 3.2.8. Time of Addition Assay The monolayers of Vero-76 cells seed in 24-well tissue culture plates were infected for 1 h at room temperature with CVB5 dilutions to give final m.o.i. of 1. After adsorption, the monolayers were washed two times with D-MEM medium with l-glutamine, supplemented with $1\%$ inactivated FBS, 1 mM sodium pyruvate and 0.025 g/L kanamycin (maintenance medium), and incubated with the same medium at $5\%$ CO2 and 37 °C (time zero). Vero-76 cells CVB5 were treated with benzotriazole derivative (20 μM) or reference for 1 h during infection period (at -1 to 0) and at specific time point, 0 to 2, 2 to 4, 4 to 6, post infection. After incubation period, the monolayers were washed two times with maintenance medium and incubated with fresh medium until 12 h post infection. Then, the plates were frozen at −80 °C and the viral titers were determined by plaque assay. ## 3.2.9. Statistical Analysis All biological experiments were independently repeated at least three times. The data are reported as mean ± standard deviation (SD). The statistical significance (** $$p \leq 0.002$$) was performed in GraphPad Prism (San Diego, CA, USA.) ## 3.3. Experimental The chemical characterization of the selected and deeply analyzed compounds 18e and 43a are reported below, all the other compounds’ analysis can be found in the Supplementary Material. N-(4-((4-fluoro-1H-benzo[d][1,2,3] triazol-1-yl)methyl)phenyl)pivalamide (18e) Compound 18e was obtained, in $19\%$ total yield; mp: 160–163 °C; TLC (petroleum ether/ethyl acetate $\frac{7}{3}$) Rf: 0.23. 1H NMR (400 MHz, DMSO-d6) δ: 9.22 (1H, br s, NH), 7.67 (1H, d, $J = 8.4$ Hz, H-7), 7.62 (2H, d, $J = 8.4$ Hz, H-3’,5’), 7.55-7.50 (1H, m, H-6), 7.30 (2H, d, $J = 8.4$ Hz, H 2’-6’), 7.23 (1H, t, H-5), 5.94 (2H, s, CH2), 1.19 (9H, s, 3CH3). 13C-NMR (DMSO-d6) δ: 26.97 (3CH3), 50.87 (CH2), 107.23 (CH), 108.63 (CH), 119.04 (2CH), 128.14 (2CH), 128.63 (CH), 129.93 (C), 135.20 (C), 135.37 (C), 139.00 (C), 150.81 (C), 153.35 (C), 176.97 (C). LC/MS: m/z 327 [M+H]+. N-(3-((5,6-dichloro-1H-benzo[d][1,2,3]triazol-1-yl)methyl)phenyl)-4-chlorobenzamide (43a) Compound 43a was obtained, in $15\%$ total yield; mp: 213–214 °C; TLC (petroleum ether/ethyl acetate $\frac{7}{3}$) Rf: 0.47. 1H NMR (400 MHz, DMSO-d6) δ: 10.32 (1H, s, NH), 8.52 (1H, s, H-4), 8.4 (1H, s, H-7), 7.93 (2H, d, $J = 8.4$ Hz, H-2”,6”), 7.73 (1H, d, $J = 7.8$ Hz, H-4′), 7.68 (1H, s, H-2′), 7.59 (2H, d, $J = 8.8$ Hz, H-3”,5”), 7.36 (1H, t, $J = 8.0$ Hz, H-5′), 7.15 (1H, d, $J = 6$,8 Hz, H-6′), 6.00 (2H, s, CH2). 13C-NMR (DMSO-d6) δ:164.46 (CO), 144.25 (C), 139.42 (C), 136.42 (C), 135.93 (C), 133.40 (C), 132.08 (C), 130.79 (C), 129.59 (2CH), 129.13 (CH), 128.40 (2CH), 127.24 (C), 123.23 (CH), 120.64 (CH), 120.13 (CH), 119.33 (CH), 112.51 (CH), 51.14 (CH2). LC/MS m/z 415, 417 [M+H]+. ## 4. Conclusions In this work, we reported the synthesis and characterization of a large series of benzotriazole-based derivatives variously functionalized on the main core and equipped with an aromatic or aliphatic chain. Compounds were assayed against a wide panel of viruses and the obtained results allowed a SARs analysis to highlight the moieties eventually endowed with antiviral activity. Most of the active compounds showed a specific activity against CVB5. Notably, derivative 18e was found to be endowed with a considerable anti-enteroviral activity coupled with a cytotoxic profile in the high micromolar range and was selected to deepen its mechanism of action. TEER experiment was run on human epithelial cells and the results confirmed the safety of compound 18e. When analyzed in apoptotic assay, this derivative protected cells from the CVB5-induced apoptosis. In the following time course assay, our compound displayed its utmost activity during the pre-treatment and infection period. So far, these findings prompted us to speculate on the main involvement of 18e during the entry process of the virus and suggested our benzotriazole derivative as a potential anti-CVB5 agent worth investigating and optimizing further. ## Figures, Schemes and Table **Figure 1:** *Previously reported benzotriazole-based compounds with biological activities, BTZ1 [41], BTZ2 [42], BTZ3 [43], BTZ4 [44], BTZ5 [46], BTZ6 [47], BTZ7 [48].* **Figure 2:** *General structures of our benzotriazole-based antiviral compounds: series (A), active against CVB (EC50 values between 8–10 µM) and RSV (EC50 values 3–7 µM). Series (B), active on HTNV (EC50 < 5 µM), CVB (EC50 values between 4–8 µM) and RSV (EC50 values 2–3 µM) [51,52,53,54].* **Figure 3:** *The precursor N1,N4-bis(4-(5,6-dichloro-1H-benzo[d][1,2,3]triazol-1-yl)phenyl)succinamide (A) and its active derivative N1,N4-bis(4-((5,6-dichloro-1H-benzo[d][1,2,3]triazol-1-yl)methyl)phenyl)succinamide (B).* **Figure 4:** *Structural modifications on our hit compounds: introduction of a methylene bridge (red) and displacement of the substituent on the benzene ring (blue).* **Scheme 1:** *General procedure for intermediates compounds: 3a, b; 4a,b; 5b; 6a,b; 8a–e; 9a–e; 10e, 11a,b,d; 12a–e Reaction conditions: I, from 1a,b, anhydrous N,N-Dimethylformamide (DMF) or N,N-dimethylacetamide (DMA), Cs2CO3 at $t = 50$/70 °C; ii, from 1a–e, ethanol, hydrated hydrazine in molar ratio 1:10, $10\%$ palladium on activated charcoal at $t = 80$/90 °C or methylhydrazine in 1:10 molar ratio, at 100 °C in autoclave for 48 h.* **Scheme 2:** *I. stirred at r.t.; II. DMA or DMF at 80 °C; III. DMF at 100 °C. General procedure to obtain the final compounds: amides 23b–29b, 75b, and 76b and urea-derivatives 30b–34b were obtained by using benzotriazol-2-ylphenylamino derivatives 5b and 11b as starting compounds.* **Scheme 3:** *I. stirred at r.t.; II. DMA or DMF at 80 °C; III. DMF at 100 °C. General procedure to obtain the final compounds: Amides 15e–22e, 35a, 36a, 37b, 38b, 39a–48a, 49b–57b, 77b, 78b, 79c, 80c, 81d, 82d, 83b, 84b, 85c–88c, 89d–94d. Urea-derivatives 58a–62a, 63b–74b, 95a–98a, 99b, 100b, 101c–103c, 104d–107d were gained by using benzotriazol-1ylphenylamino derivatives 6a, 6b, 12a–e as starting compounds.* **Figure 5:** *(A–C) SARs analysis from the synthetized compounds.* **Figure 6:** *Evaluation of cell monolayer permeabilization as transepithelial electrical resistance (TEER) assay. Caco-2 cell monolayers were incubated with LPS at 1 μg/mL (black squares) as negative control, compound 18e at 20 µM (blue triangles), compound 43a at 20 µM (green triangles), and Control (red circles) as positive control. Statistically significant differences are expressed as follows: * = $p \leq 0.05$ LPS/Control; *** = $p \leq 0.001$ LPS vs. Control. Each value represents the mean ± SD of independent experiments ($$n = 3$$).* **Figure 7:** *Derivative 18e protected Vero 76 cells from apoptosis induced by CVB5 infection. The percentage of live, apoptotic, and necrotic cells were measured by flow cytometry using the PI-annexin V assay. The graph shows the percentage of live, apoptotic, and necrotic cells. Each value represents the mean ± SD of independent experiments ($$n = 3$$).* **Figure 8:** *Virucidal activity (expressed as plaque-forming units (PFU/mL) of benzotriazole 18e (20 µM) against CVB5 infectivity at either 4 °C or 37 °C for 2 h. 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--- title: Clinical Application of Intravitreal Aflibercept Injection for Diabetic Macular Edema Comparing Two Loading Regimens authors: - Yoo-Ri Chung - Kyung Ho Lee - Kihwang Lee journal: Medicina year: 2023 pmcid: PMC10054468 doi: 10.3390/medicina59030558 license: CC BY 4.0 --- # Clinical Application of Intravitreal Aflibercept Injection for Diabetic Macular Edema Comparing Two Loading Regimens ## Abstract Background and Objectives: We investigated and compared the efficacy of three and five monthly loading regimens of an intravitreal aflibercept injection (IVA) in patients with diabetic macular edema (DME). Materials and Methods: This was a retrospective study that included patients diagnosed with DME and treated with an either three or five monthly aflibercept loading regimen from July 2018 to March 2022. Information on clinical characteristics and changes in the central retinal thickness (CRT) were obtained from medical records. Results: In total, 44 eyes of 44 patients with DME treated with IVA were included in this study, with 30 eyes treated with 3-monthly loadings (three-loading group) and 14 eyes with 5-monthly loadings (five-loading group). The mean CRT significantly decreased from the baseline one month after loading in both the three-loading and five-loading groups ($p \leq 0.001$). Four cases were refractory to treatment in the three-loading group, while there were no cases of refractory DME in the five-loading group. The stability rate was significantly higher in the five-loading group at three months after loading ($$p \leq 0.033$$). Conclusions: Five-monthly loading regimens of IVA might be favorable for DME considering the rate of refractory cases, stable duration, and the importance of early responsiveness to IVA in DME. ## 1. Introduction Diabetic macular edema (DME) is one of the main causes of chronic visual impairment and vision loss in the working adult population with diabetic retinopathy (DR) [1]. The prevalence of diabetes mellitus (DM) is increasing worldwide, leading to an increase in the incidence of DR and DME. The International Diabetes Federation estimated the number of individuals with DM to be 463 million in 2019 and projected it to be 700 million by 2045 [2]. In 2020, the numbers of adults with DR and DME were estimated to be 103.12 million and 18.83 million, respectively; by 2045, the numbers are projected to increase to 160.50 million and 28.61 million [3]. Complications of proliferative DR that also cause vision loss in patients with DM include vitreous hemorrhage, tractional retinal detachment, and proliferative vitreoretinopathy [4]. Vascular endothelial growth factor commonly acts on the above complications [4,5,6]. Currently, the most widely used treatment for DME is an intravitreal injection of anti-vascular endothelial growth factor (VEGF) [6]. The three anti-VEGF agents ranibizumab, bevacizumab, and aflibercept have proven to be effective in treating DME and improving visual acuity [7,8,9]. Among these anti-VEGF agents, aflibercept (which has a longer acting duration than that of the other anti-VEGF agents) has been approved for the treatment of DME based on the results of several landmark studies [10,11]. However, the study design of the initial loading regimen differed between studies. The VISTA and VIVID studies showed significantly better functional and anatomical outcomes after an aflibercept administration every four or eight weeks after five initial monthly injections than those after laser photocoagulation [12]. In the DA VINCI study, aflibercept was initiated with three monthly doses and then administered as needed (PRN; Pro Re Nata), showing consistent results with an administration of aflibercept every 4 weeks [13]. Furthermore, the one-year results of protocol T showed an improvement of 13.3 letters in the mean visual acuity letter score from the baseline to one year, with six initial monthly doses followed by PRN dosing [7]. Based on these clinical trials and subsequent studies, many experts agree that DME treatment by blocking VEGF typically requires several monthly doses at the beginning to maximize the clinical outcomes over time [14]. There is no consensus on the efficacy of loading doses and the cost-effectiveness of repeat injections due to the lack of studies that directly compare the effects of aflibercept injections after loading. A recent review revealed that the criteria on loading frequency varied by study, ranging from three to six consecutive monthly injections [15]. The national health insurance system in South Korea allowed only three consecutive injections of anti-VEGF agents for DME patients until the year 2019. The five-consecutive loading regimen was covered by the national health insurance system in South Korea starting in the year 2020. The purpose of this study was to compare the two regimens to identify any benefits of five loading injections despite clinical and economic burdens. Accordingly, we conducted this study to identify an effective treatment method by examining the clinical features and results of patients who initially received three or five monthly injections of aflibercept. ## 2. Materials and Methods The medical records of patients diagnosed with DME and treated with a three- or five-monthly loading regimen of aflibercept (Eylea®; Bayer HeathCare, Berlin, Germany) at the Ophthalmology Department of Ajou University Hospital from July 2018 to April 2021 were retrospectively reviewed. This study was approved by the Institutional Review Board of Ajou University Hospital, Suwon, Korea (IRB No.: AJIRB-MED-MDB-21-707) and complied with the Declaration of Helsinki. DME was identified by optical coherence tomography (OCT) using a Heidelberg SPECTRALIS® OCT device (Heidelberg Engineering, Heidelberg, Germany). The CRT was defined as the distance from the hyperreflective line of the internal limiting membrane to the hyperreflective line of the retinal pigment epithelium (Bruch’s membrane) complex [16] and was obtained using the automatically generated thickness map protocol of the OCT device. Representative cases are presented in the Supplementary Materials (Figure S1). DME was defined as CRT ≥320 μm in men or ≥305 μm in women on OCT [9]. The exclusion criteria were as follows: [1] age < 20 years, [2] macular edema suspected to originate from factors other than DME, [3] a history of pars plana vitrectomy, [4] prior intravitreal anti-VEGF injection within two months, [5] prior steroid injection (intravitreal or posterior sub-Tenon) within six months, [6] focal/grid photocoagulation or panretinal photocoagulation within the previous six months, [7] active intraocular inflammation or infection in either eye, and [8] uncontrolled glaucoma in either eye. Only one eye was randomly selected and enrolled in the current study if a patient received an intravitreal aflibercept injection (IVA) in both eyes. Medical history, clinical characteristics, and information regarding current diabetic medications were obtained from individuals’ medical records. Blood pressure was measured during each injection visit (including both systolic and diastolic values). Glycated hemoglobin (HbA1c) data were collected from the preceding three months prior to the first IVA, and the DR grade was assessed using fundus photographs and fluorescein angiography findings. IVA (2 mg/0.05 mL) was administered in a standard manner by one of the three participating retinal specialists. A baseline OCT was performed in the week before the initial loading IVA and was repeated one month after the last loading IVA. Refractory DME was defined as a CRT decrease <$10\%$, the occurrence of new subretinal fluid (SRF) and/or intraretinal fluid (IRF), or a lesion of SRF or IFR found after loading injections. As the number of loading injections differed by groups, the follow-up months were counted from the last loading injection (Figure 1). All patients underwent ophthalmic examinations at every monthly visit, including a slit lamp examination, dilated fundus examination, intraocular pressure measurement, and OCT. An additional treatment was performed if necessary according to the retreatment criteria of [1] CRT at one month after IVA loading ≥320 μm (male) or ≥305 μm (female); [2] if CRT increased by more than $10\%$ compared to CRT at one month after IVA loading; and [3] new SRF or IRF. If the OCT findings did not meet the retreatment criteria, they were defined as “stable”. The stability rate was defined as the proportion of “stable” eyes at each time point. Additional treatments included aflibercept and other anti-VEGF agents, the administration of steroids, focal lasers, or vitrectomy according to the clinical judgement of each clinician. All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM SPSS, IBM Corp., Armonk, NY, USA). The chi-square test and independent t-test were used to compare categorical and continuous variables, respectively. A paired t-test was used to detect changes in numerical values at each time point of the study relative to the baseline values within the groups. A repeated-measures analysis of variance (ANOVA) test was performed to verify differences in the changes in CRT between the 3-loading and 5-loading groups. Logistic regression analysis was performed to identify factors associated with a stable status following loading injections: this is presented as the odds ratio with a $95\%$ confidence interval and p value. Statistical significance was set at a p value < 0.05. ## 3. Results In total, 44 eyes from 44 patients with DME were included in this study. Among these eyes, 30 were treated with 3 IVA loading regimens and 14 were treated with 5 IVA loading regimens. The mean age was 57.7 ± 11.8 years (range: 39–85). The demographic characteristics of the patients are summarized in Table 1. The use of dipeptidyl peptidase-4 (DPP-4) inhibitors was more frequent among antidiabetic medications in the three-loading group, but there were no significant differences in the baseline characteristics, such as the duration of diabetes or HbA1c level. There was no statistically significant difference in initial CRT between the two groups ($$p \leq 0.437$$). The mean CRT decreased from 490.8 ± 123.5 μm at the baseline to 308.2 ± 89.1 μm at one month after loading in the three-loading group ($p \leq 0.001$), whereas it decreased from 461.4 ± 95.1 μm at the baseline to 320.9 ± 65.2 μm at one month after loading in the five-loading group ($p \leq 0.001$). Four cases were resistant to treatment in the three-loading group, while there were no resistant cases in the five-loading group. The stability rate was significantly higher in the five-loading group at three months after loading ($$p \leq 0.033$$); however, there was no significant difference detected thereafter (Figure 2, Table 2). Time to recurrence was longer in the five-loading group compared to that in the three-loading group, although the difference was not significant (152.2 ± 62.6 vs. 116.6 ± 64.6 days, $$p \leq 0.156$$). There was a statistically significant difference in the total number of IVAs administered (including initial loading between the two groups) (4.2 ± 1.5 in three-loading vs. 6.1 ± 0.9 five-loading; $p \leq 0.001$), but there was no difference in the number of additional IVAs administered during the 6 months after the initial loading therapy. Logistic regression analysis indicated that the CRT reduction rate was a significant factor for stabilization for three months after loading (odd ratio 1.067, $95\%$ confidence interval 1.010–1.128, $$p \leq 0.021$$), while there were no significant variables for six months stabilization (Table 3). There were no specific antidiabetic medications associated with the stabilization of DME. ## 4. Discussion DME is a chronic and sight-threatening disease that significantly impacts quality of life [17,18]. Microvascular abnormalities and occlusions due to chronic hyperglycemia are considered the main etiologies of DME, which is associated with various growth factors. Among these growth factors, VEGF causes an abnormal occlusive function of the inner blood–retinal barrier and causes an accumulation of extracellular interstitial fluid [19,20]. Since anti-VEGF agents were introduced based on the mechanisms of DME, intravitreal injections of anti-VEGF agents have replaced laser photocoagulation as the standard treatment for most DME patients [6]. Aflibercept is a widely used anti-VEGF agent for DME and is active longer after administration than other such drugs [10]. In this study, both the three and five initial loading regimens of aflibercept were effective for the treatment of DME. The non-recurrence rate at three months after loading was significantly higher in the five-loading group than that in the three-loading group. Although not statistically significant, this tendency persisted for six months. The difference between the two groups decreased with time and was almost the same at six months after loading. This trend suggests that an initial five-loading might be more effective than three-loading in the short term, but the effect gradually decreases over time in both groups. Six months after the loading treatment, an additional treatment was required in approximately two-thirds of the patients in both groups. It is believed that a larger number of loading injections might lead to a smaller number of refractory DME patients and longer stable periods without the recurrence of DME, which is important for optimal improvement in visual acuity through an early intervention. Moreover, large fluctuations in macular thickness are associated with poorer visual outcomes in eyes with DME treated with anti-VEGF injections [21,22]. Reducing the variability in DME based on macular thickness is a benefit of a five-loading regimen and can result in better visual outcomes in the long term. Although shown to be effective for DME, IVA does not evoke a response in all cases. A post hoc analysis of Protocol T evaluated the proportion of eyes with persistent DME after 24 weeks of treatment with aflibercept, bevacizumab, or ranibizumab [23]. Persistent DME for 24 weeks was less likely with aflibercept than with bevacizumab or ranibizumab; however, $31.6\%$ of eyes did not show an adequate response to aflibercept [23]. In this study, we found four refractory cases of DME, all of which were in the three-loading group. We cannot be $100\%$ sure that these refractory cases might have responded if treated with a five-loading regimen; however, the absence of refractory cases in the five-loading group is worth considering when determining the proper loading regimen for DME. Aflibercept showed good effects when replacing bevacizumab or ranibizumab in refractory DME [24]. A recent Diabetic Retinopathy Clinical Research (DRCR) study reported no significant differences in 2-year visual outcome for DME between aflibercept monotherapy and bevacizumab replaced with aflibercept, suggesting a rescue effect of later applied IVA [25]. However, in cases that do not respond to IVA, alternative methods such as steroids, laser treatment, or even surgery may be needed to treat the DME [15,26]. Of the four refractory cases presented in our study, two were treated with focal laser photocoagulation, while the others received intravitreal corticosteroid injections. In one patient treated with steroids, vitrectomy was performed for resistant DME. The prevalence of DME is increasing, highlighting the need for long-term treatment and placing significant burden on patients and insurance costs. DME is not only a chronic disease but it also occurs in both eyes in most cases; therefore, it is essential to find an effective and economical treatment regimen. There are many variations in initial treatment schedules, including 3 to 6 monthly consecutive anti-VEGF injections [15]. Furthermore, many strategies were studied to maintain and maximize the effect of anti-VEGF treatment after the loading period. A fixed bimonthly or a pro-re-nata regimen (based on strict monitoring and retreatment criteria, as stated in the DRCR.net protocol T) is recommended [14]. Treat-and-extend therapy is also a recommended regimen with non-inferior visual and anatomical improvement in DME compared to fixed dosing regimens [27,28], while less visual improvement was noted when the longest treatment interval was 16 weeks [29]. Despite these efforts, DME may persist. For such cases, there has been a report of meaningful gains in vision (with little risk of vision loss) with a continuous IVA treatment [23]. An IVA regimen of at least six consecutive injections showed efficacy in $50\%$ of non-responders to bevacizumab [30,31]. However, a continuous IVA treatment (such as that in phase III trials) is not always possible in clinical practice [32,33]. In the Korean National Health Insurance system, the number of anti-VEGF treatments covered is limited per patient, and the maximal effect should be obtained with limited resources. As shown in our study, a focus on early loading IVA might be beneficial in real-world practice, where a frequent injection such as with fixed doses in clinical trials is often limited. A five-loading regimen will reduce CRT fluctuations in patients with DME, which was reported to be associated with better visual outcomes based on a post hoc analysis from the DRCR Network protocols T and V clinical studies [21]. The effects of DPP-4 inhibitors on DME rarely have been investigated, although one study revealed no such influence [34]. In our study, DPP-4 inhibitors were used more frequently in the three-loading group compared to the five-loading group. However, their association with the stability of DME was not evident, which might be due to the similar glucose controls in the two groups despite different proportions of antidiabetic medications. This study has several limitations related to its retrospective nature, the small number of included patients, and the relatively short follow-up period. As mentioned above, a longer follow-up period might demonstrate a different tendency. The difference in the numbers of patients in the groups is also a limitation and was affected by the change in the coverage policy of the national health insurance system in South Korea. In addition, no untreated DME group was included in this retrospective study. Moreover, the treatment response to IVA in DME is limited to anatomical improvement. Further prospective, randomized, large-scale, well-controlled trials may provide evidence for the optimal loading IVA treatment method for DME. ## 5. Conclusions Despite the limitations, this study provides a valuable insight into the optimal loading treatment regimen of IVA for DME. 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--- title: Long-Term Resistance–Endurance Combined Training Reduces Pro-Inflammatory Cytokines in Young Adult Females with Obesity authors: - Adi Pranoto - Maulana Bagus Adi Cahyono - Reinaldi Yakobus - Nabilah Izzatunnisa - Roy Novri Ramadhan - Purwo Sri Rejeki - Muhammad Miftahussurur - Wiwin Is Effendi - Citrawati Dyah Kencono Wungu - Yoshio Yamaoka journal: Sports year: 2023 pmcid: PMC10054472 doi: 10.3390/sports11030054 license: CC BY 4.0 --- # Long-Term Resistance–Endurance Combined Training Reduces Pro-Inflammatory Cytokines in Young Adult Females with Obesity ## Abstract A sedentary lifestyle and an unhealthy diet increase the risk of obesity. People with obesity experience adipocyte hypertrophy and hyperplasia, which increases the production of proinflammatory cytokines, thereby increasing the risk of morbidity and mortality. Lifestyle modification using non-pharmacological approaches such as physical exercise prevents increased morbidity through its anti-inflammatory effects. The purpose of this study was to examine the effects of different types of exercise on decreased proinflammatory cytokines in young adult females with obesity. A total of 36 female students from Malang City aged 21.86 ± 1.39 years with body mass index (BMI) of 30.93 ± 3.51 kg/m2 were recruited and followed three different types of exercise interventions: moderate-intensity endurance training (MIET), moderate-intensity resistance training (MIRT), and moderate-intensity combined training (MICT). The exercise was performed at a frequency of 3x/week for 4 weeks. Statistical analysis was performed using the Statistical Package for Social Science (SPSS) version 21.0, using the paired sample t-test. The results revealed that serum IL-6 and TNF-α levels were significantly decreased between pre-training and post-training in the three types of exercise (MIET, MIRT, and MICT) (p ≤ 0.001). The percentage change in IL-6 levels from pre-training in CTRL was (0.76 ± $13.58\%$), in MIET was (−82.79 ± $8.73\%$), in MIRT was (−58.30 ± $18.05\%$), in MICT was (−96.91 ± $2.39\%$), and (p ≤ 0.001). There was a percentage change in TNF-α levels from pre-training in CTRL (6.46 ± $12.13\%$), MIET (−53.11 ± $20.02\%$), MIRT (−42.59 ± $21.64\%$), and MICT (−73.41 ± $14.50\%$), and (p ≤ 0.001). All three types of exercise consistently reduced proinflammatory cytokines such as serum levels of IL-6 and TNF-α. ## 1. Introduction Obesity has increased globally over the last 50 years and is now considered an epidemic or even a pandemic in the 21st century [1,2]. Currently, the prevalence of obesity worldwide has more than doubled compared to 1975, when only $3.2\%$ of men and $6.4\%$ of women had obesity. If this pattern of growth continues, the prevalence of obesity will inevitably increase to $18\%$ in men and $21\%$ in women by 2025 [3]. According to Indonesian Basic Health Research (RISKESDAS) 2018, the prevalence of obesity among people older than 18 years was $21.8\%$, which was higher than in 2013 ($14.8\%$) and 2007 ($10.5\%$) [4]. Notably, this condition is alarming and poses a serious threat to the health of populations worldwide [5,6]. Physiologically, obesity is associated with low-grade chronic inflammation (LGCI) [7]. This is because individuals with obesity experience adipocyte hypertrophy and hyperplasia [8], causing a mechanical stressor that stimulates macrophage M1 activation [9]. Proinflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and interleukin 6 (IL-6) are released by activated M1 macrophages [10]. The implication of this is an increased risk of insulin resistance [11], myocardial infarction [12], hypertension, stroke [13], gallstones, non-alcoholic fatty liver disease (NAFLD) [14], and several types of cancer [15,16,17,18]. Moreover, the onset of obesity often occurs in the young population, and this population will likely suffer from more extended morbidity [19]. An unhealthy diet and lack of physical activity lead to obesity [6,20,21]. Through their anti-inflammatory effects, lifestyle changes using an exercise-based non-pharmacological approach are considered effective in preventing increased morbidity [22,23]. Regular moderate-intensity exercise has an anti-inflammatory effect by lowering blood levels of basal cytokines such as IL-6 and TNF-α [16,24]. In women with obesity, hypertrophy and hyperplasia of adipocytes trigger stress and stimulate macrophage activation [25,26]. Activated macrophages induce the production of IL-6 and TNF-α via the nuclear factor-kappa beta (NF-κβ) pathway [27,28]. Regular exercise induces increased IL-6 secretion into the blood [22], resulting in the activation of the extracellular signal-regulated kinase $\frac{1}{2}$ (ERK$\frac{1}{2}$) pathway, thereby increasing lipolysis [29,30,31]. Continuous lipolysis induced by regular exercise can reduce the amount of visceral fat in the body [32], leading to lower basal levels of serum IL-6 and TNF-α [33]. Exercise can also cause muscles to adapt by increasing the number of mitochondria and becoming more efficient at oxidizing fatty acids, thereby reducing the need for glycogen, blood glucose, and lactate production during exercise [34,35,36]. A decrease in glycogen correlates with a decrease in IL-6 synthesis through the AMP-activated protein kinase (AMPK) and p38 mitogen-activated protein kinase (p38MAPK) pathways [37]. Exercise also correlates with decreased M1 infiltration of adipocytes such that proinflammatory cytokine levels at basal levels decrease [38,39]. Previous studies have revealed that in comparison to resistance training, endurance exercise was more effective at lowering the blood levels of IL-6 and TNF-α [40]. Other studies have revealed that serum levels of IL-6 and TNF-α were higher in endurance exercise than in resistance exercise [41]. Based on the results of these studies, there remains an uncertainty regarding the different types of exercise that may be used to reduce IL-6 and TNF-α levels. Appropriate exercise interventions can be a solution for reducing the level of inflammation and mortality and morbidity rates among patients with obesity. According to the latest guidelines by the World Health Organization and the American College of Sports Medicine, regular resistance training can provide global health benefits by preventing cardiovascular disease mortality, incident hypertension, type 2 diabetes, and cancers, and improving mental health (by reducing symptoms of depressive and anxiety), and can also improve adiposity [42,43,44]. Therefore, the purpose of this study was to examine the effects of different types of exercise on decreased proinflammatory cytokines in young adult females with obesity. ## 2.1. Research Design This was a true experimental study with a pre-test–post-test control group design. A total of 42 participants underwent anthropometric measurements and body composition. Six participants did not meet the inclusion criteria. A total of 36 women with obesity (based on Asia-Pacific BMI classification) who had a body mass index (BMI) of 30.93 ± 3.51 kg/m2, an age of 21.86 ± 1.39 years, blood pressure of (systolic blood pressure 113.50 ± 9.52 mmHg, diastolic blood pressure 79.92 ± 7.37 mmHg), a resting heart rate of (RHR) 79.89 ± 7.97 bpm, oxygen saturation (SpO2) 97.58 ± $1.96\%$, a fasting blood sugar of 91.72 ± 5.84 mg/dL, and hemoglobin of 15.24 ± 1.94 g/dL were selected to be participants in the study, and blood samples were collected. All participants were provided information about the study orally and in writing, and they consciously filled out and signed an informed consent form. All selected respondents had no history of smoking, alcohol consumption, or chronic diseases such as kidney failure, lung disease, diabetes mellitus, hypertension, or cardiovascular disease. It was confirmed that all respondents were not undergoing a weight loss program using either medication or diet, and were not active in sports activities. The participants were randomly assigned to four groups: CTRL ($$n = 9$$, control group), MIET ($$n = 9$$, moderate-intensity endurance training group), MIRT ($$n = 9$$, moderate-intensity resistance training group), and MICT ($$n = 9$$, moderate-intensity combined training group). The exercise was performed at a frequency of 3x/week for 4 weeks. In this study, the dropout rate was $0\%$, and the attendance rate was $100\%$. After the 4 week intervention program, anthropometric and body composition measurements were taken, and blood samples were collected. A flowchart of the study is shown in Figure 1. ## 2.2. Measurement of Body Composition and Physiological Parameters Height was measured using a portable stadiometer Seca 213. Body composition was measured using a Seca mBCA 554. Seca Mbca 554 is a medical body composition analyzer that uses BIA to calculate body composition. Blood pressure and resting heart rate were measured using an OMRON HBP-9030 digital tensiometer. A Beurer PO 30 Pulse Oximeter was used to measure oxygen saturation (SpO2), while body temperature (BT) was measured using an OMRON MC-343F Digital Thermometer administered orally. ## 2.3. Exercise Protocol and Blood Sampling The exercise protocol was implemented and supervised by a personal trainer from Atlas Sports Club Malang (East Java 65146, Indonesia). The MIET intervention was performed by running on a treadmill at an intensity of 60–$70\%$ HRmax for 35 min. The MIRT intervention was performed with an intensity of 60–$70\%$ 1-RM, with 4–6 sets at 12–15 reps, with active rest of 30 s between sets, for a total exercise time of 35 min/session. The method used in MIRT is circuit training, divided into upper and lower body parts. Upper body resistance training included pull-downs, shoulder presses, chest presses, and tricep push-downs, while lower body resistance training included leg presses, leg extensions, leg curls, and barbell squat presses (upper and lower body resistance training was not performed simultaneously, but on different days). The MICT was performed by combining endurance training with resistance training on separate days (lower body resistance training (Monday), upper body resistance training (Wednesday), and endurance training (Friday)) with a training duration of 35 min/session. The warm-up and cool-down for the three types of exercise were each performed for 5 min at an intensity of $50\%$ HRmax and carried out by walking quickly on the treadmill. The exercise was performed at a frequency of 3x/week for 4 weeks. The intervention was conducted from 07.00–09.00 am in Fitness Center Atlas Sports Club Malang (East Java 65146, Indonesia). Heart rate during exercise was monitored using a Polar H10 heart rate sensor. The study environment had a humidity level of 50–$70\%$ and a room temperature of 26 ± 1 °C [45]. Blood sampling was carried out twice, both pre-training (0 weeks) and 24 h post-training (4 weeks) in the cubital vein (4 mL). Blood sampling both pre-and post-training was carried out after the subjects had fasted overnight for 12 h. The collected blood samples were centrifuged for 15 min at 3000 rpm. The separated serum samples were immediately processed to analyze IL-6 and TNF-α levels. ## 2.4. Measurement of Cytokines Pro-Inflammatory Pro-inflammatory cytokines such as IL-6 levels were measured using commercial ELISA Kits (Cat. No.:E-EL-H6156; Human IL-6 ELISA Kit; Elabscience Biotechnology Inc., Houston, TX 77079, USA) with a sensitivity level of 0.94 pg/mL and a detection range of 1.56–100 pg/mL, while TNF-α levels were measured using commercial ELISA kits (Cat. No.: E-EL-H0109; Human TNF-α ELISA Kit; Elabscience Biotechnology Inc., Houston, TX 77079, USA) with a sensitivity level of 4.69 pg/mL and a detection range of 7.81–500 pg/mL. Several studies have validated the accuracy of commercial ELISA kits used to analyze IL-6 and TNF-α levels [22,46,47]. ## 2.5. Statistical Analysis Normality was assessed using the Shapiro–Wilk test, while Levene’s test was used for homogeneity. The parametric paired sample t-test was used to determine the differences in data between pre- and post-training in each group. The data were normally distributed, and a one-way ANOVA test was performed to determine the difference in data in all groups, followed by Tukey’s HSD post hoc test. If the data were not normally distributed, the non-parametric Kruskal–Wallis Test was performed, followed by the Mann–Whitney U test. The relationship between the parameters was evaluated using Pearson’s correlation coefficient test. All statistical analyses used a significance level of $5\%$, and all data are presented as mean ± SD. ## 3. Results In this study, the dropout rate was $0\%$, and the attendance rate was $100\%$. The analysis results from the basic characteristics of all subjects in the four groups shown in Table 1. The analysis results of the average levels of pro-inflammatory cytokines based on time in the four groups (CTRL vs. MIET vs. MIRT vs. MICT) shown in Table 2. The analysis of the average pre-training serum IL-6 levels in the four groups (CTRL, MIET, MIRT, MICT) showed no significant difference (p ≥ 0.05), whereas the non-parametric analysis of the average post-training serum IL-6 levels and delta (Δ) showed a significant decrease in all four groups (CTRL, MIET, MIRT, MICT) (p ≤ 0.001). A significant difference (p ≤ 0.001) in the average decrease in post-training serum IL-6 levels between MICT vs. CTRL, MICT vs. MIET, MICT vs. MIRT, MIET vs. CTRL, MIET vs. MIRT, and MIRT vs. CTRL is shown in the Mann–Whitney U Test. The non-parametric analysis also showed a significant difference in the average delta (Δ) decrease in serum IL-6 levels between MICT vs. CTRL, MICT vs. MIRT, MIET vs. CTRL, and MIRT vs. CTRL, with significant values (p ≤ 0.001), while the average delta (Δ) decreased serum IL-6 levels between MICT vs. MIET, and MIET vs. MIRT showed no significant difference (p ≥ 0.05). The analysis of the average pre-training serum TNF-α levels in the four groups (CTRL, MIET, MIRT, MICT) showed no significant differences (p ≥ 0.05), while the results of the non-parametric analysis on the average post-training serum TNF-α levels and delta (Δ) showed a significant decrease in all four groups (CTRL, MIET, MIRT, MICT) (p ≤ 0.001). The non-parametric analysis also showed a significant difference in the average decrease in post-training serum TNF-α levels between MICT vs. CTRL, MICT vs. MIET, MICT vs. MIRT, MIET vs. CTRL, and MIRT vs. CTRL, with significant values (p ≤ 0.001), while MIET and MIRT showed no significant difference in the average decrease in serum TNF-α levels post-training (p ≥ 0.05). The non-parametric analysis also showed a significant difference in the average delta (Δ) decrease in serum TNF-α levels between MICT vs. CTRL, MIET vs. CTRL, and MIRT vs. CTRL with significant values (p ≤ 0.001), while the average delta (Δ) decreased serum TNF-α levels between MICT vs. MIET, and MIET vs. MIRT showed no significant difference (p ≥ 0.05). The analysis in Table 3 shows a positive relationship between Δ serum IL-6 levels and Δ body mass index, Δ body fat percentage, Δ fat mass, Δ fat-free mass, Δ waist circumference, Δ waist-to-hip ratio, and Δ leptin, and showed a moderate correlation among variables. Δ serum IL-6 levels were also found to have a negative relationship with Δ skeletal muscle mass and Δ adiponectin, and showed a moderate correlation between the three. Δ serum TNF-α levels were found to have a positive relationship with Δ body mass index, Δ body fat percentage, Δ waist circumference, Δ waist-to-hip ratio, and Δ leptin, and showed a moderate correlation among variables. However, other body fat markers such as Δ fat mass and Δ fat-free mass showed weak positive correlations with Δ serum TNF-α levels. Δ serum TNF-α levels were also found to be negatively correlated with Δ skeletal muscle mass and Δ adiponectin, and showed a moderate correlation between the three. ## 4. Discussion Our study showed that there was no significant difference in serum IL-6 and TNF-α levels between the CTRL pre-training and post-training groups, whereas MIET, MIRT, and MICT showed significant decreases in serum IL-6 and TNF-α levels pre-and post-training (Figure 1 and Figure 2). However, the analysis revealed that the greatest decrease occurred in MICT, followed by MIET and MIRT (Figure 2 and Figure 3). Combination training is considered the best exercise because it has the most anti-inflammatory effect compared to aerobic exercise and resistance training [48,49]. Combination exercise reduces serum IL-6 and TNF-α levels more effectively than aerobic or resistance training [50]. Our study results reported that combined training is better at reducing pro-inflammatory cytokines than aerobic and resistance training independently. In this study, aerobic exercise was considered better than resistance training at reducing serum IL-6 and TNF-α levels. This is in accordance with a previous study by Sabag et al. [ 40], which stated that aerobic exercise for 45 min with a capacity of 50–$70\%$ HRmax for 12 weeks in female participants with obesity aged 50–60 years resulted in a greater decrease in IL-6 levels than resistance training. Ho et al. [ 48] reported that 12 weeks of aerobic exercise in participants with obesity aged 40–66 years at an intensity of $60\%$ HRR for 30 min was more effective in lowering serum TNF-α levels than 12 weeks of resistance training in four sets of 8–12 repetitions. A meta-analysis of the obese population related to cardiometabolic health parameters revealed that combined training is more effective in controlling body composition, cardio-respiratory fitness, blood lipids, blood pressure, and blood glucose compared with endurance training and resistance training [51]. Combined training integrates aerobic and muscle-strengthening activities into a single session. This multi-component exercise modality has a greater effect on increasing the metabolic rate, FFM, high-density lipoprotein (HDL,) and insulin while also lowering SBP, DBP, mean arterial pressure (MAP), and low-density lipoprotein (LDL). Hence, currently, international guidelines recommend systematic multicomponent exercise regimens for obese individuals. Adipocyte hypertrophy and hyperplasia in women with obesity causes stress and activation of macrophages. Activated macrophages release TNF-α and induce IL-6 production via the NF-kβ pathway [27,28]. MIET inhibits adipocyte hypertrophy and hyperplasia via lipolysis [24]. Lipolysis occurs via the ERK$\frac{1}{2}$ pathway, which is activated after a single session of aerobic exercise [52]. Regular exercise contributes to this mechanism, resulting in a reduction in fat mass [32] and inflammatory markers. MIRT suppresses IL-6 and TNF-α production through muscle adaptation to stressors. Muscle contraction during exercise reduces glycogen reserves in muscles. Reduced glycogen reserves promote myokine IL-6 production via the AMPK and p38 AMPK pathways. Activation of this pathway triggers an increase in IL-6 mRNA levels in muscle and blood. Elevated serum IL-6 signals the liver to initiate gluconeogenesis. MIRT regularly adapts muscles by increasing the number of mitochondria in muscles and making fatty acid oxidation more efficient, thus reducing the need for glycogen, blood glucose, and lactate production during exercise [37]. MIRT has also been shown to lower TNF-α gene expression [53]. The increase in beta-oxidation and lipase enzymes after MIRT enhances fatty acid uptake in the skeletal muscles, which directly lowers adipose tissue [54]. Consequently, the levels of inflammatory markers (IL-6 and TNF-α) decrease. Therefore, combined exercise has the best results in terms of lowering inflammatory markers (IL-6 and TNF-α), because it incorporates both the MIET mechanism that stimulates lipolysis and the MIRT mechanism that enables muscle adaptation to stressors. Adipocytes produce inflammatory markers such as IL-6 and TNF-α [55]. This is evidenced by the correlation between body fat mass and inflammatory markers. A meta-analysis of patients with obesity who participated in an exercise intervention for at least 4 weeks discovered that aerobic exercise burns visceral fat more effectively than resistance training or combination therapy. Resistance training and post-exercise combinations did not significantly change visceral fat levels [50]. However, this might be influenced by the participant’s diet, which cannot be controlled in the study; therefore, it is possible that participants from certain groups consumed foods with high fat content. Based on previous studies, it is possible to hypothesize that the decrease in fat mass, as confirmed in this study, was a determinant of the reduction in serum levels of IL-6 and TNF-α in young women with obesity [49]. Regular exercise can reduce morbidity and mortality, especially when started at a young age [15]. Increased levels of inflammatory markers (IL-6 and TNF-α) in the body are associated with an increased risk of insulin resistance and cardiovascular disease [56]. Due to the increased maximum oxygen volume (VO2max), exercise increases the expression of glucose transporter type 4 (GLUT4) in cell membranes, improving insulin sensitivity by 25–$50\%$ and helping in maintaining normal blood glucose levels [57]. Therefore, exercise can be one of the pillars of lifestyle modification in individuals with obesity [21,45]. Regular exercise can reduce stenosis in coronary arteries by increasing nitric oxide (NO) and endothelial nitric oxide synthase (eNOS) production, and increasing anti-inflammatory cytokines in the vascular endothelium [58]. Strict inclusion criteria were used, and preliminary research was conducted to measure energy expenditure between types of exercise; therefore, the exercise was expected to provide good results and form a non-pharmacological regimen for obese people. This study has a few limitations. First, the study was limited to IL-6 and TNF-α as parameters; thus, we were unable to explain the molecular mechanisms involved in reducing IL-6 and TNF-α levels. Second, this study was only conducted on young adult females with obesity; therefore, the findings of this study cannot be generalized to all age groups and sexes. Another limitation is the length of the intervention. The data cannot be extrapolated to any time frame outside of 4 weeks. In addition, we could not fully control any physical activity carried out outside the 4-week training program. During the intervention period, we were unable to control the participants’ food intake. To prove the mechanism, this study needs further research to explore the molecular mechanisms underlying the reduction of pro-inflammatory cytokines such as IL-6 and TNF-α. ## 5. 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--- title: Photochemical Reduction of Silver Nanoparticles on Diatoms authors: - Adrián León-Valencia - Sarah Briceño - Carlos Reinoso - Karla Vizuete - Alexis Debut - Manuel Caetano - Gema González journal: Marine Drugs year: 2023 pmcid: PMC10054479 doi: 10.3390/md21030185 license: CC BY 4.0 --- # Photochemical Reduction of Silver Nanoparticles on Diatoms ## Abstract In this work, the photochemical reduction method was used at 440 or 540 nm excitation wavelengths to optimize the deposition of silver nanoparticles on the diatom surface as a potential DNA biosensor. The as-synthesized nanocomposites were characterized by ultraviolet-visible spectroscopy (UV-Vis), Fourier transforms infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning transmission electron microscopy (STEM), fluorescence microscopy, and Raman spectroscopy. Our results revealed a 5.5-fold enhancement in the fluorescence response of the nanocomposite irradiated at 440 nm with DNA. The enhanced sensitivity comes from the optical coupling of the guided-mode resonance of the diatoms and the localized surface plasmon of the silver nanoparticles interacting with the DNA. The advantage of this work involves the use of a low-cost green method to optimize the deposition of plasmonic nanoparticles on diatoms as an alternative fabrication method for fluorescent biosensors. ## 1. Introduction Biological nanomaterials have gained importance in biomedicine due to their large variety of bioresources, synthesis methods, versatility, and the possibility to further enhance their features through material functionalization [1,2]. They have become the focus of the next generation of biomedical tools, such as drug delivery, target-specific nanomaterials, biosensors, and bioimaging materials [3]. In matters of biosensing and bioimaging materials, diatoms are great options due to their particular structures, characteristic shapes, replicability, luminescent properties, and biocompatibility [4]. Naturally occurring biosensors doped with plasmonic nanoparticles are increasingly used to detect physiologically important analytes in real biological samples (i.e., blood, plasma, urine, and saliva) [5,6]. Biosensors are materials that detect single molecular species by combining the molecular recognition properties of biological macromolecules with signal transduction mechanisms that couple ligand-binding to readily detectable physical changes. The choice of the substrates for the analytical applications depends on the transduction methods, i.e., fluorescence or chemiluminescence, and the application of the measurements. In recent years, fluorescent biosensors based on biomaterials have been reported using organic dyes, inorganic semiconductors [7], carbon quantum dots [8], and diatoms as fluorescence biosensors [9]. Diatoms are low-cost and biocompatible 3D materials that show interesting and remarkable optical properties [10,11]. Diatoms have been applied in two main monitoring techniques in biosensing applications, i.e., fluorescence and surface-enhanced Raman scattering (SERS) [12]. Fluorescence immunoassays based on diatoms are developed by cross-linking antibodies on the surfaces of diatoms. A significant increase in the photoluminescence intensity was observed upon biomolecular interactions with the analyte, indicating the biosensing response of the diatoms [13]. It has been reported that incident light on a diatom frustule generates enhanced electromagnetic fields on or near the surface of the diatom structure [14]. This results in increased excitation of the fluorophore and emission of more photons. Additionally, a fluorophore on the surface of a frustule experiences an increase in the density of optical states, which results in enhanced emission due to the Purcell effect [15,16]. This dual-modal optical enhancement results in boosted fluorescence signals for the easier detection of analytes [17]. Due to their unique structural properties, diatoms are capable of enhancing the localized surface plasmon resonance (LSPR), leading to near-field optical amplification of the signal [17] due to the photonic, hierarchical, micro-scale periodicity of the diatom frustule pores that allow for the signal enhancement of the electromagnetic field induced by LSPR ‘hot spots’ with large SERS enhancement factors [14]. As a consequence, diatom biosilica has found wide applications in the fields of biosensing [18], diagnostics [19], and therapeutics. Several methods have been reported to optimize the properties of diatoms, as their surfaces can be functionalized and decorated with different materials depending on the desired characteristic to be improved [2,20]. These properties can be improved by the functionalization and decoration with plasmonic nanoparticles as potential surfaced enhanced Raman scattering (SERS) biosensors [21,22], photoluminescent immunosensor [18], and multifunctional drug delivery carriers [4]. Taking advantage of the intrinsic luminescence of diatom frustules and the plasmonic resonances at visible wavelengths associated with the intrinsic surface plasmon frequencies of metallic nanoparticles [23], these nanocomposites could be potential materials for biosensors [14,19]. It has been reported that natural diatom biosilica combined with metallic nanoparticles could be used in sensing, diagnostics, and therapeutics, taking advantage of the fluoresce and the SERS effect [24]. In this work, a simple low-cost photoreduction method to optimize the deposition of silver nanoparticles on diatoms was employed and a preliminary study as a potential DNA fluorescence-detecting biosensor was carried out. The novelty relies on controlling the silver nanoparticle growth and deposition on the diatom surface by irradiating the samples with 440 or 540 nm excitation wavelengths, respectively. The fluorescence properties and plasmonic resonance signals of silver nanoparticles on diatoms were enhanced, demonstrating potential applications as DNA fluorescence-detecting biosensors. ## 2.1. Ultraviolet-Visible Spectroscopy (UV-Vis) After the photochemical reduction process with 540 nm or 440 nm wavelengths, the sample solutions changed from colorless to purple for the samples irradiated with 440 nm (Ag Blue) and yellow for the sample irradiated at 540 nm (Ag Green). Figure 1 shows the absorption spectra of the silver nanoparticles on diatoms after the photochemical process. In these spectra, the absorption peak in the UV range from 200 nm to 300 nm was due to diatom frustules in both samples [25]. The photoreduction of the silver nanoparticles over the diatoms is evidenced by the surface plasmon resonance (SPR) peak observed at 424 nm from the excitation of free electrons of the spherical-shaped silver nanoparticles [4]. To complement the structural analysis of the diatom, the surface area and pore volume were measured using the Brunauer–Emmett–Teller technique, obtaining 102.30 m2/g and 0.22 cm3/g, respectively. The diatom surface provides a suitable environment for the photochemical reduction of the silver nanoparticles on the diatom surface. ## 2.2. X-ray Photoelectron Spectroscopy (XPS) X-ray photoelectron spectroscopy was employed to measure the silver nanoparticle binding energies and atomic concentrations over the diatoms after the photochemical process. XPS measurements were carried out in the range of 0–1200 eV; the results are presented in Figure 2 and Table 1. The most intense peaks in the spectra correspond to O1s, Si2p, C1s, and Ag3d elements. Figure 2d shows the high-resolution scan of Ag3d, confirming the growth of silver nanoparticles over the diatom surface. In these spectra, we observe the highest percentage of AgO $86\%$ in the diatom irradiated at 440 nm compared with the diatom irradiated at 540 nm at $78\%$. In Table 1, the atomic concentration of Ag3d is 0.8 % higher for the sample irradiated at 440 nm. The decrease in the intensity of the O1s peak at 532 eV for the samples after the photoreduction treatment suggests the interaction between the silver nanoparticles and the diatom surface. The results of the deconvolution analysis of the oxygen core level reveal a greater presence of oxygen–carbon bonding compared to oxygen–metal bonding in the Ag blue diatom due to the prevalence of functional groups. This is further substantiated by the higher atomic concentration of C1s, as depicted in Figure 2a,b. Based on the results obtained with XPS, we conclude that we obtained the highest concentration of silver nanoparticles on the diatom surface for the sample irradiated at 440 nm. ## 2.3. Scanning and Transmission Electron Microscopy (SEM and TEM) Figure 3a shows the diatomite skeletal structure with a cylindrical and porous frustule with well-defined dimensions and an average of 25 μm in length, 10 μm in diameter, and a pore size of 0.9 ± 0.2 μm. In this figure, the effectiveness of the photoreduction process is revealed by the presence of silver nanoparticles on the surface of the diatoms. In Figure 3b, the nanoparticles irradiated with the 540 excitation wavelength show agglomerations with 10 ± 3 nm. Meanwhile, in Figure 3c, the diatoms irradiated at 440 nm excitation wavelengths show a high concentration of nanoparticles with 13 ± 5 nm and 9 ± 3 nm uniformly distributed over the diatom surface. ## 2.4. Fourier Transform Infrared Spectroscopy (FTIR) In Figure 4, the most prominent peak of the diatom appears at 1003 cm−1 related to the Si–O–Si stretching, at 791 cm−1 to the Si-OH silanol stretching, and 444 cm−1 to the siloxane bending [26]. These spectra are characteristic of the siliceous structure of the diatom frustule and show that the photoreduction process does not alter the diatom structure. After the photoreduction process, we added a drop of DNA to the nanocomposites and characterized them using FTIR spectroscopy. In Figure 4 and Table 2, we identify the main peaks related to the interaction between the DNA and the nanocomposites through the N-H and C-N bindings at 2974 and 1044 cm−1 [27]. ## 2.5. Raman Spectroscopy Raman spectra of the diatoms are shown in Figure 5. Diatoms with silver nanoparticles (after photoreduction: Ag blue and Ag green) and DNA spectra show flat lines(Figure 5a–c,f, respectively). A drop of DNA was added to the nanocomposites, which resulted in an enhancement of the Raman intensity for the sample irradiated at 440 nm (Figure 5e), with 5.5 times higher detection sensitivity for DNA (Figure 5d). In these spectra, we identify the main peaks related to the DNA interacting with the nanocomposites through the N-H, C-N, and C-H bonds reported in Table 3, which are in good agreement with the results obtained with FTIR (Figure 4 and Table 2). Our findings are consistent with previous studies that have reported on applying Ag NPs on Pinnularia diatoms for SERS sensing using Rhodamine at 532 nm, resulting in a 4–6× improvement in sensitivity [28]. Additionally, gold-coated Aulacoseira diatoms were effective SERS substrates, exhibiting a significant enhancement of the spontaneous Raman scattering of p-Mercaptoaniline by a factor of 105 [29]. ## 2.6. Optical and Fluorescence Microscopy The fluorescence enhancement of the diatoms irradiated at 440 nm in Figure 6e is explained when the incident wavelength leads to the excitation of the surface plasmon, coherent electronic motion, and the d electrons [4]. When plasmonic nanoparticles are excited with molecular vibration results in an increase in the electrostatic fields surrounding the metallic nanoparticles on the diatom surface, this behavior is consistent with the observed surface plasmon band in Figure 1 in the visible region, due to the surface plasmon oscillation of free electrons and the high concentration of nanoparticles on the diatom, in good agreement with the XPS results in Figure 2 and the SEM images in Figure 3. ## 3. Discussion In the first part, we evaluated the silver nanoparticle’s photoreduction over the diatom’s surface using ultraviolet-visible spectroscopy (UV-Vis) by the surface plasmon resonance peak at 424 nm [4]. With X-ray photoelectron spectroscopy, we found the highest percentage of AgO $86\%$ in the diatom irradiated at 440 nm compared with the diatom irradiated at 540 nm with $78\%$, in agreement with the highest concentration of nanoparticles evidenced by scanning electron microscopy. Our results reveal that silver nanoparticles were deposited on the diatom surface, likely via an electrostatic interaction by the photoreduction process at 440 or 540 nm excitation wavelengths. Changing the irradiation wavelength using the photoreduction method allows the control of the nanoparticle size and distribution on the diatom surface. The growth of the nanoparticles could be explained when the nanoparticles are in resonance with the excitation wavelength forming rapid nucleation of Ag NPs on the diatom surface; this process is known as plasmon-assisted growth [30]. In this process, the λirr dependence control the size and anisotropy of the nanoparticles. As shown in Figure 3d, larger sizes, and a wider distribution are obtained for the samples irradiated at 540 nm wavelength. Meanwhile, the 440 nm excitation wavelength promotes a gradual growth of the nanoparticles along the diatom surface with a uniform narrow distribution [31]. In the second part, we added a drop of DNA to the nanocomposites. We characterized them using FTIR and Raman spectroscopy, identifying the main peaks related to the interaction between the DNA and the nanocomposites through the N-H and C-N binding [32]. Finally, our results reveal that the highest concentration of Ag NPs on the diatom surface was obtained for the sample irradiated at 440 nm (Ag Blue), causing a surface-enhanced resonance Raman effect and the highest fluorescence response. The enhanced intensity observed comes from the optical coupling of the diatoms’ guided-mode resonance, the silver nanoparticles’ localized surface plasmon, and the DNA’s coupling on the nanocomposite surface. It has been reported [33] that the electromagnetic enhancement observed originates from two contributions; the local field enhancement and the radiation enhancement. The plasmon energy from the silver nanoparticles on the diatom forces the Raman process to occur in the DNA, the energy is transferred back into the plasmon, and the scattered radiation is detected. Another explanation could be related to the Hot spots formed by the interaction of the nanoparticles on the diatom surface. If the DNA interacts with the hot spot, the electromagnetic field increases, providing the surface-enhanced Raman scattering effect [34]. Previous studies [14] have demonstrated that the wavelengths of the localized surface plasmon (LSP) resonances at the metallic surfaces are determined by the overall geometries and the aggregation states of the Ag NPs. The concentration of Ag NPs induces plasmonic extinction at longer wavelengths when individual nanoparticles are in a close-packed assembly and coupled with each other. The frequency and intensity of the plasmon oscillation depend on the degree of agglomeration as well as orientation with respect to the polarization direction of the excitation light. In our case, the enhancement of the fluorescence response of the nanocomposite irradiated at 440 nm, was 5.5 times higher with DNA. This enhancement is due to the multiple resonances of similar aggregation states that have close resonant frequencies of the Ag NPs irradiated at 440 nm. This work demonstrates a way to design a surface-enhanced Raman spectroscopy (SERS) signal while simultaneously increasing the fluorescence signal through a combination of diatoms and silver nanoparticles. This behavior is particularly desirable for diagnosis and biosensing applications. ## 4.1. Chemicals Diatoms were collected from the Guayllabamba inter-mountain basin, Ecuador, from the planktonic species and genus Aulacoseira. Hydrogen peroxide (H2O2), sulfuric acid (H2SO4, and trisodium citrate (Na3C6H5O7) were purchased from Loba Chemie. Silver nitrate (AgNO3) and sodium borohydride (NaBH4) were obtained from Sigma-Aldrich. The chemicals were not further modified and were used as received. ## 4.2. Diatom Extraction Diatoms were separated from the rock using a scalpel, extracting the white layers to obtain a white powder (Figure 7a). Since diatoms probably contain significant residues from the rock, a purification method was performed (Figure 7b). Diatoms were treated with a piranha treatment with 80 mL of H2SO4 (1M) and 20 mL of H2O2, to clean the diatoms from the rock and eliminate all the organic compounds and pollutants. For this process, 7 g of diatoms were used. The piranha treatment was performed using a relation 4:1 of H2SO4 and H2O2, and the diatoms were immersed slowly in the solution for 30 min at 60 ∘C with stirring. After the time-lapse, the solution was washed several times with water and, at the same time, tested with 0.5 M of NaOH solution. A white precipitate was obtained to indicate the presence of clean diatoms. The white powder sample was dry in the oven at 40 ∘C–60 ∘C for three days [20]. ## 4.3. Photoreduction of Silver Nanoparticles on Diatoms The photoreduction process was performed using irradiation of light at 440 or 540 nm excitation wavelength, respectively (Figure 8), following the design of Saade et al. [ 35] with further modifications previously reported [36,37] to provide the power of wavelength to the chambers using LEDs of 1 W each. Eight LEDs were placed in a series configuration with a current of 0.7 A and 5 V, inside a PVC tube of 12 cm in height, 11 cm in diameter, and 2 mm in thickness. To decorate the samples, 50 mg of diatoms were dispersed in 50 mL of H2O. Then, 0.9 mL of sodium borohydride was added to the solution. Afterward, and with constant stirring, 75 μL of silver nitrate ($0.1\%$) was injected each 5 min for 1 h. Furthermore, the samples were kept at constant stirring and exposed to the wavelength source inside the chambers for 4 h. The same process was repeated for both irradiation wavelengths (440 or 540 nm). ## 4.4. DNA Purification and Functionalization A bacteria culture was performed using Gram-negative E to obtain the DNA. coli ATCC 25922, for 24 h at 37 ∘C and constant shaking. Afterward, the purification of the DNA was performed using a Thermo Scientific GeneJET Genomic DNA Purification Kit. Bacteria cells were harvested in 1.5 mL and centrifuged for 10 min. Then, the pellet was suspended in 180 μL of their digestion solution, followed by adding 20 μL of proteinase K. After shaking thoroughly, the tube was incubated at 56 ∘C in a shaking water bath for 30 min, followed by the addition of 20 μL of RNA solution mix and incubated for 10 min, and 200 μL of lysis solution was added and vortexed for 15 s. Then, vortexing mixed 400 μL of $50\%$ ethanol. The sample was transferred to a DNA purification column, and the residue was centrifuged for 1 min at 6000 rpm. The sample was washed with 500 μL of the buffer solution, centrifuged for 3 min at 8000 rpm, and repeated three times before eluting the genomic DNA with the purification column. The DNA sample was incubated for 2 min at room temperature and centrifuged for 1 min at 8000 rpm. The purified DNA was stored at −20 ∘C for later use. Finally, the DNA was attached to the decorated diatom by the dripping method with 1 μL of DNA on 0.1 g of decorated diatom at room temperature. ## 4.5. Characterization The surface area was measured using the Brunauer–Emmett–Teller technique in an ASAP 2100 from Micromeritics. Infrared analysis was performed using an Agilent Technologies spectrometer Cary 360 with a diamond attenuated total reflectance (ATR) accessory and resolution of 4 cm−1. UV-*Vis spectra* were acquired with a LAMBDA 1050 UV/Vis/NIR, with Accessory Praying Mantis. Scanning Transmission Electron Microscopy was performed with a TESCAN Mira 3 model STEM mode and back Scattered Electrons in SEM. Fluorescence images were performed with the Olympus BX63 microscope with 365 nm excitation wavelength. Raman measurements were acquired using a HORIBA LabRAM HR Evolution spectrometer with a 633 nm excitation wavelength. X-ray Photoelectron Spectroscopy (XPS) measurements were carried out using a VersaProbe III 5000 photoelectron spectrometer (Physical Electronics), employing Al Kα X-rays with a photon source of 1486.7 eV. Survey scans were collected from 0 to 1400 eV with a pass energy of 226 eV for each sample. Data processing was performed according to Multipack software, applying the Shirley-type background consideration. Curve fitting was performed using a nonlinear algorithm assuming mostly Gaussian peak shape without asymmetries. Survey XPS data were used to examine the atomic composition and surface of the tree species under analysis. After correction with the experimentally determined sensitivity factors, atomic percentage values, and elemental ratios were calculated from the peak-area ratios. ## 5. 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--- title: GSK3β Inhibition Reduced Vascular Calcification in Ins2Akita/+ Mice authors: - Kristina I. Boström - Xiaojing Qiao - Yan Zhao - Xiuju Wu - Li Zhang - Jocelyn A. Ma - Jaden Ji - Xinjiang Cai - Yucheng Yao journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054481 doi: 10.3390/ijms24065971 license: CC BY 4.0 --- # GSK3β Inhibition Reduced Vascular Calcification in Ins2Akita/+ Mice ## Abstract Endothelial–mesenchymal transition (EndMT) drives the endothelium to contribute to vascular calcification in diabetes mellitus. In our previous study, we showed that glycogen synthase kinase-3β (GSK3β) inhibition induces β-catenin and reduces mothers against DPP homolog 1 (SMAD1) to direct osteoblast-like cells toward endothelial lineage, thereby reducing vascular calcification in Matrix Gla Protein (Mgp) deficiency. Here, we report that GSK3β inhibition reduces vascular calcification in diabetic Ins2Akita/wt mice. Cell lineage tracing reveals that GSK3β inhibition redirects endothelial cell (EC)-derived osteoblast-like cells back to endothelial lineage in the diabetic endothelium of Ins2Akita/wt mice. We also find that the alterations in β-catenin and SMAD1 by GSK3β inhibition in the aortic endothelium of diabetic Ins2Akita/wt mice are similar to Mgp−/− mice. Together, our results suggest that GSK3β inhibition reduces vascular calcification in diabetic arteries through a similar mechanism to that in Mgp−/− mice. ## 1. Introduction Vascular calcification is a common and severe complication of diabetes mellitus which affects more than $9\%$ of the American population [1,2,3,4,5]. Previously considered to be a passive process of mineral precipitation, vascular calcification is now known as an active process that involves ectopic bone formation [1,2,3,4]. In this process, dysregulated systemic and local factors compel vascular cells to switch cell fates to osteogenic differentiation [1,2,3,4,5,6,7,8,9,10]. In diabetes mellitus elevated by hyperglycemia, bone morphogenetic protein (BMP) signals drive endothelial cells (ECs) to transdifferentiate into osteoblast-like cells causing arterial calcification [5,7,8,9,10]. Indeed, the role of the endothelium in vascular calcification is not limited to being a source of osteoinductive factors responding to hyperglycemia, oscillatory shear stress, or hyperlipidemia [9,11,12]. It also directly contributes to the calcifying process of osteoprogenitor cells [5,6,7,8,9,10,13,14,15]. Osteoblast-like cells with EC origin can be detected in calcified lesions of diabetic aortic tissues and atherosclerotic plaques [5,6,7,8,9,12]. Mechanistically, ECs are driven by endothelial-mesenchymal transitions (EndMTs) to gain plasticity and differentiate into osteoblast-like cells [5,7,8,9,10,14]. Previous studies have demonstrated mechanistic similarities between vascular calcification in Matrix Gla Protein (MGP) deficiency and diabetic models. These include increased BMP activity in the aortic endothelium of Mgp−/− mice, diabetic Ins2Akita/+ mice, db/db mice, and human islet amyloid polypeptide transgenic rats [9]. The elevated BMP signaling stimulates the endothelium to contribute cells to the calcifying process in Mgp−/− and diabetic Ins2Akita/+ aortas [5,7,8]. The increased BMP induced by high glucose in ECs drives ECs toward osteogenic differentiation through EndMTs [5,6,7,8,9]. The EC-derived osteoblast-like cells are detected in calcified lesions in diabetic aortas by lineage tracing, and the differentiation of these cells and calcification are limited by BMP inhibition [6,7,9]. The Ins2Akita/wt mouse results from the Akita mutation, which largely reduces mature insulin by disruption of the two disulfide bonds of A and B chains [16]. Ins2Akita/wt mice become spontaneously diabetic at 3–4 weeks of age and are recognized as a model for type I diabetes mellitus (DM1) [17]. Previous studies have shown that Ins2Akita/wt mice develop vascular calcification and provide not only a monogenic diabetic model but also a model of diabetic calcific vasculopathy [5]. Glycogen synthase kinase 3 (GSK3) is a serine/threonine kinase that is constitutively activated in unstimulated cells [18]. The activity of GSK3 is regulated by serine phosphorylation in response to extracellular signals [19]. GSK3 plays different roles in osteogenic and endothelial differentiation. GSK3 promotes osteogenic differentiation [20], and GSK3 deficiency disrupts the maturation of osteoblasts, resulting in the reduction of bone formation [21]. In contrast, GSK3 prevents endothelial differentiation, and inhibition of GSK3 promotes the differentiation, proliferation, and migration of ECs [22,23]. GSK3 has two isoforms, GSK3a and GSK3β. SB216763 is a small molecule compound that specifically inhibits the activity of the GSK3 isoforms in an ATP-competitive manner [24]. SB216763 has been commonly used to probe the function of GSK3 inhibition [18]. In a previous study, our results suggested that the aortic osteoblast-like cells were redirected back to endothelial differentiation by the SB216763 treatment in Mgp−/− mice [25]. We also showed that osteoblast-like cells with EC origin contributed to aortic calcification in Ins2Akita/+ mice [7]. Here, we hypothesize that GSK3β inhibition ameliorates vascular calcification in diabetic Ins2Akita/+ mice. ## 2.1. GSK3β Inhibition Reduced Aortic Calcification in Ins2Akita/+ Mice To determine whether GSK3β inhibition reduces aortic calcification in Ins2Akita/+ mice, we treated Ins2Akita/+ mice with SB216763 (5 µg/g daily) or saline control at 36 weeks of age for 4 weeks. Alizarin red staining showed a robust decrease of aortic calcification in the SB216763-treated Ins2Akita/+ mice (Figure 1a,b). The quantification of total aortic calcium confirmed the reduction of calcium in the mice (Figure 1c). Immunoblotting of whole aortic tissues showed that SB216763 reduced the expression of osteogenic markers, osterix and osteocalcin (Figure 2a,b). Together, the results suggested that SB216763 reduced the calcification in diabetic Ins2Akita/+ mice. ## 2.2. GSK3β Deletion Limited Aortic Calcification in Ins2Akita/+ Mice Previously, we performed lineage-tracing using Col1α1CreERT2 mice and identified osteoblast-like cells in Mgp−/− aortic tissues [25]. We showed that osteoblast-specific deletion of GSK3β reduced aortic calcification in Mgp−/− mice [25]. To determine if osteoblast-specific deletion of GSK3β ameliorates vascular calcification in diabetes mellitus, we treated mice at 34 weeks of age with tamoxifen (75 mg/kg, daily) for 5 days to delete GSK3β in osteoblast-like cells as previously described [25]. At 40 weeks of age, we examined the aortic tissues. Alizarin red staining showed reduced calcification in the Col1a1CreERT2 GSK3βflox/floxIns2Akita/+ mice (Figure 3a,b). Total aortic calcium was also significantly decreased in the mice with GSK3β deletion (Figure 3c). Immunoblotting of whole aortic tissues revealed the reduction of osteogenic markers in Col1a1CreERT2 GSK3βflox/floxIns2Akita/+ mice after GSK3β deletion (Figure 4a,b). The results suggested that osteoblast-specific deletion of GSK3β reduced the calcification in diabetic Ins2Akita/+ mice. ## 2.3. GSK3β Inhibition Redirected Osteoblast-like Cells toward Endothelial Differentiation in Ins2Akita/+ Mice To determine if GSK3β inhibition directed EC-derived osteoblast-like cells in Ins2Akita/+ mice to revert endothelial differentiation, we generated VE-cadherincreERT2RosatdTomatoIns2Akita/+ mice. At 18 weeks of age, we treated the mice with tamoxifen (75 mg/kg, daily) for 5 days to label the aortic ECs as previously described [25]. At 20, 30, and 40 weeks of age, we isolated tdTomato-positive aortic cells and examined the endothelial and osteogenic markers (Figure 5a). Real-time PCR showed a decrease of endothelial markers with an increase of osteogenic markers in the tdTomato-positive cells of Ins2Akita/+ mice (Figure 5b). We treated the mice with SB216763 (5 µg/g daily) at 36 weeks of age for 4 weeks and isolated tdTomato-positive cells (Figure 5c). The results showed that SB216763 prevented the decrease of endothelial markers and inhibited the increase of osteogenic markers (Figure 5d), suggesting that GSK3β inhibition directed EC-derived osteoblast-like cells back to endothelial differentiation in Ins2Akita/+ mice. Previous studies showed that in Mgp−/− mice, SB216763 increased β-catenin, thereby suppressing SMAD1 and osteoblastic fate but stimulating β-catenin and endothelial differentiation [25]. Here, we examined β-catenin and SMAD1 in tdTomato-positive aortic cells of VE-cadherincreERT2RosatdTomatoIns2Akita/+ mice treated with SB216763. Immunoblotting showed increased β-catenin but decreased SMAD1 in the tdTomato-positive cells of the SB216763-treated group (Figure 6a,b), suggesting that GSK3β inhibition guided EC-derived osteoblast-like cells back to endothelial differentiation in Ins2Akita/+ mice, similar to the findings in Mgp−/− mice. ## 3. Discussion This study provides evidence that GSK3β inhibition reduces vascular calcification in diabetes mellitus. The role of GSK3 in diabetes mellitus has been well investigated in recent studies. GSK3 activity was found to regulate insulin sensitivity, which directly affects glycogen synthesis and glucose metabolism [26]. Several signaling pathways are involved in these processes, such as the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway [26]. Interestingly, inhibition of GSK3 improves the activity of glycogen synthase and glucose uptake, pointing to GSK3 inhibition as a potential antidiabetic strategy [27]. However, the activation of GSK3 in diabetic vascular calcification has never been reported, although GSK3 has been shown to promote osteogenic differentiation and bone formation [20,21]. GSK3β is one of the GSK3 isoforms. Here, we find that limiting GSK3β reduces the calcification in diabetic mice and reveals that the GSK3β inhibitor SB216763 redirects osteoblast-like cells to endothelial differentiation, similar to our previous observations in Mgp−/− mice [25]. These findings might bring more attention to GSK3 inhibition as a strategy to limit diabetes and calcification. EndMTs have been observed to contribute to vascular calcification in diabetes mellitus. Previous studies demonstrated that ECs lose their normal morphology but express mesenchymal stem cell markers to migrate through a degraded internal elastic lamina into the arterial media and contribute to calcification [6,7,10]. The studies showed that excess BMP activity induces a number of serine proteases, such as elastases and kallikreins, to activate Sry-box 2(Sox2) expression in ECs and trigger EndMTs toward osteogenic differentiation [28]. A recent study constructed a systematic screen to explore the possibility of re-directing osteoblast-like cells in vascular calcification back to endothelial differentiation. The GSK3β inhibitor SB216763 was identified to have this capacity and decreased vascular calcification in Mgp−/− mice [25]. In this study, the GSK3β inhibitor SB216763 also reduced vascular calcification in diabetic Ins2Akita/+ mice. Our results suggest that GSK3β inhibition prevents EndMTs and reduces calcification in diabetes. ## 4.1. Animals Ins2Akita/+ (C57BL/6-Ins2Akita/J), GSK3βflox/flox (B6.129(Cg)-Gsk3btm2Jrw/J), Col1α1CreERT2 (B6.Cg-Tg(Col1α1-cre/ERT2)1Crm/J), and B6.Cg-RosatdTomatoGt(ROSA)26Sortm9(CAG−tdTomato)Hze/J mice were obtained from the Jackson Laboratory. The VE-cadherincre/ERT2 mouse was obtained as a gift from Dr. Ralf Adams. Genotypes were confirmed by PCR [29], and experiments were performed with generations F4–F6. Littermates were used as wild-type controls. All mice were fed a standard chow diet (Diet 8604, Harlan Teklad Laboratory, Indianapolis, Indiana, United States). The studies were reviewed and approved by the Institutional Review Board and conducted in accordance with the animal care guideline set by the University of California, Los Angeles. The investigation conformed to the National Research Council, Guide for the Care and Use of Laboratory Animals, Eighth Edition (Washington, DC, USA: The National Academies Press, 2011). We bred Col1a1CreERT2GSK3βflox/flox mice with Ins2Akita/+ mice to create Col1a1CreERT2 GSK3βflox/floxIns2Akita/+ mice. SB216763 (Sigma-Aldrich, S3442) was injected via tail vein or retro-orbital injection (5 µg/g, daily) as in previous studies [30]. Injections of the Ins2Akita/+ mice and wild-type mice started at 36 weeks of age and continued for 4 weeks. 75 mg/kg of tamoxifen (Sigma-Aldrich, T5648) was injected daily for 5 days. ## 4.2. RNA Analysis Real-time PCR analysis was performed as previously described [25]. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as a control gene. Primers and probes for mouse VE-cadherin (Mm00486938_m1), osterix (Mm00504574_m1), osteocalcin (Mm03413826_mH), Flk1 (Mm01222421_m1), and von Willebrand factor (Mm00550376_m1) were obtained from Applied Biosystems as part of Taqman® Gene Expression Assays. ## 4.3. Pre-Sorting of tdTomato Positive Cells The pre-sorting of aortic tdTomato positive cells was performed as previously described [25]. The aortas were perfused briefly with dispase and enzymatically dispersed. Then, the aortas were dissected into small pieces and incubated for 45 min prior to cell isolation, fixation, staining, and FACS analysis. ## 4.4. Immunoblotting Immunoblotting was performed as previously described [17]. Equal amounts of cellular protein or tissue lysates were used. These include SMAD1 (Cell Signaling Technology, 9743), β-catenin (R&D system, AF1329. Minneapolis, MN. USA), osterix (Santa Cruz Biotechnology, sc-22536. Dallas, TX, USA), Flk1 and VE-cadherin (all from BD Bioscience, 55,307 and 562,242, San Jose, CA, USA), and vWF (Dako, A0082, Santa Clara, CA, USA). β-Actin (Sigma-Aldrich, A2228. Saint Louis, MO, USA) was used as a loading control. ## 4.5. Quantification of Aortic Calcium Total aortic calcium was measured using a calcium assay kit (Bioassay) as previously described [25]. ## 4.6. Alizarin Red Staining Slides were stained with Alizarin red solution ($2\%$ Alizarin red in distilled water) for 2 min. Then, excess solution was removed. The sections were dehydrated in acetone, followed by acetone-xylene (1:1) solution. After that, the sections were cleared by xylene and mounted with mounting medium. ## 4.7. Lesion Quantification The mice were euthanized, and then perfusion fixed with $10\%$ buffered formalin via the left ventricle for 4 min. The proximal aorta was excised. The specimen was embedded in OCT (Tissue-Tek, Fisher Scientific, Waltham, MA, USA), frozen on dry ice, and stored at −80 °C until sectioning. Serial cryosections were prepared. From then on, every fifth 10-μm section was collected on poly-D-lysine–coated slides. Sections were stained with hematoxylin and Alizarin red. Slides were examined by light microscopy, and the lesion area was quantified with computer-assisted image analysis (Image-Pro Plus, Media Cybernetics, Bethesda, MD, USA). ## 4.8. Statistical Analysis Data were analyzed for statistical significance by ANOVA with post hoc Tukey’s analysis. The analyses were performed using GraphPad Instat®, version 3.0 (GraphPad Software). Data represent mean ± SD. $p \leq 0.05$ was considered significant, and experiments were performed a minimum of three times. ## 5. 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--- title: Repurposing Astragalus Polysaccharide PG2 for Inhibiting ACE2 and SARS-CoV-2 Spike Syncytial Formation and Anti-Inflammatory Effects authors: - Chia-Yin Lee - Anh Thuc Nguyen - Ly Hien Doan - Li-Wei Chu - Chih-Hung Chang - Hui-Kang Liu - I-Lin Lee - Teng-Hsu Wang - Jin-Mei Lai - Shih-Ming Tsao - Hsiu-Jung Liao - Yueh-Hsin Ping - Chi-Ying F. Huang journal: Viruses year: 2023 pmcid: PMC10054482 doi: 10.3390/v15030641 license: CC BY 4.0 --- # Repurposing Astragalus Polysaccharide PG2 for Inhibiting ACE2 and SARS-CoV-2 Spike Syncytial Formation and Anti-Inflammatory Effects ## Abstract The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious threat to global public health. In an effort to develop novel anti-coronavirus therapeutics and achieve prophylactics, we used gene set enrichment analysis (GSEA) for drug screening and identified that Astragalus polysaccharide (PG2), a mixture of polysaccharides purified from Astragalus membranaceus, could effectively reverse COVID-19 signature genes. Further biological assays revealed that PG2 could prevent the fusion of BHK21-expressing wild-type (WT) viral spike (S) protein and Calu-3-expressing ACE2. Additionally, it specifically prevents the binding of recombinant viral S of WT, alpha, and beta strains to ACE2 receptor in our non-cell-based system. In addition, PG2 enhances let-7a, miR-146a, and miR-148b expression levels in the lung epithelial cells. These findings speculate that PG2 has the potential to reduce viral replication in lung and cytokine storm via these PG2-induced miRNAs. Furthermore, macrophage activation is one of the primary issues leading to the complicated condition of COVID-19 patients, and our results revealed that PG2 could regulate the activation of macrophages by promoting the polarization of THP-1-derived macrophages into an anti-inflammatory phenotype. In this study, PG2 stimulated M2 macrophage activation and increased the expression levels of anti-inflammatory cytokines IL-10 and IL-1RN. Additionally, PG2 was recently used to treat patients with severe COVID-19 symptoms by reducing the neutrophil-to-lymphocyte ratio (NLR). Therefore, our data suggest that PG2, a repurposed drug, possesses the potential to prevent WT SARS-CoV-2 S-mediated syncytia formation with the host cells; it also inhibits the binding of S proteins of WT, alpha, and beta strains to the recombinant ACE2 and halts severe COVID-19 development by regulating the polarization of macrophages to M2 cells. ## 1. Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a positive-strand-enveloped RNA virus identified during the pneumonia outbreak in December 2019, causes a human disease called coronavirus disease 2019 (COVID-19) [1]. During viral replication, the spike (S) protein cleaves into two subunits, S1 and S2. S1 is responsible for binding to host cell angiotensin-converting enzyme 2 (ACE2) receptors, and S2 is primarily involved in regulating viral fusion and entry into the host cell by forming a six-helical bundle via the two-heptad repeat domain [2]. Viral enzymes, proteins, and cytokines involved in virus entry, replication, and host macrophage overreaction are potential drug targets for the development of therapeutic options for SARS-CoV-2 [3]. Patients initially infected with SARS-CoV-2 have symptoms similar to those of the flu. Rapid replication of the viral genome leads to continuous activation of the immune system. Macrophages are multifaceted within the alveolar space, and their distinct functions depend highly on their polarization, generally characterized as M1 or M2 macrophages. Based on distinct gene expression and functional profiles, M1 macrophages are proinflammatory macrophages that are crucial against pathogens, whereas M2 macrophages inhibit inflammation and modulate the repair of damaged tissues [4,5]. Notably, M1 macrophages dampen the growth and enhance the apoptosis of lung cells. Conversely, inhibition of viral entry using an ACE2-blocking antibody substantially enhances the activity of M2 macrophages [6]. Thus, we propose that increased M2 macrophage polarization improves the inflammatory lung microenvironment. Due to permanent damage to alveolar and endothelial cells and alveolar–capillary barrier interruption, patients commonly present with dyspnea and persistent symptoms of viral pneumonia, including decreased oxygen saturation and lymphocytosis, together with ground-glass images and alveolar exudates with intralobular involvement on lung imaging. As a result, these symptoms rapidly progress to severe acute lung injury—called acute respiratory distress syndrome (ARDS) [7,8]—and septic shock, eventually leading to multiple organ failure. Due to an excessive immune response, surviving patients suffer from long-term symptoms, including fatigue, dyspnea, and cognitive dysfunction and generally have an impact on everyday functioning [9]. Currently, there is no fully proven treatment for COVID-19 patients with excessive inflammation. Some anti-inflammatory and antifibrotic drugs, such as pirfenidone and nintedanib, are considered to reduce ARDS-induced lung damage. However, neither has been studied in the case of acute exacerbations nor ARDS due to the possible consequence of liver toxicity and increased patient’s risk of bleeding [10,11,12]. PG2® lyophilized injection (PhytoHealth Corporation, Taipei, Taiwan) is an injectable medicinal product containing an active fraction of Astragalus polysaccharides which is extracted, isolated, and purified from the roots of *Astragalus membranaceus* (Huangqi in Chinese). The roots of Astragalus membranaceus, also known as Astragali radix, have long been used to treat “qi deficiency (lack of energy)” in traditional Chinese medicine (TCM) [13,14]. It has been clinically proven to ease fatigue among advanced cancer patients and has been approved by the Taiwan Food and Drug Administration (TFDA) as a prescription drug for relieving cancer-related fatigue (CRF). As included in the approved label of PG2, it can stimulate medullary hematopoiesis and enhance immune function [15]. It was reported that PG2 can increase the activity of natural killer cells (NK cells) and production of IL-2 as well as enhance resistance in normal mice by regulating the immune system and prolonging survival under the dual insults from X-ray radiation at the median lethal dose and invasion by cytomegalovirus (CMV) [15]. Current clinical research has reported that PG2 could decrease the neutrophil-to-lymphocyte ratio (NLR), which is a chronic inflammation marker and a prognostic indicator of worse clinical outcomes in several cancer types [16]. NLR on admission is also considered a predictor of the severity and mortality of COVID-19 patients in the latest reports [17,18]. Wang et al. recently reviewed the successful management of COVID-19 cases at Chung-shan Medical University Hospital, Taichung, Taiwan, including four patients receiving standard care who had high NLRs and marked lymphopenia and were treated with PG2 during hospitalization [19]. The decrease in NLR in these four patients was faster than that in other patients who did not receive PG2, and all four cases successfully recovered from severe COVID-19 symptoms [19]. The current report sheds light on the positive effects of Astragalus polysaccharides against life-threatening outcomes of the disease in COVID-19 patients. Based on our previous research on in silico analysis, Astragalus polysaccharides were identified to be a promising treatment for COVID-19 [20]. Gene set enrichment analysis (GSEA) of the PG2 treatment transcriptional profile showed that PG2 can reverse COVID-19 signatures (MSigDB database) as well as ARDS (GSE76293), thus providing the rationale for PG2 as a potential therapy against SARS-CoV-2 infection. In addition, biological experiments also indicated that Astragalus polysaccharides inhibited the binding of SARS-CoV-2 S protein to ACE2 and blocked the fusion ability of the S protein. Furthermore, in lung epithelial cells, PG2 treatment can increase the expression levels of let-7a, miR-146a, and miR-148b, whose functions have been shown to target the viral genome to prevent viral replication and regulate the Toll-like receptor (TLR) signaling pathway to prevent overactivation of macrophages and cytokine storm [7,21,22]. Our study elucidates PG2 mechanisms that support its benefits for future usage; PG2 can elevate miRNAs having antiviral potential and anti-inflammatory ability of macrophages, thereby driving M2 macrophage polarization. ## 2.1. PG2 Injection PG2 Injection was provided by PhytoHealth Corporation (Taipei, Taiwan) through a series of proprietary processes—including water extraction of *Astragalus membraneous* (AM) root, ethanol precipitation, condensation, filtration, purification, and spray drying—to obtain highly purified (>$90\%$) polysaccharides with average molecular weights ranging from 20,000 to 60,000 Da. The major polysaccharides in this product were α-1,4-linked glucans, with a certain degree of branching at six positions on the backbone residues. Other components of this product included arabinogalactans, rhamnogalacturonans, and arabinogalactan proteins. The composition of PG2 and its determination methods have been previously described in [23]. ## 2.2. L1000 Gene Expression Profiling M2 cells were treated with PG2 (32 mg/mL) for 6 h, and gene expression profiling was performed using L1000 expression profiling by Genometry, Inc., Cambridge, MA, USA. The L1000 profiling protocol includes the capture of mRNA transcripts from whole-cell lysates by oligo-dT followed by the generation of cDNAs via reverse transcription and amplification using polymerase chain reaction (PCR). To determine the expression levels of 978 landmark genes, the PCR amplicon was hybridized to barcoded Luminex beads, and specific probes were annealed to the cDNA. ## 2.3. Gene Set Enrichment Analysis (GSEA) For each gene set, GSEA determined the enrichment score and subsequently normalized the score according to its size. The score can be positive or negative, which demonstrates that a gene set is enriched at the top or bottom of the list of ranked genes, respectively, based on expression levels. The C2 gene set collection included in the MSigDB v.7.4. database was utilized in the GSEA in this study. The GSE76293 microarray for ARDS signature was retrieved from the Gene Expression Omnibus (GEO), which was pre-processed using the limma package. GSEA was performed using 1000 permutations with a gene set permutation type. ## 2.4. Cell Culture Baby hamster kidney (BHK)-21 cells, a fibroblast cell line derived from baby hamster kidneys (ATCC, cat. no. CCL-10), were cultured in Dulbecco’s Modified Eagle Medium (DMEM, Gibco, cat. no. 12100046) and supplemented with $10\%$ FBS and 1 × penicillin/streptomycin solution. BHK-21 was incubated at 37 °C in a $5\%$ CO2 atmosphere and trypsinized every 2 days. After seeding for 24 h, cells were used for plasmid transfection and cytotoxicity assay. Calu-3 cells, a human epithelial lung cell line derived from a patient with lung adenocarcinoma (ATCC, cat. no. HTB-55), were cultured in Dulbecco’s Modified Eagle Medium (DMEM, Gibco, cat. no. 12100046) and supplemented with $10\%$ FBS and 1 × penicillin/ streptomycin solution. Calu-3 was incubated at 37 °C in a $5\%$ CO2 atmosphere and trypsinized every 3–4 days. After seeding for 48 h, cells were used for cell–cell fusion assay, cytotoxicity assay, and western blotting assay. BEAS-2B, a human normal bronchial epithelial cell line (ATCC, cat. no. CRL-9609), was cultured in RPMI medium supplemented with $10\%$ FBS (Invitrogen, ThermoFisher, Waltham, MA, USA), $1\%$ PSA, $1\%$ nonessential amino acid, and 2 mM L-glutamate (Invitrogen). Cells were maintained at 37 °C with $5\%$ CO2 in a cell incubator and passaged every 3–4 days. For the experiment, the cell line was used at an early passage (before passage 6). The human monocytes THP-1 cell line (BCRC, cat. no. 60430) used in this study was obtained from the Bioresource Collection and Research Center (BCRC) and was cultured in RPMI 1640 medium with high glucose (Gibco, cat. no. A1049101). The RPMI medium was supplemented with $10\%$ FBS (Gibco, cat. no. A2720803), 100 IU/mL penicillin, and 0.1 mg/mL streptomycin. THP-1 monocytes were differentiated into macrophages by 24 h incubation with phorbol 12-myristate 13-acetate (PMA) at 50 ng/mL followed by 24 h incubation in RPMI medium for ELISA, qRT-PCR, and western blotting assay. ## 2.5. Cell–Cell Fusion Assay The assay was performed as previously described [24]. Briefly, on a six-well plate, donor BHK-21 cells were seeded at 4 × 105 cells/well and transfected with both EGFP and S plasmids (Wuhan strain) at a ratio of 1:5 using Lipofectamine™ 2000 Transfection Reagent (Invitrogen, cat. no. 11668019). After 24 h, 1 mL of enzyme-free PBS-based cell dissociation buffer (Gibco, cat. no. 13151014) was added to each well, and the cells were allowed to resuspend in serum-free DMEM (Gibco, ThermoFisher, Waltham, MA, USA). The cells were then cocultured with human lung cancer Calu-3 cells seeded in a single layer to induce cell–cell interactions in the presence or absence of PG2 (0.2, 0.67, or 2 mg/mL). The cocultured cells were then incubated at 4 °C for 1 h. The unbound cells were then removed using PBS, and the growth medium was replaced. Initial images of EGFP-positive cells in five random areas were used to evaluate the binding efficiency. An inverted fluorescence microscope (Olympus IX70) was used to capture the images. Furthermore, the corresponding doses of PG2 were added and incubated for 4 h at 37 °C. Images of five fields of EGFP-positive cells were randomly taken as previously described, indicating fusion efficiency. The quantification of binding efficiency and syncytial cell formation was performed as previously described [24]. ## 2.6. Trimeric S Protein Assay Enzyme-linked immunosorbent assay (ELISA) was performed to examine the ability of PG2 to intervene in the ability of wild-type trimeric SARS-CoV-2 S protein (Wuhan strain) or variants (α, β, γ, δ) to bind to biotinylated human ACE2 recombinant protein. The experimental procedures were performed as previously described [24]. Briefly, each well of a 96-well plate was coated overnight at 4 °C with 500 ng/mL of S protein (Cat. no. GTX135972-pro; GeneTex, Irvine, CA, USA) diluted in coating buffer containing 15 mM sodium carbonate and 35 mM sodium hydrogen carbonate at pH 9.6. The next day, after washing three times with washing buffer (PBS with $0.05\%$ (v/v), Tween-20 (pH 7.4)), 300 μL of blocking buffer prepared from washing buffer supplemented with $0.5\%$ (w/v) bovine serum albumin (BSA) for 1.5 h at 37 °C was added. Different doses of PG2 (1, 2, 4, 8 mg/mL) or 10 μg/mL of inhibitor (GeneTex, cat. no. GTX635791) were then replaced and incubated for 1 h at 37 °C. Next, the plate was incubated at 37 °C for 1 h with 125 ng/mL of biotinylated human ACE2 protein (Cat. no. AC2-H82E6-25ug; ACROBiosystems, OX, London, UK). Next, 100 ng/mL/well of Streptavidin-HRP conjugates (GeneTex, cat. no. GTX635791) was added and incubated for another 1 h at 37 °C. Finally, the washed plate was incubated with 200 μL of TMB substrate per well for an additional 1 h at 37 °C in the dark. A stop solution (50 µL) was used to block the reaction. The absorbance was measured at 450 nm using a microplate reader (Cytation 5, BioTek, Winooski, VT, USA). ## 2.7. qRT-PCR Analysis BEAS2B cells were used to screen for biological agents that affect respiratory tract infection mechanisms. To determine whether the candidate drugs can induce let-7a, miR-148, and miR-146 expression levels, 1 × 106 cells were seeded in a 10-cm dish for at least 16 h before 24 h of drug treatment. Total RNA from the cells was extracted using the RNA Extraction Kit (Cat. no. DR100; Geneaid, New Taipei City, Taiwan). TRIzol reagent (Invitrogen) was used to lyse cells, allowing DNA to bind to the genomic DNA mini spin column. The flow-through containing RNA was then transferred to the RNA mini spin column for RNA binding. Contaminants were removed using a wash buffer, and the purified total RNA was eluted in RNase-free water. This process was followed according to the manufacturer’s instructions. Additionally, 1 μg of total RNA was used for reverse transcription using the SuperScript III First-Strand Synthesis Kit (Invitrogen) and oligo-dT priming as per the manufacturer’s instructions. For qPCR, cDNA was amplified using SYBR green PCR master mix (Applied Biosystems, ThermoFisher, Waltham, MA, USA). The real-time PCR primers used in the assay were forward sequences specific for has-let-7a-5p (5′-GCCTGAGGTAGTAGGTTGTATAGTTA-3′), hsa-miR148b-5p (5′-AAGUUCUGUUAUACACUCAGGC-3′), hsa-miR-146a (5′-UGAGAACUGAAUUCCAUGGGUU-3′), and U54 (homo) (5′-GGTACCTATTGTGTTGAGTAACGGTGA-3′). U54 was used as an internal control. ## 2.8. Western Blotting Cells were exposed to different treatments at different time points as indicated in the Section 3 and figure legends; later, they were harvested and lysed on ice with RIPA lysis buffer, followed by centrifugation at 12,000× g for 10 min. The lysate was subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and the proteins were electrotransferred onto polyvinylidene fluoride membrane. The membrane was then blocked with $5\%$ non-fat dry milk in Tris-buffered saline at room temperature for 1 h and incubated with the primary antibody overnight, followed by secondary antibody incubation for 1 h. Immunoreactive bands were visualized using enhanced chemiluminescence (ECL) (Thermo cat. no. 34580). Images were captured using a Luminescence Imaging system (LAS 4000™M, Fuji Photo Film Co., Ltd., Minato, Tokyo, Japan). The densities of the bands were measured using Image J software. The ratio of proteins to the internal control (GAPDH or α-tublin) were calculated. The relative expression levels of proteins were normalized to the control group, which was assigned a value of 1. The following antibodies were used: rabbit anti-CD163 monoclonal antibody (1:1000, cat. no. ab182422; Abcam Inc., Toronto, ON, Canada); rabbit anti-CD86 monoclonal antibody (1:1000, Abcam, cat. no. ab239075); rabbit anti-GAPDH monoclonal antibody (1:10,000, GeneTex, cat. no. GTX100118); Peroxidase AffiniPure Goat Anti-Rabbit IgG (1:5000, Jackson Lab, cat. no. 111-035-045); rabbit anti-ACE2 monoclonal antibody (1:3000, GeneTex, cat. no. GTX01160); rabbit anti-TMPRSS2 polyclonal antibody (1:2000, GeneTex, cat. no. GTX64544); and rabbit anti-α-tubulin polyclonal antibody (1:3000, GeneTex, cat. no. GTX112141). ## 2.9. Induction of Human M2 Macrophages and FACS Analysis Following a literature protocol [25], human macrophage preparation was conducted by freshly isolating peripheral mononuclear cells from the blood of healthy donors following standard density gradient centrifugation with Ficoll-Paque. CD14+ cells from peripheral mononuclear cells were purified via high-gradient magnetic sorting. CD14+ monocytes were cultured for six days in a complete RPMI-1640 medium supplemented with 10 ng/mL human macrophage colony-stimulating factor (M-CSF) for the induction of macrophages. CD14+ monocytes were differentiated into an M2-like phenotype: M-CSF for seven days, followed by 20 ng/mL IL-4 for an additional day. For FACS analysis, human M2 macrophages were stained with monoclonal mouse anti-human CD163 (Cat. no. 155306; BioLegend, San Diego, CA, USA) and CD206 (mannose receptor, MR) antibodies (BioLegend, cat. no. 321152). The cells were suspended in PBS at a density of 1 × 105 cells/mL. A $5\%$ BSA buffer was used to block nonspecific antigens. The cells were analyzed using a CytoFLEX flow cytometer (Beckman Coulter, Brea, CA, USA). Nonspecific mouse immunoglobulin was used as the isotype control. For measuring the production of IL-10 and IL-1RN, ELISA was used. Concentrations of IL-10 (BioLegend, cat. no. 430604) and IL-1RN (Cat. no. DRA00B; R&D Systems, Minneapolis, MN, USA) levels in the supernatants of human M2-like macrophages were measured using commercially available ELISA kits (Human IL-1RN, R&D, Cat. no. DY280; Human IL-10, R&D, Cat. no. DY217B). The ELISA was performed according to the manufacturer’s instructions. ## 2.10. Statistics Data are presented as the mean ± standard error of the mean. Statistical calculations were performed using the GraphPad Prism software (GraphPad, San Diego, CA, USA). One-way analysis ANOVA with Dunnett’s test was used for multiple comparisons. Single-parameter comparisons were performed using unpaired Student’s t-tests. p-values of less than 0.05, 0.01, and 0.001 were considered significant. ## 3.1. GSEA Reveals the Effect of PG2 on Reversing COVID-19 Signatures Gene expression profiles of M2 macrophages treated with PG2 were analyzed via GSEA to identify potential novel indications, as well as the underlying mechanism. Interestingly, GSEA suggested that treatment with PG2 could reverse the SARS-CoV-2 infection signatures; the genes increased/decreased in the disease conditions can be decreased/increased after drug treatment. The COVID-19 signature was described by Blanco-Melo et al. [ 26] as genes being up/downregulated by SARS-CoV2 infection compared to other respiratory viruses, indicating unique signatures of COVID-19. From the transcriptional responses to PG2 treatment, we observed that the SARS-CoV-2 signature in Calu-3 and bronchial epithelial cells was reduced, in which genes upregulated by SARS-CoV-2 infection were downregulated (NES < 0). Moreover, strongly enhanced genes in postmortem lung samples from COVID-19-positive patients were also decreased by PG2 treatment (NES = −2.58) (Table 1, Figure 1A–C). In contrast, the GSEA results also indicated an anti-SARS-CoV-2 effect of PG2 via a reduction in the gene set of the COVID-19 adverse outcome pathway (WikiPathways—WP4891), maturation of the SARS-CoV-2 S protein (Reactome—R-HSA-9694548), translation of SARS-CoV-2 structural proteins (Reactome—R-HSA-9694635), and SARS-CoV-2 infection (Reactome—R-HSA-9694516) (Table 1, Supplementary Figure S1A–D). The effect of PG2 on ARDS was also investigated using the ARDS signature obtained by significantly upregulated genes in blood polymorphonuclear neutrophils (PMNs) from patients with ARDS (GSE76293). A negative NES indicated that PG2 was able to reduce the number of genes upregulated in ARDS patients (Table 1, Figure 1D). Given that ferroptosis has been elucidated in SARS-CoV-2-induced multi-organ damage [27], PG2 might also reduce ferroptosis to cure COVID-19 as the transcriptional profile of PG2 treatment showed a significant decrease in gene sets related to ferroptosis (WikiPathways—WP4313) and iron uptake and transport (Reactome—R-HSA-917937) (Table 1, Supplementary Figure S1E,F). ## 3.2. Suppression of SARS-CoV-2 S Protein-Mediated Syncytium Formation by PG2 Receptor-dependent syncytial formation promoted by the SARS-CoV-2 S protein on the cell membrane is a crucial step in the cellular invasion of SARS-CoV-2 [28,29,30]. Indeed, clinical evidence of infected syncytial pneumocytes in COVID-19 patients who died implies a high correlation between pneumocyte syncytia and severe COVID-19 pathogenesis [31,32]. Hence, we investigated the binding efficiency of EGFP-S-positive BHK-21 cells and hACE2-receptor-expressing Calu-3 cells treated with PG2 in a cell–cell fusion assay. The attachment between BHK-21 cells and Calu-3 cells represents the binding of the SARS-CoV-2 S protein to the ACE2 receptor. Syncytial formation caused by the fusion of BHK-21 and Calu-3 cells was quantified to evaluate the PG2 inhibitory effect. As shown in Figure 2, there was no significant difference in the number of EGFP-positive cells between the three PG2-treated groups and the control group (Figure 2A, upper panel; Figure 2B, gray bars). After an additional 4 h of incubation, multinucleated giant cells with expanded EGFP signals were detected in the control treatment, suggesting the formation of a S-mediated syncytium. Compared to the control group, more than $20\%$ and $40\%$ of the area of EGFP-positive syncytium was reduced in the presence of 0.67 and 2 mg/mL PG2 treatment, respectively (Figure 2A, bottom panel; Figure 2B, white bars). However, the unchanged expression levels of ACE2 and TMPRSS2 after 5 h of PG2 treatment were validated by western blot (Supplementary Figure S2). These results indicate that PG2 could suppress the formation of WT SARS-CoV-2 S protein-mediated syncytium in a dose-dependent manner between BHK-21 and Calu-3 cells in an in vitro system. The current results suggest that PG2 could be effective against SARS-CoV-2 by inhibiting membrane fusion. However, this needs to be validated by inducing SARS-CoV-2 infection and utilizing PG2 to study its efficiency. ## 3.3. The Inhibitory Effect of PG2 on the Binding of SARS-CoV-2 S Protein with ACE2 Is Variant Specific We compared the potential inhibitory effects of PG2 on the current circulating variants by employing an ELISA-based trimeric S protein binding assay. As shown in Figure 3, the presence of PG2 at concentrations between 1 and 8 mg/mL marginally reduced the binding efficiency of the trimeric S protein from the wild-type, alpha, and beta variants (Figure 3A–C). Among these three types, PG2 appeared to be more effective when confronted with S proteins from the alpha and beta strains. In contrast, PG2 had only a modest effect on the gamma variant (Figure 3D) and did not affect the delta variant (Figure 3E). ## 3.4. PG2 Elevates Let-7a, miR-148b, and miR-146a Expression Levels Previous studies demonstrated that condensed extracts, APS and APS-L, from Astragalus polysaccharides could effectively block inflammation and viral replication by increasing the levels of let-7a, miR-148b, and miR-146a [20]. Thus, we examined the efficacy of PG2, the highly purified Astragalus polysaccharides, on inducing these targeted miRNAs by measuring their expression levels in BEAS2B cells after 24 h of PG2 treatment using qRT-PCR. The results indicated that PG2 was efficient in enhancing the expression of all three targeted miRNAs at both doses, but the effect of the low dose was slightly more prominent than that of the high dose. In this part, PG2 100 and 1000 µg/mL significantly augmented let-7a, miR-148b, and miR-146a expression 2.7- and 2.4-fold, 1.6- and 1.2-fold, and 1.6- and 1.3-fold (Figure 4A–C), respectively. These results suggested that PG2 can effectively enhance let-7a, miR-148b, and miR-146a expression levels. ## 3.5. PG2 Differentiates THP-1-Derived Macrophages into M2-like Phenotype To investigate the polarization effect in macrophages of PG2, THP-1 monocytes were incubated with PMA (50 ng/mL) for 24 h, followed by incubation with fresh medium to differentiate M0-type macrophages. M0-type macrophages were treated with different PG2 doses for 24 and 48 h. CD163, a scavenger receptor, is widely used as a marker for M2 macrophage polarization and inflammation [33]. According to the western blotting results, the expression levels of the CD163 significantly increased in a dose- and time-dependent manner post-incubation with PG2. These results indicated that PG2 could polarize macrophages toward the M2 type (anti-inflammatory type) (Figure 5). ## 3.6. PG2 Stimulates Human Monocyte to M2 Macrophage Transition M2 macrophages have anti-inflammatory functions and alleviate cytokine storms in severe COVID-19 [6]. To further investigate whether PG2 might increase M2 polarization, human-monocyte-derived macrophages were treated with either PG2 or IL-4. The interleukin 4 receptor (IL-4R) can bind to IL-4 and induce anti-inflammatory immune activity. IL-4 was reported to activate M2 macrophages that express CD163 and CD206 markers [34] and anti-inflammatory cytokines, such as IL-10 and IL-1R antagonist (IL-1RN) [35]. M2 macrophages have anti-inflammatory functions and alleviate cytokine storms in severe COVID-19 [6]. To determine the effectiveness of PG2 in promoting anti-inflammatory capacity, we investigated whether PG2 could stimulate M2 macrophage polarization. To analyze whether PG2 could modify macrophage differentiation, PG2 cells were treated with CD14-enriched cells and evaluated for the induction of macrophage-associated cell surface antigens described above. M2 macrophage differentiation was demonstrated by the upregulation of CD163 and CD206 (Figure 6A,B). Interestingly, CD14-enriched cells exposed to PG2 showed increased protein expression of CD163 and CD206 without IL-4 stimulation. As anticipated, the percentage of CD163+CD206+-expressing M2 macrophages treated with PG2 was significantly increased, as confirmed by flow cytometry. Furthermore, the anti-inflammatory cytokines IL-10 and IL-1RN were increased during M2 macrophage polarization. Our results showed that PG2 significantly increased IL-10 and IL-1RN levels (Figure 6C). These results indicated the anti-inflammatory capacity of PG2 by stimulating M2 macrophage differentiation and anti-inflammatory cytokine secretion. ## 4. Discussion As of 11 August 2022, according to the US FDA, there were more than 640 incoming drug development projects, 470 trials in review, 12 treatments approved for emergency use, and 2 approved treatments—including remdesivir and baricitanib. Although lower fatality rates and clinical improvements in the early stages of infection were observed [36,37], these approved drugs showed no significant improvement in response to severe COVID-19 in various patients [38]. The process of SARS-CoV-2 infection begins with the attachment of viral S protein to the human ACE2 receptor, resulting in entry into the cells and causing extensive cell damage. This further triggers cytokine levels, leading to ARDS and multiple organ failure. Considering that prevention is believed to be better than cure, the search for drugs to prevent viral infections and the onset of severe illness requires relentless effort. Learning from the experience from the use of Chinese herbal medicines after decades treating epidemics, there is still an urgent need to provide complementary and alternative treatments for the management of patients with SARS-CoV-2 infection [39,40]. In an effort to rapidly find a drug that can treat COVID-19, we have utilized a bioinformatics approach to rapidly screen for a potential drug, and we identified PG2. Previous studies has revealed transcriptome fingerprints of COVID-19 infections [26], which we can use to screen among our drug response transcriptome library for potential compounds to reverse the disease signature via GSEA. This method can be applied for other diseases to quickly identify potential therapy for future pandemic similar to the COVID-19 situation. PG2 has been shown in previous clinical trials to be effective in modulating the immune system in humans, as well as having fewer side effects and a high safety profile. To elucidate the potential pharmacological mechanisms and targets of PG2 with suggestions from the GSEA results we discovered that PG2 has the potential to treat COVID-19 by inhibiting its fusion activity, modulating miRNAs in lung epithelial cells, and effectively regulating macrophage activity. A schematic summary of the potential mechanisms of PG2 targeting SARS-CoV-2 and ARDS is shown in Figure 7. PG2 not only acts as a fusion inhibitor of viral infection in the host cells but also has the potential to inhibit viral replication by inducing let-7a, miR-148b, and miR-146a miRNA expression, stimulating M2 macrophage differentiation and triggering the secretion of anti-inflammatory cytokines, including IL-10 and IL-1RN. Our results are labeled in red, while the potential mechanisms of PG2 are labeled in green. Figures were created using BioRender.com. Unlike SARS-CoV, which uses the endosomal membrane fusion pathway to infect host cells, SARS-CoV-2-infected cells form the syncytium, suggesting that SARS-CoV-2 can primarily use the plasma membrane fusion pathway to invade and replicate within host cells [3,41]. Consistently, in a cell–cell fusion assay, the SARS-CoV-2 S protein can efficiently regulate syncytium formation between the donor and receiving cells in the absence of exogenous protein hydrolases such as trypsin, whereas the SARS-CoV S protein cannot. In fact, for the majority of viruses, endosomal membrane fusion tends to activate host cell antiviral immunity; therefore, it is less effective than plasma membrane fusion [42,43]. In addition, the S-protein-mediated membrane fusion not only participates in the SARS-CoV-2 entry process but also plays other potential roles in severe COVID-19 pathogenesis, such as promoting viral dissemination, immune escape, and inflammatory response [44]. Therefore, S-protein-mediated membrane fusion is a potent target for the development of anti-SARS-CoV-2 drugs [31]. Recent reports have shown that SARS-CoV-2 primarily uses host proteases, such as TMPRSS2 and furin, for plasma membrane fusion [29,45], and PG2 could effectively inhibit the fusion ability of S protein, which is presumed to be a potential drug for preventing the fusion of viruses and their further progression. The binding of the viral S protein to the human ACE2 receptor initiates the host cellular invasion of SARS-CoV-2, enabled by the receptor-binding domain (RBD) region on S1 of the SARS-CoV-2 S protein during viral binding and the fusion peptide (FP) on S2 responsible for viral fusion [46]. During host cell entry, the linkage between glycans and complexed sugar molecules on the viral surface and host cells via glycoproteins is essential [47]. Although glycans present on the S protein contribute negligibly to viral binding, they play a substantial role in viral cell invasion and fusion with the host cell [48]. Considering that Astragalus-based formulas contain polysaccharides, such as β-galactosidase, to explain the role of PG2 in repressing fusion, we hypothesized that PG2 could compete with the S2 subunits or glycans on the surface of S proteins. Using an ELISA-based binding assay, the interference of trimeric S protein and hACE2 binding in the presence of PG2 was clearly demonstrated. Interestingly, such inhibitory effects were variant-specific, and PG2 appeared to be more effective when confronted with wild-type, alpha, and beta variants (Figure 3). Moreover, the different results of the binding of SARS-CoV-2 S protein ACE2 between cell–cell fusion assay and ELISA binding assay might be due to the assay conditions (Figure 2 and Figure S2). In the cell–cell fusion assay, in addition to ACE2, there are additional cellular factors that interact with SARS-CoV-2 to facilitate or stabilize the binding of the S protein with ACE2 [49]. Furthermore, the SARS-CoV-2-S protein expressed on BHK-21 might undergo post-translational modifications (PTMs), such as glycosylation and palmitoylation, which are critical for SARS-CoV-2-S protein-mediated membrane fusion and infection [50]. Therefore, we speculated that additional host factors and PTMs might reveal not only different results from various experimental approaches but also various responses of SARS-CoV-2 variants to the treatment of PG2. In addition to inhibiting the fusion ability of S protein, PG2 significantly enhanced miRNA expression in lung epithelial cells. Nearly all biological processes, including development, hemostasis, and inflammation, are regulated by miRNAs. miRNAs are small non-coding RNAs that regulate gene expression by targeting mRNAs [51]. Several miRNAs have been observed to have viral inhibitory effects by targeting the viral RNA genome and/or inhibiting the expression of virus-dependent cellular cofactors [52,53]. PG2 significantly increased the expression levels of let-7a in lung epithelial cells (Figure 4A). Let-7 is a family of human cells consisting of 13 members. Let-7a has been reported to suppress IL-6 expression [54,55], an abundant inflammatory factor induced by SARS-CoV-2. Furthermore, it has also been reported that in THP-1 cells pri-let-7a overexpressing, let-7a not only decreased the IL-6 mRNA level but also significantly reduced the expression of several other SARS-CoV-2 related pro-inflammatory cytokines and chemokines, including IL-1β, IL-8, GM-CSF, and TNF-α [56]. In addition to cytokine storm inhibition, let-7a was also believed to be effective in inhibiting SARS-CoV-2 RNA and protein expression, as well as viral replication [57]. Our results also demonstrated that PG2 could be a potential drug to inhibit the replication of SARS-CoV-2 in lung epithelial cells and suppress cytokine storms by inducing the expression of let-7a. Additionally, we used the Mienturent database, an interactive web tool for miRNA-target enrichment and network-based analysis, to identify the signaling pathways regulated by hsa-let-7a-5p, hsa-miR-148b-5p, and hsa-miR-146a-5p. *The* genes targeted by these miRNAs were enriched to the AP-1 transcription factor network and the forkhead box O (FoxO) signaling pathway (Supplement Table S1). A previous study showed that the SARS-CoV accessory protein induces AP-1 transcriptional activity through the activation of the c-Jun N-terminal kinase (JNK) pathway [58]. Inhibition of NF-κB/JNK would be effective against sepsis-induced acute lung injury [59]. Currently, novel agents that suppress NF-κB/JNK signaling, including tocilizumab and baricitinib, have been approved for the treatment of SARS-CoV-2 [60,61]. Therefore, the direct effects of PG2 on these inflammatory pathways were investigated. Macrophages are ubiquitous in human organs and are present in large numbers in the lungs. Monocytes of bone marrow origin differentiate into alveolar macrophages, which serve as the first line of defense against invading organisms, such as pathogens and harmful substances [62,63,64]. Macrophages can be divided into two functional phenotypes. Excessive pathogenic infections may lead to enhanced M1 macrophage activity, resulting in the accelerated and massive production of inflammatory cytokines and chemokines, further leading to cytokine storms. In contrast, the activation of M2 macrophages triggers the release of anti-inflammatory cytokines, thereby limiting inflammation and promoting tissue repair [65]. Persistent enrichment of the alveolar space with pro-inflammatory monocytes and continued drive of alveolar inflammation has been observed in some patients infected with SARS-CoV-2 who developed severe pneumonia and ARDS [66]. To determine whether PG2 could effectively promote the conversion of macrophages to an anti-inflammatory phenotype, we differentiated THP-1 cells into THP-1 macrophages and observed that PG2 could effectively enhance the expression of CD163 (a marker of M2 macrophages) in THP-1 macrophages, indicating M2 polarization of PG2, which highlighted the anti-inflammatory effect of PG2. The clinical efficacy of anti-IL-6R in COVID-19 patients has been tested in a recent randomized, double-blind phase III COVACTA trial (NCT04320615; clinicaltrials.gov) but showed an insignificant decrease in fatality [67]. This is further evidence that cytokines other than IL-6 are involved in regulating pathological mechanisms. Considering the broad anti-inflammatory effects of M2 macrophages, M2-polarizing PG2 may play a vital role in balancing the inflammatory environment. It is alarming that convalescent patients, even those with mild COVID-19, can sustain persistent symptoms for months post-infection, referred to as “long COVID” [68]. No approved treatments are available for these patients. However, anti-inflammatory treatment is a potential medical support that can be provided to these patients, which may support our hypothesis that PG2 is a candidate for treating long-term COVID cases [69]. Accumulating data have revealed that cytokine storm is often related to COVID-19 pneumonia and its exacerbation in severe cases [70]. In particular, the innate immune response, which is mostly regulated by macrophages in response to SARS-CoV-2 infection, possibly contributes to ARDS [71]. Depending on their microenvironment, they are polarized to either the classically activated phenotype (M1) or alternatively activated phenotype (M2). It has been previously established that during SARS-CoV-2 infection, M2 macrophages are essential innate cells. Suppressing viral invasion by an anti-ACE2 antibody robustly improved the efficiency of M2 macrophages [6]. M2 macrophages are often polarized by IL-4 and/or IL-13 and exhibit high surface expression of CD163 and CD206. Our culture system revealed that PG2-induced human monocytes polarize into M2 macrophages and produce anti-inflammatory cytokines in the absence of IL-4 and/or IL-13 stimulation. In contrast, PG2-induced M2 macrophages exhibited similar phenotypes, as the levels of anti-inflammatory cytokines IL-10 and IL-1RN were substantially induced. These similar immune response patterns of M2 macrophages may suggest that PG2 can activate M2 macrophage differentiation but is independent of IL-4Ra and/or IL-13Ra signaling. Finally, PG2 can stimulate M2 macrophage activation and exert anti-inflammatory properties to prevent the pathogenesis of cytokine storms in lung damage caused by COVID-19. In conclusion, our bioinformatics platform delineates the moonlight role of PG2 via reversing the SARS-CoV-2 infection signatures. Empirically, PG2 not only blocks the binding of WT, alpha, and beta S proteins to recombinant ACE2 while suppressing WT viral entry into the host cells but also promotes M2 macrophage polarization and anti-inflammatory cytokine production. Our study rationalizes the efficacy of PG2 treatment in patients with severe COVID-19 symptoms due to a decrease in NLR. Considered together, these results suggest that PG2 is a potent repurposed drug with multiple effects in SARS-CoV-2-infected patients in the absence of effective approved drugs for COVID-19 treatment. ## References 1. 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--- title: Leaf Extract of Perilla frutescens (L.) Britt Promotes Adipocyte Browning via the p38 MAPK Pathway and PI3K-AKT Pathway authors: - Fancheng Chen - Silin Wu - Dejian Li - Jian Dong - Xiaowei Huang journal: Nutrients year: 2023 pmcid: PMC10054491 doi: 10.3390/nu15061487 license: CC BY 4.0 --- # Leaf Extract of Perilla frutescens (L.) Britt Promotes Adipocyte Browning via the p38 MAPK Pathway and PI3K-AKT Pathway ## Abstract The leaf of Perilla frutescens (L.) Britt (PF) has been reported to negatively affect adipocyte formation, inhibit body-fat formation, and lower body weight. However, its effect on adipocyte browning remains unknown. Thus, the mechanism of PF in promoting adipocyte browning was investigated. The ingredients of PF were acquired from the online database and filtered with oral bioavailability and drug-likeness criteria. The browning-related target genes were obtained from the Gene Card database. A Venn diagram was employed to obtain the overlapped genes that may play a part in PF promoting adipocyte browning, and an enrichment was analysis conducted based on these overlapped genes. A total of 17 active ingredients of PF were filtered, which may regulate intracellular receptor-signaling pathways, the activation of protein kinase activity, and other pathways through 56 targets. In vitro validation showed that PF promotes mitochondrial biogenesis and upregulates brite adipocyte-related gene expression. The browning effect of PF can be mediated by the p38 MAPK pathway as well as PI3K-AKT pathway. The study revealed that PF could promote adipocyte browning through multitargets and multipathways. An in vitro study validated that the browning effect of PF can be mediated by both the P38 MAPK pathway and the PI3K-AKT pathway. ## 1. Introduction Obesity is mainly caused by an imbalance of energy intake and consumption, which is characterized by a large number of lipids accumulated in white adipocytes [1]. Long-term excess white fat deposition not only changes the body shape but also increases the risk of diabetes and hyperlipidemia [2]. Interestingly, the beige adipocytes present in white adipose tissue are similar in structure and function to brown adipocytes, with more lipid droplets, and are rich in mitochondria and highly expressed thermogenesis markers of uncoupling protein 1 (UCP1) [3]. The promotion of adipocyte browning, which can increase the amount of beige or brite adipocytes, increases energy expenditure and could be a potential approach to prevent obesity. Several important molecules have been reported to play an important role in adipogenesis and browning regulation. Sakaguchi et al. [ 4] revealed that the phosphatase-binding protein Alpha4 (α4) plays an important part in adipogenesis and mitochondrial thermogenesis. It acts through the insulin signaling pathway. The knockout of α4 leads to impaired adipogenesis as well as thermogenesis but increased insulin resistance. Lee et al. [ 5] reported that regulated development and DNA damage response 1 (REDD1) upregulation can simulate preadipocyte differentiation through atypical IKK-independent NF-κB activation by sequestering IκBα from the NF-κB/IκBα complex. Adenosine monophosphate-activated protein kinase (AMPK) regulates energy balance and the metabolic switch. AMPK stimulates the catabolic pathway of adenosine triphosphate (ATP) production and shuts down the ATP-consuming anabolic pathway, respectively increasing energy production and expenditure [6]. Therefore, it also has been reported as a vital molecule for adipocyte browning. Traditional Chinese Medicine (TCM) is a rich resource to inspire novel insights into therapeutic approaches. Several herbs from TCM have been investigated for their pharmacological function in increasing calorie expenditure and reducing fat-tissue formation in mice. Cinnamon, the bark of trees of the Cinnamomum genus, has been proven to induce browning in the subcutaneous adipocytes of obese mice. Oral administration of cinnamon extract can promote UCP1 expression in the subcutaneous adipose tissue and reduce the body weight of obese mice [7]. The β3-adrenergic receptor (β3-AR) may be involved in cinnamon-extract-induced browning. Wang et al. [ 8] found that ginger can promote adipose-tissue browning by regulating the SIRT1/AMPK/PCG-1α pathway and upregulating the gene expression of beige adipocyte-selective markers. As a result, the identification of a safe herb that can promote white adipocyte browning is a feasible strategy for treating obesity and related pathophysiological conditions. It is interesting to note that both of the aforementioned herbs that can promote adipocyte browning belong to the Pungent-Warm Exterior-Releasing medicinal family, according to the theory of TCM. The leaf of Perilla frutescens (L.) Britt (PF) is also a member of the Pungent-Warm Exterior-Releasing medicinal family. Thomas et al. [ 9] found that Purple Perilla (P. frutescens var. acuta) leaf extract has anti-obesity effects in rodents and can be effective in obesity management due to its ability to reduce lipid accumulation in differentiated adipocytes and prevent an increased body weight in C57BL/6J mice fed high-fat diets. Feng et al. [ 10] found that PF extract demonstrated a negative effect on adipocyte formation from 3T3L-1 pre-adipocytes. Another study demonstrated that PF extract can inhibit body-fat formation and lower the body weight of obese mice [11]. Consequently, it could be postulated that PF may also promote adipocyte browning. PF extract comprises more than one component ingredient, indicating complicated pharmacological targets and mechanisms. So far, most existing studies on herb extracts have concentrated on single or limited ingredients and targets, lacking an integral exploration of the pharmacological mechanisms of the herb [12,13]. As a result, it poses a challenge to systemically investigate the reaction ingredients of the PF extract on vital molecules to promote browning. Since the traditional approaches are limited, a novel systemic approach, network pharmacology, which was established based on the theory of Shao Li published in 2013, was employed in the present study [14]. Network pharmacology, as a in silico technique, focuses on the synergy of multicomponent and multitarget systems, which is very suitable for plant extract study. It has emerged as a useful tool for understanding the fine details of drug–target interactions [15]. Network-based topological analysis tools, particularly dynamic analysis tools, have great potential for finding and developing multitarget drugs and identifying alternative targets [16]. Molecular docking is a computational simulation to explore ligand conformations adopted within receptor binding sites during intermolecular recognition [17]. Recently, it has also drawn great attention in the field of plant research [18,19]. Singh et al. [ 20] used molecular docking, long-term molecular dynamics, and molecular-mechanics Poisson–Boltzmann surface-area analysis to find out the potential of quinoline-based molecules as allosteric inhibitors. In the present study, network pharmacology methods were used in combination with molecular docking to reveal the potential molecular mechanisms of PF promoting adipocyte browning, and results were validated by experimental evidence. The overall workflow is shown in Figure 1. ## 2.1. Leaf of Perilla frutescens (L.) Britt (PF) Bioactive Ingredient Acquisition The ingredients in PF were obtained through the symMap database, the Traditional Chinese Medicines Integrated Database (TCMID), and the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) [17]. The chemicals with oral bioavailability ≥$30\%$ and with violations of no more than two items in the five criteria of drug-likeness were screened out as competent pharmacological compounds for further study. The drug-likeness information of each ingredient can be retrieved from the SwissADME database (http://www. swissadme.ch, accessed on10 August 2022) [21]. ## 2.2. Prediction of Protein-Encoding Target Genes Based on Compound Structures Swiss-Target-Prediction [22], a website database tool, was used for target-protein prediction. The SMILE formula of each compound was retrieved from the PubChem database and then input into the online tool for drug-target prediction. Targets with a prediction probability of less than 0.1 were excluded. ## 2.3. Search for Browning-Related Targets Adipocyte browning-related genes were found in the GeneCards database; “adipocyte browning” and “adipose browning” were used as search keywords. Protein-encoding genes with a disease relevance score ≥3 were chosen for further investigation. ## 2.4. Topological Analysis for the Interactions among Overlapped Target Genes The overlapped genes of both PF-related genes and browning-associated targets were filtered by a Venn diagram. Based on the aforementioned overlapped genes, a topological interaction network was created after inputting the list of genes into the String database, intending to screen out the hub genes. For the topological network establishment, the interaction score was set as 0.4. Further topological analysis was performed using the MCODE plugin of Cytoscape, which was used to screen out the core clusters from the entire network. ## 2.5. Enrichment Analysis Based on GO and KEGG Database The potential pathways and biological functions of the overlapped genes were predicted using enrichment analysis. The R package “cluster profile” was used to execute the analysis. The enriched items with an adjusted p-value < 0.01 were set as the cutoff values. ## 2.6. Exploration of the Interactions among Ingredients, Targets, and Pathways To further elucidate the correspondence between the active ingredient and overlapped target proteins, the ingredient–target network was constructed. Furthermore, to study the connection between protein targets and the 15 top pathways, the targets–pathway correspondence was also added, and the ingredient–target–pathway (I-T-P) network was established. To characterize the role of active ingredients in the network, three topological parameters were measured, namely degree, betweenness, and closeness [16]. ## 2.7. Molecular Docking Simulation The top seven active ingredients filtered from the I-T-P network and the top seven targets screened based on the PPI network were paired for a molecular docking simulation, which was conducted using the AutoDock software package [23]. For the preprocessing stage, the 2D structures of ingredients were acquired from the PubChem database, which were then transformed into 3D structures as well as optimized with minimal energy using Chem3D software and converted to the pdbqt format. The protein crystal structure was obtained for the PDB protein bank. The 3D structures of AKT1 (PDB id: 1UNP), CASP3 (PDB id: 1NME), EGFR (PDB id: 1M14), MAPK14 (PDB id: 1A9U), PPARG (PDB id: 1I7I), SRC (PDB id:1O41), STAT3 (PDB id: 6NJS), and VEGFA (PDB id: 1MJV) were then imported and preprocessed in the PyMOL software for dehydrated, hydrogenated, and pdbqt format conversion. The final calculations of the docking and binding energies were conducted using AutoDock Vina 4.2. The docking results were visualized in the Pymol software. The estimated binding affinity score ΔG (kcal/mol) was calculated to characterize the compound- and protein-binding force [24]. A lower binding-affinity score indicated a better binding affinity [25]. The results were visualized by Discovery Studio 2012 and visualized using a heatmap plot. ## 2.8. Molecule Dynamics of Ligand and Target Combination The binding of docked ligand–receptor complex systems was further validated by molecular dynamics simulations using the AMBER 18 software [26]. For the preprocessing stage, Gaussian 09 software [27] was employed to set the charges of the ligand. The GAFF2 small-molecule force field and the ff14SB protein force field [28] were assigned to ligand and protein receptors, respectively. The LEaP module was used to add hydrogen atoms to the system, a truncated octahedral TIP3P solvent box was added at a distance of 10 Å from the system, Na+/Cl− was added to the system to balance the system charge, and finally, the topology and parameter files for the simulation were output. The system first underwent energy optimization and was then heated to 298.15 K. A 500 ps NVT (isothermal) phylogenetic simulation was then conducted and an equilibrium simulation of 500 ps was performed. At the final stage, 100 ns NPT (isothermal isobaric) phylogenetic simulations were performed. The geometrical parameters of the systems, such as the root mean square deviation (RMSD) and root mean square fluctuation (RMSF), were determined and compared with the primitive ligand complex system. ## 2.9. Preparation of PF Extract The Perilla frutescens (L.) Britt leaves were purchased in the local market, and then dried and crushed into powder. Dried PF powder was dissolved in $70\%$ ethanol in a 1:30 (g/mL) ratio [29,30]. The solution was kept in a water bath at 60 °C for 1 h and then centrifuged at 3000 r/min for 10 min. The supernatant was filtrated, and the recovered ethanol fraction was concentrated. The extraction procedure was repeated three times, combining the three extracts. The mixed ethanol supernatant of all extracts was then filtered, concentrated, freeze-dried into a powder, and stored at 4 °C for later use [29,31]. ## 2.10. Cell Culture and Differentiation Primary mouse-bone-marrow mesenchymal stem cells (BMSCs) [32] were cultured in Dulbecco’s modified Eagle’s medium (DMEM; Shenggong, Shanghai, China) supplemented with $10\%$ bovine calf serum and $1\%$ penicillin–streptomycin (Biyuntian, Wuhan, China). When the cell density reached $80\%$ confluence, cells were seeded. Two days after confluence, the cells were cultured with an adipogenic differentiation medium containing 0.5 mM isobutylmethylxanthine, 1 μM dexamethasone, 10 μM rosiglitazone, and 10 μg/mL insulin (ADP1, Guangzhou Bojin Biotechnology Co., Ltd., Guangzhou, China) supplemented with $10\%$ fetal bovine serum and $1\%$ penicillin–streptomycin (Biyuntian, Wuhan, China) to induce adipocyte differentiation. The time point was set as Day 0. After 2 days, the ADP1 medium was changed to a maintenance medium (ADP2, Guangzhou Bojin Biotechnology Co., Ltd.), including 10 μg/mL insulin only, until Day 10. PF was added to the BMSCs starting from Day 0 and the medium changed every three days. For the inhibitor test, BMSCs were pretreated with AKT inhibitor SC394003 (10 μM, Santa Cruz, CA, USA) and p38 inhibitor (SB203580) (10 μM, Sigma-Aldrich, Munich, Germany) for 24 h and then simulated with the same fresh medium for 30 min before sample collection. ## 2.11. Cell Viability Assay The Cell Counting Kit-8 (CCK8, Dojindo, Kumamoto, Japan) assay was employed to determine cell viability. BMSCs were seeded and incubated with PF (0, 50, 100, 200, 400, 800, and 1600 μg/mL). After 10 days of induction, the cells were washed with PBS, and $10\%$ CCK-8 solution diluted with alpha-MEM medium was added to each well; then, they were incubated for an hour, and the absorbance at 450 nm was measured by a microplate reader (Thermo, Waltham, MA, USA). ## 2.12. Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) Real-time quantitative polymerase chain reaction (RT-qPCR) [33] was used to characterize adipogenesis-related gene expression. The total RNA of the BMSCs was extracted using TRIzol reagent and then reversely transcribed to complementary DNA (cDNA). RT-qPCR was carried out with SYBR Green Master Mix, following the manufacturer’s instructions, using an ABI PRISM 7500 PCR Sequence Detection System (Applied Biosystems, Foster City, CA, USA), and the melting curve was tested simultaneously. The primers are listed in Supplemental Table S1. ## 2.13. Western Blot Analysis Cells were lysed to obtain the total protein content using freshly prepared radioimmunoprecipitation assay buffer (RIPA) at 4 °C [33]. Protein was then normalized and separated by $10\%$ sodium dodecyl sulfate-polyacrylamide gel (SDS PAGE) and transferred to a PVDF membrane (Millipore, Burlington, MA, USA). The membrane was subsequently blocked and incubated with a diluted primary antibody. Finally, it was incubated with a secondary antibody for visualization using an electrochemiluminescence detection reagent (SAB, College Park, MD, USA). The grayscale bands were analyzed by ImageJ (National Institutes of Health, Bethesda, MD, USA) software. Actin was used as an internal control. Actin, PI3K, P-PI3K, AKT, P-AKT, STAT3, P-STAT3, and PPARG antibodies with a dilution ratio of 1:3000 were purchased from Servicebio (Wuhan, China). UCP1, CREB, and P-P38 antibodies with a dilution ratio of 1:1000 were purchased from Servicebio Co. (Wuhan, China). P38 and P-CREB antibodies with a dilution ratio of 1:1000 were purchased from Abcam (Cambridge, UK) ## 2.14. Determination of Lipid Accumulation The Oil Red O (ORO) staining method [34] was employed to characterize the intracellular lipid accumulation, according to the manufacturer’s instructions. After incubation for 30 min, the stained lipid droplets were viewed under a microscope. The lipid accumulation was quantified by solving in isopropanol, and then the absorbance at 520 nm was checked. ## 2.15. Mitochondrial Mass Measurement The BMSCs that were treated with PF or left untreated for 10 days were washed with PBS and incubated with DMEM containing 100 nM MitoTracker Green FM (Beyotime Biotechnology, Jiangsu, China) for 30 min at 37 °C [35]. Cells were washed with PBS and then incubated in a prewarmed DMEM medium at 37 °C. Fluorescent intensity at 490 nm was observed using an Olympus confocal microscope (FV10-MCPSU). ## 2.16. Statistical Analysis Statistical analysis was conducted using Prism 8 software. Data were expressed as the mean ± SD and analyzed using one-way ANOVA. Differences between groups were considered to be statistically significant if values of $p \leq 0.05.$ ## 3.1. Putative Targets of PF Activating Browning There were 396 compounds in PF obtained from those the aforementioned databases. After screening by oral bioavailability and drug-likeness criteria, 49 compounds were found. A total of 19 compounds were excluded, as no target could be predicted with a prediction probability of more than 0.1. Overall, 427 PF-predicted genes were finally generated from 30 compounds, and 1493 browning-related genes were found using the GeneCards database, based on which 342 genes were selected with a relevance score of more than 3. Eventually, 56 overlapped genes predicted by 17 compounds from both the PF-predicted genes and browning-related genes were selected using Venn diagrams, as shown in Figure 2A. ## 3.2. Enrichment Analysis The enrichment analysis was performed based on the 56 overlapped targets to predict the potential mechanisms of PF promoting adipocyte browning. Overall, 1735 biological process (BPs), 27 (cell components) CCs, and 82 molecular functions (MFs) were enriched in the GO analysis. The biological process enrichment conducted by the Glue GO plugin is shown in Figure 2B, and the top 10 terms in each subitem are illustrated in Figure 2C. It was predicted that PF activating adipocyte browning might occur through the intracellular receptor-signaling pathway, activation of protein kinase activity, response to peptide hormone, and regulation of the lipid metabolic process. In the meantime, target proteins were located in the membrane raft, membrane microdomain, cell-leading edge, vesicle lumen, and early endosome. The reactome pathway analysis indicated that the MAPK signaling pathway, nuclear-receptors metapathway, and IL-18 signaling pathway may be related to the PF-activated browning mechanism, as shown in Figure 3A. The KEGG pathway analysis screened out 155 pathways with statistical significance, including the PI3K-Akt signaling pathway, MAPK signaling pathway, AGE-RAGE signaling pathway in diabetic complications, estrogen signaling pathway, and lipid and atherosclerosis. The top 15 KEGG pathways with the highest gene ratio were selected for visualization, as shown in Figure 3B. ## 3.3. Protein–Protein Interaction (PPI) Network of Targets for ZYS Promoting Adipocyte Browning PPI analysis, as plotted in Figure 4A, was conducted on 56 common genes. The top 30 proteins with the most adjacent nodes are plotted in Figure 4B. These proteins may play a significant part in activating adipocyte browning. The core cluster genes were filtered by the MCODE plugin, as shown in Figure 4C–E. It also seems that the function of cluster 1 plays a major role in promoting adipocyte browning, as it includes most of the genes. ## 3.4. Ingredient–Target–Pathway (I-T-P) Network Construction The I-T-P network was established to illustrate the ingredients and their correspondence to the receptors and pathway involved, including 88 nodes and 312 edges, as shown in Figure 5. The top five compounds with the highest edge numbers were luteolin (C8), nerolidyl acetate (C11), 1-(2,4,5-triethoxyphenyl) propane-2-amine (C1), isoeugenol (C7), and dibutyl phthalate (C4). The mean topological parameters of the top five compounds were 12 degrees, 0.0728 of node betweenness, and 0.3506 of closeness. The top five target nodes with the most connections were AR, ESR1, PTGS2, PTPN1, and SRC. The mean value of topological parameters was 8 degrees, 0.0398 of node betweenness, and 0.3442 of closeness, respectively. The 17 compounds of PF are listed in Table 1. ## 3.5. Molecular Docking Demonstrating Compound–Protein Interaction To further elucidate the combination of compound and predicted proteins, a molecular docking simulation was performed. As the lowest binding energy indicated the most stable binding modality, the binding pattern with the lowest binding energy was simulated. Based on the PPI and enrichment results, eight key browning-related targets (AKT1, CASP3, EGFR, MAPK14, PPARG, SRC, STAT3, and VEGFA) and seven compounds with top-degree values in the I-T-P network were paired for molecular docking. The binding energy results are summarized in the heat map shown in Figure 6. It is generally accepted that a binding energy less than −4.25 kcal/mol indicates specific binding activity of the ligand to the receptor, while a binding energy less than −5.0 kcal/mol indicates better binding activity [36]. According to the affinity score, MAPK14 can bind with C1 and C4; the binding mode included van der Waals, pi-alkyl, alkyl, pi-sigma, and conventional hydrogen bonds. AKT1 can also bind with C11; the binding mode included pi-alkyl, alkyl, and pi-sigma. The binding patterns and the connected amino acid residues are plotted in Figure 7. ## 3.6. Molecular Dynamics Simulation of Ligand Complex According to the I-T-P network, AKT1/C11, MAPK14/C1, and MAPK14/C4 are the possible ligand–receptor complexes for combining AKT1 and MAPK14. The molecular binding was also simulated through molecular dynamics simulation. As shown in Figure 8A1–C1, all systems of the protein reach convergence, indicating that the simulation finally stabilizes. For AKT1/C11, the protein–ligand complex part converged at 40 ns and was very stable in the subsequent simulations. The RMSD of the C11 simulation was within 2 Å throughout, with only weak fluctuations occurring around 67 ns. For MAPK14/C1, the RMSD of the protein–ligand complex was found to converge at 15 ns and fluctuate around 3 Å in the later part of the simulation, while the RMSD of the C1 remained stable throughout the simulation, with an RMSD within 1 Å. In the case of MAPK14/C4, the RMSD of the complex system was larger and less stable than MAPK14/C1. Nevertheless, the RMSD of the small molecule fluctuated within 2 Å, indicating that the small molecule can still bind stably in the active site. The RMSF characterizes the rigidity of the ligand–receptor complex. Higher rigidity indicates more stable binding and superior enzymatic activity. As shown in Figure 8A2–C2, the RMSF of the whole protein was consistently found to be within 2 Å in the three systems, indicating the high rigidity of protein achieved by ligand binding. The RMSF of MAPK14 was lower when combined with C4 compared with C1, indicating that C4 improved MAPK14 rigidity. Hydrogen bonding is one of the strongest noncovalent interactions; the higher the number of hydrogen bonds, the more favorable the binding of small molecules and proteins. The number of hydrogen bonds formed between ligands and proteins during the simulation was ranked as MAPK14/C1>AKT1/C11>MAPK14/C4. MAPK14/C1 formed the largest number of hydrogen bonds, which may be the reason that MAPK14/C1 had the strongest stability of the abovementioned complexes, as shown in Figure 9. ## 3.7. Effect of PF on Bone Marrow Mesenchymal Stem Cell (BMSC) Viability BMSCs were co-cultured with PF at different concentrations, as shown in Figure 10A. The CCK8 kit was used to test cell viability after eight days of intervention. It revealed that PF with a concentration of no more than 400 μg/mL demonstrated no significant cytotoxicity against the viability of BMSCs. ## 3.8. PF Inhibited Lipid Accumulation and Downregulated Adipogenesis-Related Gene Expression ORO staining revealed a notable dose-dependent decrease in lipid accumulation, which indicated the inhibition of adipogenesis in PF-treated adipocytes, as shown in Figure 10B,C. BMSCs treated with 200 μg/mL PF showed the downregulated expression of white adipocyte-specific genes Zfp423 and leptin, as well as the pan-adipogenesis genes fabp4 and pparg, as shown in Figure 10D. ## 3.9. PF Promoted Mitochondrial Biogenesis and Upregulated Brite Adipocyte-Related Gene Expression Mito-tracker staining showed increased mitochondrial activity when treated with 200 μg/mL PF, as shown in Figure 11A,B. The RT-qPCR also showed that PF intervention could promote the expression of the brite adipocyte-related genes PGC-1α, PRDM16, and Cox7a1. The results of the Western blot, as well as RT-qPCR, showed the elevated expression of the browning-specific marker UCP1, as illustrated in Figure 11C,D. ## 3.10. Effect of PF on Browning Could Be Mediated by the p38 MAPK Pathway as Well as PI3K-AKT Pathway The expression of core genes screened was validated by Western blot, as shown in Figure 12 and Figure 13. It seems that PF intervention did not change the expression level of p38 MPAK (MAPK14), AKT1, and STAT3, but enhanced their phosphorylation level. As for PPARG, the expression was downregulated. The network pharmacology prediction showed that the p38 MAPK and PI3K-AKT pathways could be the potential pathways involved in adipocyte browning. As a result, the expression of p38 MAPK and its phosphorylation was examined, and an increased expression was observed after treatment with PF. The phosphorylation of downstream transcription factor CREB was also found to have an increased expression, as shown in Figure 12. Similarly, the expression of PI3K and AKT1, as well as their phosphorylation, were also examined. It also showed an increased phosphorylation level after the intervention of PF. To further confirm the role of the p38 MAPK and PI3K-AKT pathway in adipocyte browning, the expression of browning-specific marker UCP1 and the phosphorylation of p38 were examined after intervention with p38 MAPK inhibitor SB203580. As shown in Figure 14, the increased expression of UCP1, as well as p-P38, was downregulated after the addition of the inhibitor. Similarly, the UCP1 expression and the phosphorylation of AKT1 was examined after being treated with AKT inhibitor SC394003, which inhibited the increased expression of UCP1 as well p-AKT1, as shown in Figure 15. In all, PF could promote browning via the p38 MAPK as well as PI3K-AKT pathway, leading to the differentiation into brite adipocytes. ## 4. Discussion Due to changes in diet and genetic factors, the number of obese people is increasing year by year [37]. When energy intake exceeds energy depletion for a long time, excess nutrients are converted into triglycerides and stored in fat cells. This process is accompanied by the proliferation and differentiation of adipose stem cells and the increase in lipid storage, which leads to the proliferation of adipose tissue. Obesity increases the risk of cardiovascular and cerebrovascular diseases, diabetes, cancer, and other noninfectious diseases, seriously endangering human health [38]. Currently, obesity is mainly treated with surgery or drugs to reduce the body’s energy intake. Orlistat is an intestinal fat inhibitor, which can achieve weight loss by reducing the absorption of fat in food, but resulting in a deficiency of fat-soluble vitamins in the long term [39]. Liraglutide is an analog of glucagon-like peptide-1, which increases the risk of hypoglycemia and acute pancreatitis [40]. Qsymia is a type of weight-loss drug aimed at the central nervous system, accompanied by side effects such as headache, sleep loss, constipation, and vertigo [41]. So far, the most-adopted therapeutic strategy is to treat obesity by reducing energy intake. However, it also produces many side effects related to it. As a consequence, increasing energy consumption could become a promising strategy for treating obesity. White adipocytes can be transformed into brown-like adipocytes. This process is called “Browning” [42]. Currently, it is considered that the browning of white adipocytes is an effective measure against obesity [43]. PF (the dry leaf of the Labiatae plant P. frutescens) has various effects, such as regulating glucose and lipid metabolism, antioxidation, antidepression, and relieving cough and asthma [44,45,46]. Studies have reported that the total flavonoid extract of Perilla leaves can regulate glucose and lipid metabolism disorders in diabetic model mice and has a good antidiabetic effect [47]. In this study, the browning effect promoted by PF was analyzed via the combination of network pharmacology and in vitro validation to explore a new therapeutical approach against obesity. The GO enrichment analysis demonstrated that the top enriched biological processes were the intracellular receptor-signaling pathway, activation of protein kinase activity, response to peptide hormone, regulation of lipid metabolic process, and peptidyl-serine phosphorylation, which are responsible for signal transduction. The CC enrichment showed that these proteins were mainly located on the membrane raft, membrane microdomain, vesicle lumen, transferase complex, and transcription regulator complex, indicating that they are mostly located within the cells. The main functions of these potential target genes are related to nuclear receptor activity, ligand-activated transcription factor activity, protein serine/threonine kinase activity, DNA-binding transcription-factor binding, and phosphatase binding, which are mostly related to the signal-transduction cascade. In all, the GO enrichment results indicate that the target genes enriched are mostly responsible for intracellular signal transduction within the cell. A total of 56 target genes of PF were overlapped and selected as potential targets for the promotion of adipocyte browning. Core targets were screened out by PPI network analysis and the MCODE plugin. It was interesting to note that AKT- and MAPK-related targets (AKT1, AKT2, MAPK14) were shown in cluster 1, indicating that they may play an important role in the PPI network. MAPK14 belongs to the p38 MAPK family, whose function is to initiate signal-transduction cascades that can finally activate transcription factors when cells are simulated by external stimulation, such as stress or proinflammatory cytokines [48]. The KEGG pathway analysis indicated that lipid and atherosclerosis, the PI3K-Akt signaling pathway, the estrogen signaling pathway, and the p38 MAPK signaling pathway might be involved in the browning process, stimulated by PF. P38 MAPKs initiate downstream signal transduction via phosphorylation. It has been reported that there are more than 200 substrates, including some kinases, leading to phosphorylation cascades, such as CREB1, ATF1, STAT1, and STAT3 [49]. The p38 MAPK pathway has been widely studied. Lee et al. reported that adapalene, an anti-acne agent with retinoic acid receptor agonism, induces adipose browning through the RARβ-p38 MAPK-ATF2 pathway [50]. Mukherjee et al. found that the addition of prednisone to 3T3-L1 pre-adipocytes can promote browning, characterized by the upregulation of browning-specific genes, such as UCP1, PGC-1α, and PRDM16 [51]. The activation is mediated by the p38 MAPK pathway, activating the transcriptional factor ATF2. Wu et al. found a mesencephalic astrocyte-derived neurotrophic factor (Manf), which is a feeding-induced hepatokine that can ameliorate diet-induced obesity by promoting adipose browning via the p38 MAPK pathway [52]. Several studies have also shown that the PI3K-Akt signaling pathway can play a part during the browning process. Zhao et al. showed that Vitamin D3 could inactivate the PI3K/Akt/mTOR/p53 signaling pathway and inhibit the expression of browning-specific markers but could promote autophagy [53]. Another study showed that the downregulation of osteopontin demonstrated a negative effect on the browning of WAT and downregulated the expression of PPARγ via the PI3K-AKT pathway [54]. Molecular docking and molecular dynamic simulation confirmed the stability of ligand binding with MAPK14 and AKT1. The in vitro experiments were conducted to validate the browning effect of PF based on the BMSCs. The browning process is accompanied by an increase in browning markers, including uncoupling protein-1 (UCP-1), pparγ-assisted activator 1α (PGC-1α), and positive regulatory domain containing 16 (PRDM16) [55]. The results of the Western blot, as well as RT-qPCR, showed the elevated expression of the browning-specific marker UCP1, the typical brite adipocyte-specific marker. Mito-tracker staining showed increased mitochondrial activity when treated with 200 μg/mL PF, and RT-qPCR showed that PF intervention could promote the expression of thermogenic genes PGC-1α, PRDM16, and Cox7a1. The phosphorylation of p38 MAPK, as well as AKT1, was examined, and an increased expression was both observed after treatment with PF. The role of the p38 MAPK pathway as well as the PI3K-AKT pathway in adipocyte browning was further confirmed by the p38 MAPK inhibitor SB203580 and AKT inhibitor SC394003. In all, the in vitro validation confirmed that PF could promote adipocyte browning via the p38 MAPK as well as the PI3K-ATK pathway, leading to the differentiation of brite adipocytes. As for the limitation of the present study, only a small part of the mechanisms or pathways by which PF promotes adipocyte browning were analyzed and discussed. More browning- or adipogenesis-related genes can be examined by RT-qPCR to explore more possible mechanisms. Further studies are needed to validate the potential role of more pathways, such as estrogen signal pathways. ## 5. Conclusions In conclusion, the study revealed the therapeutic function of PF and possible mechanisms involved in the promotion of adipocyte browning. 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--- title: 'Assessment of Low-Level Air Pollution and Cardiovascular Incidence in Gdansk, Poland: Time-Series Cross-Sectional Analysis' authors: - Radosław Czernych - Artur Jerzy Badyda - Grzegorz Kozera - Paweł Zagożdżon journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054494 doi: 10.3390/jcm12062206 license: CC BY 4.0 --- # Assessment of Low-Level Air Pollution and Cardiovascular Incidence in Gdansk, Poland: Time-Series Cross-Sectional Analysis ## Abstract [1] Background: More than 1.8 million people in the European Union die every year as a result of CVD, accounting for $36\%$ of all deaths with a large proportion being premature (before the age of 65). There are more than 300 different risk factors of CVD, known and air pollution is one of them. The aim of this study was to investigate whether daily cardiovascular mortality was associated with air pollutants and meteorological conditions in an urban environment with a low level of air pollution. [ 2] Methods: Data on daily incidence of strokes and myocardial infarctions in the city of Gdansk were obtained from the National Health Fund (NHF) and covered the period from 1 January 2014 to 31 December 2018. Data on the level of pollution, i.e., SO2, NO, NO2, NOx, CO, PM10, PM2.5, CO2, O3 and meteorological conditions came from the foundation: Agency of Regional Air Quality Monitoring in the Gdańsk metropolitan area (ARMAG). Using these data, we calculated mean values with standard deviation (SD) and derived the minimum and maximum values and interquartile range (IQR). Time series regression with Poisson distribution was used in statistical analysis. [ 4] Results: Stroke incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.019 ($95\%$CI: 1.001–1.036), 1.036 ($95\%$CI: 1.008–1.064) and 1.017 ($95\%$CI: 1.000–1.034) for every increase in IQR by 14.12, 14.62 and 22.62 μg/m3, respectively. Similarly, myocardial infarction incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.030 ($95\%$CI: 1.011–1.048), 1.053 ($95\%$CI: 1.024–1.082) and 1.027 ($95\%$CI: 1.010–1.045) for every increase in IQR by 14.12, 14.62 and 22.62 μg/m3, respectively. Both PM10 and PM2.5 were positively associated with myocardial infarction incidence. [ 5] Conclusions: *In this* time-series cross-sectional study, we found strong evidence that support the hypothesis that transient elevations in ambient PM2.5, PM10, NO2, SO2 and CO are associated with higher relative risk of ischemic stroke and myocardial infarction incidents. ## 1. Introduction Myocardial infarction and ischemic stroke are mainly a complication of atherosclerotic lesions in the respective vessels (coronary or cerebral) and therefore have the same etiology and are both clinically defined as cardiovascular diseases (CVD) [1]. The burden of CVD is greater than that of any other disease and is the leading cause of death in Europe and in the world. More than 1.8 million people in the European Union die every year as a result of CVD, accounting for $36\%$ of all deaths with a large proportion being premature (before the age of 65) [2]. According to WHO data, in 2003, premature cardiovascular mortality in Polish people aged 25–64 was 2.5 times higher than in other European Union countries. In 2014, cardiovascular diseases accounted for as much as $45.1\%$ of all deaths in Poles, including $40.3\%$ among men and $50.3\%$ among women [3]. Myocardial infarction incidence differs depending on age and sex. In total, 121 men and 25 women per 100,000 between 40 and 44 years suffer from myocardial infarction. For older age groups, this value is multiplied and equals: $\frac{1012}{416}$ (men/women aged 65–69) and $\frac{1718}{1075}$ (men/women aged 80–84 years). Myocardial infarction hospital mortality in 2012 in Poland in patients aged 35–49 years was $2.5\%$; 60–64 years, $5\%$; 80–84 years, $15\%$; and over 85 years, exceeded $20\%$ [4]. According to Global Burden of Disease data, the incidence rate in Poland for the first-in-life ischemic stroke in 2010 was $\frac{173.2}{100}$,000, while two decades earlier, it was $\frac{186.6}{100}$,000 [5]. According to the data of the National Health Fund, the number of all hospitalizations due to the treatment of stroke in Poland in 2009 was almost 95,000 and has decreased to over 88,000 since [6]. Although more than 300 different risk factors of these diseases are known, and incidence is gradually decreasing, both myocardial infarction and stroke remain a leading cause of disease disability and death in the Western world [7,8,9]. Aside from the most recognizable non-modifiable risk factors of CVD, there are factors defined as structural determinants, for example: living and working conditions. Both are often related with air pollution. Air is a complex mixture of gases and aerosols. Its composition is usually affected by the degree of industrialization and urbanization in a given area [10]. Emissions of polluting agents such as sulfur dioxide (SO2), nitrogen dioxide (NO2), nitrogen oxide (NO), carbon monoxide (CO), particulate matter with a diameter of 10 μm or less (PM10) and of 2.5 μm or less (PM2.5) as well as benzo[a]pyrene can be mostly related with inefficient modes of transport (polluting fuels and vehicles), inefficient combustion of household fuels for cooking, lighting and heating, coal-fired power plants, agriculture, and waste burning [11]. The intensity of industrialization and urbanization affects not only the natural environment but also has a number of possible human health effects. The Great Smog of London took place in the early years of the second half of the 20th century and caused hundreds of thousands of hospitalizations followed by nearly 12,000 deaths [12]. After the incident, governments across the world began to understand that unsustainable development and lack of economic and ecological resource management can do more harm than good. Since that time, scientists, often supported by policy makers, began to investigate possible effects of a polluted environment on human health. Currently, air pollution is recognized as one of the risk factors, that on a massive scale, can cause: inflammation of the upper and lower respiratory track, lung cancers, cardiovascular diseases and preterm death [11]. Most of the studies investigating the effect of short-term exposure of air pollutants on the population concentrate on urban areas with high levels of air pollution, whereas there is a scarce amount of studies of the health effect of low-level pollution [13,14,15,16]. Because of its geographical location and characteristic climate condition, Pomorskie Voivodship, along with its capital city (Gdansk), is considered to have one of the cleanest atmospheric environments in the whole of Poland. The aim of this study was to investigate whether daily cardiovascular mortality was associated with air pollutants such as: SO2, NO2, NO, NOx CO, O3, CO2 as well as PM10, PM2.5 and meteorological condition in an urban environment with low levels of air pollution. Separate analyses were carried out with respect to sex and age. ## 2.1. Study Area and Its Climate Gdansk is a city localized on the southern coast of the Baltic Sea region (northern Poland). With a population of over 470,000 citizens and an area of 262 km2, it is the capital and largest city in Pomorskie Voivodship. In a conurbation with the city of Gdynia, the resort town of Sopot, and suburban communities, these form the metropolitan area called the Tri-City, with a population of approximately 1.5 million and an area of 414 km2. It is Poland’s principal seaport and the country’s fourth-largest metropolitan area [17]. Because of its characteristic geographic location, the Gdansk climate seems to have both oceanic and continental influences. According to different categorization systems, Gdansk either has an oceanic climate or belongs to the continental climate zone. The continental characteristic of Gdansk’s climate can be explained by dry winters and precipitation maximum during summer. Nonetheless, seasonal extremes are less pronounced than those in the inland parts of Poland. The average temperatures range from −1.0 to 17.2 °C, whereas average monthly precipitation varies from 17.9 up to 66.7 mm per month with an annual total of 507 mm [18]. The vicinity of the Baltic Sea, geomorphological diversity and location within the influence of large baric centers have a major impact on the speed and direction of winds in the Pomeranian Voivodeship. In the coastal zone of the voivodship, the dominant winds are west winds, while inland and in Żuławy, they are the southeast winds. In 2018, the majority of winds in the Pomeranian Voivodeship were southern winds, the average annual speed ranging from 3.1 to 5.1 m/s. Higher wind speeds occurred in the coastal strip of the Voivodship, while the most common silence was in the Tri-City area. In the Tri-City agglomeration, winds predominated, with the average annual speed ranging from 3.1 to 5.1 m/s. Higher wind speeds were most common on Sobieszewo Island in the coastal belt of Gdynia [18]. The main source of air pollution in the Pomeranian *Voivodeship is* anthropogenic emission. It is associated with point sources from industrial plants, mainly from fuel combustion processes for energy purposes and technological processes ($23\%$), with a linear source related to road, rail, water and air transport ($15\%$), as well as in the area, related to the municipal and housing sector ($49\%$). In the case of point sources in the Tri-City agglomeration, the main pollutants are sulfur oxides SOx emitted by power plants and combined heat and power plants and, to a lesser extent, by production processes. On the other hand, in the Pomeranian zone, the highest share of sulfur oxides comes from households, i.e., from the municipal and living sector. The main pollutants emitted from road transport in the Pomeranian zone in 2018 were nitrogen oxides (NOx). In the case of the Tri-City agglomeration, the highest share in the emission of nitrogen oxides was point emission, mostly from heat and power plants in Gdańsk and Gdynia. Compact, low-rise buildings and the related heating processes in the municipal-living sector (surface emission) cause high concentrations of mainly suspended dust (PM10). Apart from households, the sources of such high emissions were also: agriculture, livestock farming, heaps, excavations, land and forests [19]. ## 2.2. Incidence Data Data on daily incidence of strokes and myocardial infarctions in the city of Gdansk were obtained from the National Health Fund (NHF) and covered the period from 1 January 2014 to 31 December 2018 (Table 1). The database contains information on the date of patient admission to the hospital unit and his/her discharge (or possible death), the poviat from which the patient came and the poviat of the hospital ward, sex and date of birth of the patient and the code of the diagnosed disease entity (ICD-10). In total, the database contains 73,413 cases of strokes and myocardial infarctions (ICD-10: I63, I61-62, respectively). Since the study focused on the area of the Gdansk municipality, cases of patients living in Gdańsk and admitted to the hospital unit in this area were selected from the NHF database. Finally, the numbers of strokes and infarctions each day were determined (total and broken down by gender and age groups), and the study period of daily incidence data was matched with the available period of daily environmental data for statistical analysis. ## 2.3. Environmental Data Data on the level of pollution came from six monitoring stations located in Gdańsk and described the concentrations of the following chemical compounds: SO2, NO, NO2, NOx, CO, PM10, PM2.5, CO2, O3 and values of temperature, humidity, atmospheric pressure, rainfall and wind strength. The monitoring stations are owned and maintained by the foundation: Agency of Regional Air Quality Monitoring in the Gdańsk metropolitan area (ARMAG). Data collected were based on measurements carried out with 1 h intervals over the studied period (years: 2014–2018, for PM2.5 from 2015 to 2018). Apart from the missing measurement periods for PM2.5, there were also, unidentified as to the cause, missing values. The number of missing values is presented in Table 2. In order to obtain a single concentration level for an individual compound for one day for the entire city of Gdańsk, the measurements from all stations were averaged, and then the third quartile ($75\%$) was selected as a measurement representative for each day. All further analyses are based on daily observations conducted for the studied 5-year period (total count of observations: 1825). ## 2.4. Statistical Methods Descriptive statistical analyses of mortality data and environmental data are summarized into mean, standard deviation, and maximum, minimum, and interquartile range (IQR) in Table 1. In the case of strokes and infarctions, instead of the number of missing observations, we give the total number of occurrences and the median. **Table 1** | Unnamed: 0 | Total Count (% of All) | Daily | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | | --- | --- | --- | --- | --- | --- | | | Total Count (% of All) | Mean (SD) | Min. | Max. | IQR | | Strokes (ICD-10: I63) | 7619 | 3.48 (1.99) | 0 | 13 | 3 | | Women | 4047 (53%) | 1.85 (1.45) | 0 | 9 | 2 | | Men | 3572 (47%) | 1.63 (1.35) | 0 | 8 | 1 | | After 65 years | 5520 (72%) | 2.52 (1.68) | 0 | 11 | 3 | | Before 65 years | 2099 (28%) | 0.96 (1.03) | 0 | 6 | 2 | | Myocardial-infarctions (ICD-10: I21, I22) | 6910 | 3.15 (1.96) | 0 | 12 | 2 | | Women | 2750 (40%) | 1.26 (1.18) | 0 | 7 | 2 | | Men | 4160 (60%) | 1.90 (1.50) | 0 | 9 | 2 | | After 65 years | 4061 (59%) | 1.85 (1.44) | 0 | 9 | 2 | | Before 65 years | 2849 (41%) | 1.30 (1.27) | 0 | 8 | 2 | The Pearson correlation matrix was used to assess the relationships between the exposure factors. The essential element of the analysis presented below is the assessment of the influence of pollution and meteorological conditions on the daily number of strokes and infarctions. An appropriate statistical model to study such a phenomenon is Poisson regression. The Poisson regression model is described by the equation:log (E (Y)) = β0 + β1X1 + … + βnXn, where Y is the dependent variable, depending on the explanatory variables X1, …, Xn, E (Y) is the average daily number of strokes or infarctions (in the Poisson distribution interpreted as intensity), while X1, …, Xn are the exposure factors (chemical compounds and weather conditions). One of the basic assumptions of this model is that the resulting variable follows the Poisson distribution. Therefore, before starting the regression analysis, Chi-square tests were performed for total strokes and infarctions as well as in the groups of women and men, and people over and before the age of 65; additionally, the frequency charts were compared with the theoretical Poisson distributions. In all cases, the distributions were not significantly different from the Poisson distribution (in each case, the p value was close to 1). First, we built regression models for individual exposure factors, taking into account the so-called lag (0–3 days) for the entire population, and then simple regression models (with one variable) in the subgroups of admitted patients—women/men and people over/before 65 years of age. Finally, we presented a multiple regression model for 9 chemical compounds (SO2, NO, NO2, NOx, CO, PM10, PM2.5, CO2, O3) as well as for temperature, humidity and atmospheric pressure. On the basis of the above models, we obtained relative risk assessments related to the increase in the concentration level of pollutants with IQR and 10 degrees Celsius for temperature, $5\%$ for humidity and 5 hPa for atmospheric pressure. The air pollutants with relative risks (RRs) and $95\%$ confidence intervals for IQR change in pollution levels less than a significance level of 0.05 in the single-pollutant model were considered for our models. All calculations and graphs were made using the R statistical package (version 3.4.1). **Table 2** | Unnamed: 0 | Missing Values (Total Count for Studied Period) | Daily | Daily.1 | Daily.2 | Daily.3 | | --- | --- | --- | --- | --- | --- | | | Missing Values (Total Count for Studied Period) | Mean (SD) | Min | Max | IQR | | Chemical compounds (μg/m3) | Chemical compounds (μg/m3) | Chemical compounds (μg/m3) | Chemical compounds (μg/m3) | Chemical compounds (μg/m3) | Chemical compounds (μg/m3) | | SO2 | 0 | 6.31 (4.08) | 1.98 | 57.73 | 3.65 | | NO | 0 | 22.83 (17.57) | 4.46 | 170.94 | 14.12 | | NO2 | 0 | 23.55 (11.96) | 5.09 | 96.49 | 14.62 | | NOx | 0 | 36.47 (29.65) | 7.05 | 294.11 | 22.52 | | CO | 0 | 496.1 (203.26) | 244.3 | 2280.1 | 164.04 | | PM10 | 0 | 26.87 (16.68) | 5.66 | 151.17 | 16.76 | | PM2.5 | 393 | 20.07 (14.27) | 3.58 | 178.83 | 12.84 | | O3 | 2 | 55.53 (22.8) | 2.36 | 130 | 31.7 | | CO2 | 8 | 800.6 (60.64) | 681.9 | 1094 | 79.89 | | Meteorological data | Meteorological data | Meteorological data | Meteorological data | Meteorological data | Meteorological data | | Temperature (°C) | 0 | 10.32 (8.73) | −15.99 | 33.08 | 13.7 | | Atmospheric pressure (hPa) | 0 | 1011.4 (8.51) | 978.2 | 1039.5 | 10.95 | | Humidity (%) | 0 | 83.05 (7.14) | 46.18 | 96.84 | 9.46 | ## 3. Results Table 1 and Table 2 summarize the daily incidence and data on environmental conditions used in the models. During the period from 1 January 2014 to 31 December 2018, there were 7619 cases of strokes. On average, there were more than three incidents of stroke each day (with maximum value of 13 strokes). The majority of cases were women ($53\%$) and men ($47\%$) older than 65 years ($72\%$). During the same period, there were 6910 myocardial infarctions. The majority of cases were men ($60\%$) and people above 65 years of age ($59\%$). During the study period, daily temperatures fluctuated between −16 and 33 °C, and ambient air pollutant levels ranged from 5.1 to 96 μg/m3 for NO2, from 244 to 2280 μg/m3 for CO, and from 5.7 to 151 μg/m3 for PM10. The IQR of the environmental data, which were used for calculating RRs in the GAM, was 13.7 °C for daily temperature, 14.6 μg/m3 for NO2, 164.04 for CO, and 16.76 μg/m3 for PM10. Table 3 shows the Pearson correlation coefficients between gaseous compounds such as SO2, NO, NO2, CO, particulate matter (PM2.5, PM10) and meteorological conditions such as temperature, humidity and pressure. The gaseous pollutants along with particulate matter were highly correlated with each other. The correlation ranged from 0.62 to 0.96. Correlation between PMs and CO was strongest (rPM10 = 0.79, rPM2.5 = 0.85). Statistically comparable was the correlation of PMs and NOx ($r = 0.73$–0.76). SO2 correlated with PMs the least (rPM10 = 0.62, rPM2.5 = 0.64). However, meteorological conditions such as temperature were moderately correlated with concentrations of traffic-related pollutants. Moreover, this correlation most often seems to be inverse, i.e., SO2 and CO were strongest (r = −0.49), whereas NOX and PMs correlations ranged from −0.29 to −0.21. The associations between stroke and myocardial infarction incidence and air pollutants with respect to lagged time are presented in Figure 1 and Figure 2, respectively. By adding individual air pollutants to the single-pollutant model, it could be observed that NO, NO2 and NOx with lag 0 were significantly associated with stroke incidence. RRs for NO, NO2 and NOx are 1.025, 1.044 and 1.022, respectively. The same pollutants are significantly related with an increased incidence of myocardial infarction. RRs for NO, NO2 and NOx are 1.031, 1.052 and 1.029, respectively. Furthermore, SO2 and PM2.5 both lagged 2 days, which were significantly related with an increased incidence of myocardial infarction as well. Although the RRs for stoke and myocardial infarction were not significant for other pollutants and lags, RRs for NO, NO2, NOx, SO2 as well as for PM10 and PM2.5 were mostly greater than 1 for lags 0 and 1. Relative risks for the whole studied population with subdivision with respect to sex and age are presented in Table 4. Stroke incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.02 ($95\%$CI: 1.001–1.04), 1,04 ($95\%$CI: 1.01–1.06) and 1,02 ($95\%$CI: 1.00–1.03), respectively. Visibly, the relationship between NO2 and stroke incidence is stronger than for other nitrogen oxides. Regarding the selected subgroups, the same relationship can be observed in the cases of women and people aged 65 year and more. For women, RRs for NO and NO2 are higher than for the general population and are equal to 1.02 ($95\%$CI: 1.00–1.05) and 1.05 ($95\%$CI: 1.01–1.09). Further analysis of the selected age groups shows distinct vulnerability to nitrogen oxides in the group of elderly people (≥65 y.o.). RRs for NO and NO2 were the same with women. The elderly group, however, shows much a higher and significant susceptibility to NOx as well as to PM2.5. The effect of the latter was not statistically significant in any other subpopulation. Although it was not statistically significant, the RRs for NO, NO2, NOx as well as for PM10 and PM2.5 were, in general, higher than 1 in the whole population as well for all four subgroups. Myocardial infarction incidence is positively associated with more atmospheric air pollutants than ischemic strokes. The increase in relative risk was 1.03 ($95\%$CI: 1.01–1.05) per 10 μg/m3 increase in SO2 concentration. Weaker but significant was the association of carbon monoxide, 1.02 ($95\%$CI: 1.00–1.04). Similarly, myocardial infarction incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.03 ($95\%$CI: 1.01–1.05), 1.05 ($95\%$CI: 1.02–1.08) and 1.03 ($95\%$CI: 1.01–1.05), respectively. Both PM10 and PM2.5 were positively associated with myocardial infarction incidence, with a stronger association for PM2.5. The increase in RR was 1.03 ($95\%$CI: 1.01–1.06) per 10 μg/m3 increase in PM2.5 concentration, whereas RR for PM10 was 1.03 ($95\%$CI: 1.00–1.05). Analysis of sex and age shows that the association between myocardial infarction and nitrogen oxide increase in concentration persists in all subgroups but seems to be stronger for women (1.06 ($95\%$CI: 1.01–1.11) per 10 μg/m3 increase in NO2) and people 65 years old or older (1.07 ($95\%$CI: 1.02–1.16) per 10 μg/m3 increase in NO2). Nonetheless, statistical significance of the association of infarction and NO and NOx persisted only for men. Men seem to be more vulnerable to particulate matter as well. PM10 and PM2.5 were positively associated with myocardial infarction incidence, with a stronger association for PM10. The increase in RR was 1.04 ($95\%$CI: 1.01–1.07) per 10 μg/m3 increase in PM10 concentration, whereas RR for PM2.5 was 1.04 ($95\%$CI: 1.01–1.07). Strength of association between myocardial incidence and particulate matter for the elderly group was significant for both PM10 and PM2.5 but with a stronger effect of PM2.5 (1.04 ($95\%$CI: 1.00–1.08) per 10 μg/m3). Aside from atmospheric pollutants, meteorological factors seem to play a certain role in the incidence of stroke. A positive association between temperature and strokes is significant for the young group of the studied population (<65 y.o.) and was equal to: 1.06 ($95\%$CI: 1.01–1.11) for every 10 °C increase. Although not significant, this relationship can also be defined as strong for the group of men (1.02 ($95\%$CI: 0.98–1.06) for every 10 °C increase. Humidity, on the other hand, is positively and significantly related with myocardial infarction, with the RR equal to 1.03 ($95\%$CI: 1.01–1.04) for every $5\%$ increase in humidity. The association persisted in both sex and age subgroups. ## 4. Discussion According to our findings, the association between particulate pollutants (PM2.5 and PM10) and stroke was positive but not statistically significant. In the case of myocardial infarction, the positive association reached a level of significance. Those results were consistent with a number of studies that reported a positive association between PM2.5 or PM10 and relative risk of CVD in general or specific cardiovascular disease, i.e., stroke (ischemic/hemorrhagic), ischemic heart disease, myocardial infarction or atrial fibrillation [13,20,21,22,23]. In the study of two cohorts (the PPS cohort and the GOT-MONICA cohort), Stockfelt et al. received a positive association between both PM10 and PM2.5 for ischemic heart disease and heart failure for only one of the cohorts, whereas the results for the other cohort were insignificant [23]. Our results are in accordance with the findings of Kuźma et al., who observed a significant effect of particulate matter exposure to cardiovascular disease hospitalizations as well as to CVD deaths [24,25]. We observed a positive association between NO2, NO and NOx and stroke as well as to myocardial infarction incidence. These findings were in agreement with a meta-analysis of 94 studies of 6.2 million events, across 28 countries, which found that NO2, SO2, and CO were all linked with higher risk of total stroke hospitalizations [26]. Our findings are also in line with Chan et al., who in a study based on hospital admission of National Taiwan University Hospital (NTUH), showed that NO2 was positively associated with higher risk of stroke mortality in China [27]. Our findings are also consistent with a large body of prior studies that assessed the positive relationship between stroke subtypes and air pollution [20,22,28]. However, other studies failed to find a positive association between gaseous pollutants and ischemic stroke or myocardial infarction [16,29,30,31]. The effect of SO2 on the incidence of CVD was pronounced and statistically significant only in the case of myocardial infarction both in female and male populations and elderly people. The effect was more pronounced in the group of women. These results are in agreement with Khniebadi et al., who assessed an increased risk of $2.7\%$ of acute myocardial infarction among 540.000 citizens of Khorramabad, Iran [32]. The effect of SO2 in the risk of myocardial infarction was stronger in the study conducted by Tuan et al. in the Brazilian municipality of São José dos Campos [33]. Filho et al. observed an increase in interquartile range within a 2-day moving average of 8.0 µg/m3 of SO2 that was associated with $7.0\%$ and $20.0\%$ increases in cardiovascular disease emergency room visits by non-diabetic and diabetic groups, respectively [34]. Similar results were obtained in a study conducted in China (Hefei) [35]. In our assessment, a statistically significant effect of carbon monoxide was limited to myocardial infarction incidence, whereas stroke incidence of women and elderly people was substantially increased but still below the significance level. Most of the prior studies are in line with our assessment. Liu et al., in a time-series analysis in 272 cities in China, found significant associations between short-term exposure to ambient carbon monoxide and cardiovascular disease mortality in China [36]. An increase in percentage mortality due to CVD was also assessed in another time-series study in China [37]. In a time-stratified case-crossover analysis conducted by Son et al., the effect of CO toward CVD mortality was highest from all air pollutants assessed by the authors, i.e., PM10, NO2, SO2 and CO [38]. The same observations were also made by other authors [20,39]. According to our assessment, ozone has a negative significant association with the incidence of myocardial infarction. There was no significant relationship between ozone and stroke incidence. To the best of our knowledge, there are two possible explanations. First, there were only two monitoring stations that assessed ozone concentrations that may not cover all fluctuations of ozone atmospheric concentrations. These results can also be explained by non-linear association of ozone and CVD morbidity or mortality with a threshold from 25 to 60 μg/m3 [36,40,41,42]. Numerous studies seem to be in line with our findings [43,44,45]. According to the results from a Danish cohort study of 49,564 individuals, the relationship of ozone and CVD mortality was inverse. The research team pointed out that O3 is often inversely correlated with pollutants such as NO2 and PM due to the atmospheric chemical reaction between O3 and NO forming NO2; the inverse correlation is also evident in our data [43]. The same statement was made by other authors who received the same curing effect of ozone [15,46]. Other long-term studies suggest minor or no significant effect on CDV risk of morbidity or mortality [41,47,48]. On the other hand, there is a large body of evidence that ozone increases the risk of CVD mortality [36,40,41,42,49,50,51,52]. According to our lag analysis, NO, NO2 and NOx lag 0 were significantly associated with stroke incidence, while lags 1–3 were not related with increased risk for stroke or for myocardial infarction. Moreover, SO2 lagged 2 days and PM2.5 lagged 2 days were significantly related with an increased incidence of myocardial infarction. Although the RRs for stoke and myocardial infarction were not significant for other pollutants and lags, RRs for NO, NO2, NOx, SO2 as well as for PM10 and PM2.5 were mostly greater than 1 for lags 0 and 1. The results suggest that the effects of PM2.5 are acute in terms of CVD deaths. Other studies discovered similar findings. Results from a national study in the United States showed that on lag day 0 and 1, PM2.5 had the largest effect on CVDs [53]. Another study in Beijing also discovered PM2.5′s lag effects within 0–3 lag days [54]. According to the lag analysis of Tian et al., the lag association of PM2.5 with CVD mortality was statistically significant from lag day 0 to 3 [55]. In our study, the strongest association between PM10 atmospheric concentration and incidence of stroke and myocardial infarction occurred for lags 0 and 1. Similar results were assessed by Fisher et al. According to the results of his case-crossover analysis, the strongest association of PM10 on ischemic stroke was for the lag 0 period [13]. This association was also observed by other authors [51,56,57,58]. Our age-oriented analysis of the influence of air pollutants indicated that elderly populations are among the most vulnerable to the risk of stroke and myocardial infarction. Risk of stroke and myocardial infarction for this group was visibly increased for the exposure to NO2, NO and NOx and PM2.5, whereas exposure to SO2 and PM10 was related with an increased incidence of myocardial infarction. Statistical significance was not achieved for any of air pollutants studied for stroke incidence for the younger part of the studied population. On the other hand, exposure of the younger group to NO2, NO and NOx has a substantially increased incidence of myocardial infarction. Similar findings were observed by Goldberg et al., who found positive associations between daily non-accidental mortality of the elderly group population and all air pollutants except for O3 [59]. This specific susceptibility of elderly people was also emphasized by other researchers [26,60,61,62,63,64,65]. Evidence suggests that women may be more vulnerable than men to develop cardiovascular events upon air pollution exposure [23,35,59,66,67,68,69,70,71]. In our research, stroke incidence due to exposure to NO2 and NO was statistically significant only in the women group. An influence of PM2.5 on stroke incidence among women, although insignificant, should be noted. Due to Clougherty’s review, more studies of adults report stronger effects among women, particularly for older persons [72]. In the PAPA Study (The Public Health and Air Pollution in Asia), Kan et al. reported stronger associations between the gaseous pollutants SO2, NO2, O3 and PM10 and daily respiratory mortality among women and the elderly [73]. On the other hand, there are some that have reported no gender differences or that have found stronger effects in men [65,74,75,76,77]. Results obtained for carbon dioxide are confusing. Evidence presented in the novel literature shows that prolonged exposure to higher than normal concentrations of CO2 in atmospheric air can cause a variety of negative health effects. These may include headache, dizziness, restlessness, tingling or pins or needles feeling, difficulty breathing, sweating, tiredness, increased heart rate, elevated blood pressure, coma, asphyxia, and convulsions [78,79]. Nonetheless, the relationship between low-level exposure to CO2 and the reported symptoms remains inconsistent between studies [80,81]. Furthermore, the literature is missing novel studies concerning short-term CO2 exposure with respect to the risk of either stroke or myocardial infarction. According to the literature, carbon dioxide (CO2) levels affect vascular smooth muscle tone and hence play an important role in cerebral autoregulation [82,83,84]. Based on the evidence provided by Slinet et al. ’s meta-analysis, acute stroke patients are significantly more likely, compared with controls, to be hypocapnic [85]. Hypocapnic patients suffer from reduced carbon dioxide concentration in the blood. Physiological concentration of carbon dioxide plays a role in relaxing the bronchi, smooth muscles, airways and blood vessels, increasing their diameter and thus reducing the risk of either stroke or myocardial infarction [86]. These physiological findings seem to be in accordance with our assessment results. Nonetheless, further epidemiological studies are required in order to evaluate the clinical impact of these findings. Our study has some important limitations related to exposure assessment. First, we used averaged estimates of ambient air pollution from six stations situated at different locations of the Gdansk municipality area, as precise addresses of hospitalized patients were not accessible. Therefore, actual personal exposure might differ from the values calculated and used for this assessment. Second, the ordinary kriging method we used to estimate daily air pollutants likely reflects urban-scale variation in pollutant levels but may not fully capture microscale spatial gradients typical of urban environments. Moreover, air pollution in urban areas is characterized by high spatial fluctuations in the levels of pollutants, which could affect the results. Third, as we used incidence data coming from the National Health Fund, such a database may contain some disease misclassifications and gaps which we do not know about. Moreover, differences between the day of stroke symptom onset and day of hospitalization may have introduced some degrees of exposure misclassification, which may tend to bias the risk estimates toward the null. Fourth, in regression models, the observations must be independent, which in our case would mean that strokes and myocardial infarctions occurring on a given day do not affect the likelihood of these occurring in the future (within the studied period). This assumption is clearly wrong, as such an incident clearly increases the likelihood of it recurring in the future, and a repeat stroke might not be related to exposure factors but simply to patient compliance. Fortunately, the share of reoccurring myocardial infarctions in our database was only $0.3\%$ (22 out of 6910 cases). Therefore, we treat these infarctions as ordinary cases, and regression models are created for all types of infarction. ## 5. Conclusions In this time-series cross-sectional study, we found strong evidence that supports the hypothesis that transient elevations in ambient PM2.5, PM10, NO2, SO2 and CO are associated with higher relative risk of ischemic stroke and myocardial infarction incidents. Daily levels of NO2 and NOx were significantly associated with the relative risk of ischemic stroke, although we did not find such significance for PM10 and PM2.5. On the other hand, strong associations of particulate matter as well as gaseous air pollutants mentioned above were observed for myocardial infarction. The strongest health outcome of pollutants exposure was observed within the same day and diminished with every following day. Health effects were heterogeneous with respect to age and sex. 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--- title: Extracellular Vesicles of COVID-19 Patients Reflect Inflammation, Thrombogenicity, and Disease Severity authors: - Anat Aharon - Ayelet Dangot - Fadi Kinaani - Mor Zavaro - Lian Bannon - Tali Bar-lev - Anat Keren-Politansky - Irit Avivi - Giris Jacob journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054500 doi: 10.3390/ijms24065918 license: CC BY 4.0 --- # Extracellular Vesicles of COVID-19 Patients Reflect Inflammation, Thrombogenicity, and Disease Severity ## Abstract Severe COVID-19 infections present with cytokine storms, hypercoagulation, and acute respiratory distress syndrome, with extracellular vesicles (EVs) being involved in coagulation and inflammation. This study aimed to determine whether coagulation profiles and EVs reflect COVID-19 disease severity. Thirty-six patients with symptomatic COVID-19 infection with mild/moderate/severe disease (12 in each group) were analyzed. Sixteen healthy individuals served as controls. Coagulation profiles and EV characteristics were tested by nanoparticle tracking analysis (NTA), flow cytometry, and Western blot. While coagulation factors VII, V, VIII, and vWF were comparable, significant differences were found in patients’ D-Dimer/fibrinogen/free protein S levels compared to controls. Severe patients’ EVs displayed higher percentages of small EVs (<150 nm) with increased expression of exosome marker CD63. Severe patients’ EVs displayed high levels of platelet markers (CD41) and coagulation factors (tissue factor activity, endothelial protein C receptor). EVs of patients with moderate/severe disease expressed significantly higher levels of immune cell markers (CD4/CD8/CD14) and contained higher levels of IL-6. We demonstrated that EVs, but not the coagulation profile, may serve as biomarkers for COVID-19 severity. EVs demonstrated elevated levels of immune- and vascular-related markers in patients with moderate/severe disease, and may play a role in disease pathogenesis. ## 1. Introduction The emerging novel coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, is presently the most relevant epidemic health threat. Healthcare centers extensively explored and reported the clinical features of the disease, but its virus pathogenicity remains unclear [1]. SARS-CoV-2 displays a high tropism to epithelial cells, such as pneumocytes, the vascular endothelium, and macrophages. This explains the high incidence of acute respiratory distress syndrome (ARDS)-like features in COVID-19 patients, which is associated with prominent activation of the inflammation–coagulation systems [2,3]. The angiotensin-converting enzyme 2 (ACE2) receptor and transmembrane serine protease 2 (TMPRSS2) play pivotal roles in SARS-CoV-2 infectivity. The coronavirus’ membrane-bound spike (S1) protein binds with high affinity to the membranous ACE2, while the S2 protein is cleaved by the host cell’s TMPRSS2 to allow viral entry into the target cell [4,5]. SARS-CoV-2 entry into host epithelial cells causes the loss of the cellular ACE2 protective (anti-inflammatory, anti-oxidative, anti-apoptotic, and anti-thrombotic) functions, leading to inflammation along with various levels of a cytokine storm, pneumonitis, and endothelial injury [6], resulting in increased procoagulant states in COVID-19 patients. Moreover, increased incidence of thromboembolic events among those with severe disease despite the use of thromboprophylaxis were documented [7]. Therefore, thrombocytopenia and fibrinolysis (high di-dimers, DD) magnitudes are considered significant predictors of mortality [8]. We recently summarized and reported on the role of hyper-fibrinolysis in the inflammation process among patients with COVID-19 [9]. We highlighted the facilitated SARS-CoV-2 cell entry by means of the membranous plasmin (the main product of the fibrinolysis) that has a function similar to that of TMPRSS2, i.e., providing a “plasmin-mediated pathway”. The increased coagulation–inflammation process in COVID-19 caused by SARS-CoV-2 is related to endothelial and epithelial host cell injuries with the involvement of extracellular vesicles (EVs). EVs include small vesicles (<150 nm, exosomes) and larger vesicles (<1 micron), which shed from the cell surface and express antigens derived from their parental cells [10]. Circulating EVs originating from blood cells and other tissues reflect physiological and pathological states and can serve as biomarkers for diagnosis, treatment monitoring, and disease prognosis [11]. The number of studies showing correlations or associations between EV characteristics and disease prognosis and severity have increased in the last decade. However, in general, the majority of studies on patient EVs are based on a relatively low numbers of subjects [12]. Previous studies have demonstrated that EVs contain cytokines and coagulation factors [13,14] and are involved in hypercoagulation [15,16], inflammation pathways [17], and vascular injury [18] and reflect endothelial damage [19]. We also demonstrated that EVs could reflect disease severity and thrombogenicity in various pathologies, including diabetic vascular complications [19], Alzheimer’s disease [20], and acute myeloid leukemia [21]. EVs serve as novel mediators in the pathogenesis of COVID-19. They facilitate viral spreading via transfer of viral particles and receptors to recipient cells [22] and therefore, should be considered as COVID-19 infectious units [23]. EVs can transfer viral receptors such as ACE2 to recipient cells to facilitate viral infection or directly transport infectious viral particles to target cells, thereby enhancing virus spreading [24]. Several reports have documented an increase in circulating EVs in COVID-19 patients [25], specifically, platelet EVs [26,27]. In addition, there are studies demonstrating the involvement of EVs in the cytokine storm and tissue injury of COVID-19 patients [28]. We therefore wanted to see if EVs can be used as biomarkers for disease severity in COVID-19 patients. We hypothesized that the magnitude of the inflammatory response of the injured host cells could determine the degree of disease severity in affected individuals and this state may be reflected by the patients’ coagulation profile and EV characteristics. We therefore conducted a study in patients with three different clinical severity levels of COVID-19 to ascertain whether the extent of endothelial cell injury and related inflammatory and coagulation processes can be determined by EVs and their use as biomarkers. ## 2. Results To define biomarkers that will reflect the inflammatory response magnitude and disease severity in COVID-19 patients, coagulation tests as well as analyses of EV characteristics (EV size, concentration, membrane antigen expression, and cytokine content), were performed. ## 2.1. Patient Characteristics Thirty-six patients with a COVID-19 infection (confirmed by positive SARS-CoV-2 RT-PCR) were divided into three groups based on disease severity (according to the Israeli Ministry of Health (MOH) criteria): mild ($$n = 12$$), moderate ($$n = 12$$), and severe ($$n = 12$$). The patient characteristics are presented in Table 1. The study also included sixteen healthy controls (HCs). Most of the patients (27, $75\%$) had a BMI > 25: overweight ($$n = 10$$ [$28\%$]) or obese ($$n = 17$$ [$47\%$]). There are no statistically significant differences in terms of age and sex between the three groups. However, the white blood cell count (WBC) was increased in the moderate group compared to the mild group ($$p \leq 0.049$$), creatinine levels were higher in the moderate group compared to the severe group ($$p \leq 0.0142$$), and the LDH and AST levels were higher in the severe group compared to the mild group ($$p \leq 0.0230$$ and $$p \leq 0.0347$$, respectively). None of our selected patients had any malignant or premalignant conditions. None of our subjects developed thromboembolic events. ## 2.2. Plasmatic Hemostatic Factors Procoagulant, anticoagulant, and fibrinolytic profiles of the COVID-19 patients were determined by specific assays, as described in our previous publication [29] and were compared to the normal ranges of each test (Table 1) and to the healthy control (HC) group (Figure 1). The von Willebrand factor (vWF) antigen, factor V (FV), and factor FVIII (FVIII) levels were comparable for all three groups (Table 2). The majority of the COVID-19 patients’ prothrombin time (PT) and partial thromboplastin time (PTT) values were within the normal range (PT $\frac{35}{36}$ of the patients; PTT $\frac{32}{36}$ of the patients, Table 2). Higher levels of D-dimer were found in the moderate and severe COVID-19 patients compared to the HC group ($p \leq 0.05$ and $p \leq 0.01$, respectively). About two-thirds of the COVID-19 patients displayed higher D-dimer levels than the normal range ($66\%$ in the mild and $75\%$ in the moderate and severe patients, Figure 1a). The percentage of protein C was found to be similar in the HCs and in the majority of COVID-19 patients ($\frac{32}{36}$). The percentage of protein C was in the normal range (70–$150\%$). Significantly higher levels of free protein S were found in the HCs (94.06 ± $8.945\%$) compared to mild COVID-19 patients (46.35 ± 16.85, $p \leq 0.001$), moderate COVID-19 patients (61.55 ± $26.18\%$, $p \leq 0.01$), and severe COVID-19 patients (54.00 ± 20.84, $p \leq 0.001$). Moreover, about $70\%$ of the COVID-19 patients ($\frac{25}{36}$) displayed lower values of free protein S, i.e., below the threshold of the normal range (<$65\%$) (Figure 1b,c). Mean fibrinogen levels were similar for all patient subgroups with significantly higher levels in the mild COVID-19 patients (522.7 ± 134.2 mg/dL) compared to the HC group (339.3 ± 43.74 mg/dL, $p \leq 0.01$). Mean fibrinogen levels were above the normal upper threshold (>348 mg/dL) in most of the COVID-19 patients ($100\%$ of the mild group, $88\%$ of the moderate group, and $75\%$ of the severe group) (Figure 1d). No significant changes were found in the levels of Alpha2-anti-plasmin (AP) between the patient groups. However, about $75\%$ of the moderate COVID-19 patients had low AP levels, below the threshold of the normal range (Figure 1e). ## 2.3.1. EV Size and Exosome Markers To ensure that the samples contained vesicles, transmission electron microscope (TEM) images were taken. The images showed EVs in a variety of sizes in all patient subgroups compared to HCs. Nanoparticle tracking analysis (NTA) displayed a similar concentration and size of EVs in platelet-poor plasma (PPP) obtained from the COVID-19 patients and HCs (multivariate analysis, Figure 2a). However, using t test analysis, we found that EVs obtained from patients with severe COVID-19 were smaller than the EVs of HCs (87.93 ± 12.76 nm vs. 99.26 ± 10.10 nm, $$p \leq 0.0076$$) (Figure 2b). In line with this result, the majority of the EVs obtained from severe COVID-19 patients were smaller than 150 nm (t test $$p \leq 0.0158$$ Figure 2c) and expressed significantly higher amounts of the exosome marker CD63 (expressed as a ratio of actin) (Figure 2d, Supplementary Figure SM1a–c). ## 2.3.2. SARS-CoV2 Entrance Proteins ACE2 and TMPRSS2 Expression in EVs Severe COVID-19 patients’ EVs displayed a trend of increasing levels of ACE and TMPRSS2 compared to HCs, and the size effect analysis displayed large differences between HCs vs. severe COVID-19 patients (ACE: t-test, $$p \leq 0.063$$, Cohen’s $d = 1.025068$ and TMPRSS2: t-test $$p \leq 0.0496$$, Cohen’s $d = 0.856734$; Figure 2d, Supplementary Figure SM1c,d). Large size effects on ACE expression were also found between the EVs of mild vs. moderate and vs. severe patients (Cohen’s $d = 0.873$ and Cohen’s $d = 0.700$, respectively) and between the EVs of mild vs. severe patients in TMPRSS2 EV expression (Cohen’s $d = 0.898499$). Moreover, ACE expression was found to correlate with exosome CD81 marker expression ($r = 0.5296$; $$p \leq 0.0054$$; Figure 2e). ## 2.3.3. EV Membrane Antigen Expression EV membrane antigens were analyzed by flow cytometry using the bead size to set the gate for EV accumulation. An example of membrane antigen expression on EVs obtained from each group is presented in Supplementary Figure SM2. The expression of three endothelial cell markers (CD144, CD31 + 41-, and CD62E) on EVs was found to be similar in the study cohorts (using multivariate analysis). However, t-test analysis showed higher levels of VE-cadherin (CD144) in the moderate COVID-19 patients’ Evs compared to HC Evs (15.38 ± 7.189 vs. 7.928 ± 5.314, $$p \leq 0.0221$$) and large size effects (Cohen’s d > 0.9) in CD144 EV expression were seen between HCs and the severe patient subgroups (Figure 3a). In addition, a t-test analysis revealed an increase in severe COVID-19 patients’ EVs expressing platelet endothelial cell (EC) adhesion molecules (PECAM-1, CD31 + CD41-; $$p \leq 0.0452$$), with a large size effect between patient subgroups (mild vs. severe patients, Cohen’s $d = 0.978$ and moderate vs. severe patients, Cohen’s $d = 0.961$). There was also a trend towards an increase in severe COVID-19 patients’ EVs expressing endothelial–leukocyte adhesion molecule 1 (E-selectin, CD62E) compared to the HCs’ EVs ($$p \leq 0.0586$$) with large size effects, when comparing the EVs’ CD62E expression between HCs and moderate and severe patients (Cohen’s $d = 0.835$) (Figure 3b,c). The EVs of the COVID-19 patients expressed significantly higher levels of platelet antigens (alpha IIb integrin CD41) compared to those of the HCs ($p \leq 0.05$ for the moderate group, and $p \leq 0.01$ for the severe group). The expression of activated platelet markers were similar in the multivariate analysis (Figure 4a,b). Levels of EVs expressing the tissue factor (TF) antigen were similar for the three groups with a trend towards a decrease in the severe group’s samples (moderate vs. severe, Cohen’s d 0.793). A TF activity assay revealed that three of the eight samples obtained from severe COVID-19 patients clotted during EV pellet isolation and were therefore excluded from the statistical analysis which showed a significant increase in TF activity in the severe group compared to the HCs (t-test, $$p \leq 0.0556$$) and to the mild group (t-test, $$p \leq 0.0451$$) (Figure 4c,d). In addition, the levels of EV expression of EPCR significantly increased in the moderate group ($p \leq 0.05$) compared to those of the HCs. Thrombomodulin (TM)-expressing EVs were similar in all study cohorts with moderate to large size effects when comparing HC vs. moderate, Cohen’s $d = 0.8669$, and HC vs. severe, Cohen’s $d = 0.60104$ (Figure 4e,f). High correlations were found in all patients’ EPCR and TM EVs ($R = 0.9037$; $p \leq 0001$) and between the percentages of EPCR-expressing EVs and CD144-expressing EVs ($R = 0.6004$; $p \leq 0001$) (Figure 5a,b). ## 2.3.4. EV Immune Cell Markers and Cytokine Content The percentage of CD4- and CD8-expressing EVs were higher in the moderate COVID-19 patients ($$p \leq 0.0077$$ and $$p \leq 0.0062$$, respectively) and CD8-expressing EVs were higher in the severe COVID-19 patients ($$p \leq 0.0051$$) compared to the HCs. The overall ratio of CD4+/CD8+ EVs in the mild ($$p \leq 0.0433$$) and severe COVID-19 patient groups ($$p \leq 0.0318$$) were lower than those in the HC group (Figure 6a–c). EVs expressing T cell activation markers (CD154 and CD28) were higher in moderate and severe COVID-19 patients compared to the HCs (Figure 6d,e). The levels of CD28-expressing EVs highly correlated with CD4- and CD8-expressing EVs (correlation with CD4: $r = 0.864$, $p \leq 0.0001$; correlation with CD8: $r = 0.6894$, $p \leq 0.0001$) (Figure 6f,g). Significantly increased levels of membrane antigens were found in the severe COVID-19 patients’ EVs that originated from monocyte or macrophages cells (CD14-expressing EVs, $$p \leq 0.012$$) compared to the EVs of the mild COVID-19 patients ($$p \leq 0.0186$$) (Figure 6h). The levels of B cell membrane antigens (CD22) were significantly increased in patients with moderate COVID-19 disease compared to the HCs ($$p \leq 0.0186$$), but decreased in severe patients compared to HCs ($$p \leq 0.0276$$) (Figure 6i). The IL-6 content was twice as high in the severe COVID-19 patients’ EVs compared to the HC EVs ($$p \leq 0.0451$$), and also compared to mild and moderate COVID-19 patients ($$p \leq 0.0186$$, $$p \leq 0.0426$$, respectively) (Figure 6; Supplementary Figure SM1e–g). There was a trend towards an increase in TNFα in the EVs obtained from all three patient subgroups compared to the HCs with moderate-large effect sizes (HC vs. mild COVID 19 patients, Cohen’s $d = 0.456$; HC vs. moderate COVID 19 patients, Cohen’s $d = 0.678$; and HC vs. severe COVID-19 patients, Cohen’s $d = 0.702$). Large size effect differences were found between IFNɣ levels in HC EVs and patient EVs (HC vs. mild COVID 19 patients, Cohen’s $d = 1.268$; HC vs. moderate COVID-19 patients, Cohen’s $d = 0.785$; and HC vs. severe COVID 19 patients, Cohen’s $d = 0.946$). The levels of IL-17 were similar for the patients and the controls, but the size effect analysis displayed large differences between HCs and severe COVID-19 patients (Cohen’s $d = 0.73115$). In addition, the size effect analysis displayed moderate differences between mild and severe COVID-19 patients in the content of TNF (Cohen’s $d = 0.428$), IFNɣ (Cohen’s $d = 0.424187$), IL-2 (Cohen’s $d = 0.544$), and IL-17 (Cohen’s $d = 0.528$) (Figure 7 and Supplementary Figure SM1f–h). ## 3. Discussion The severity of COVID-19 in affected patients is mainly determined by clinical parameters rather than by laboratory tests. It is highly important to have reliable laboratory parameters that will support the decision-making process regarding hospitalization and treatment of COVID-19 patients. Inflammatory biomarkers can clarify the patient’s condition, which is related to clinical status. For example, protein C (PC) has a prognostic utility and can serve as a biomarker for adult sepsis prognosis. A meta-analysis showed that PC levels are significantly higher in sepsis survivors compared to non-survivors and in patients with sepsis but not with disseminated intravascular coagulation (DIC) [30]. Most of the patients in our study displayed significantly higher D-dimer levels, with the highest level being in the severe group, with lower levels of free protein S and higher fibrinogen levels compared to the HC group (mainly in the mild patient group). However, the levels of all three parameters (D-dimer, free protein S, and fibrinogen) in the patient subgroups were similar, and cannot be used to distinguish between disease severities. Other laboratory test parameters, including blood cell counts and coagulation profile and chemistry (presented in Table 2), were also similar for the three subgroups. In contrast, we found that EVs could serve as biomarkers for the COVID-19 disease intensity. The EVs of COVID-19 patients with moderate and severe disease revealed changes in endothelial function, coagulation, immune cell response, and inflammation properties. Our study supports recently published studies, albeit based on relatively small groups, showing that the EVs of COVID-19 patients may play a role in endothelial injury, coagulation, and inflammation [31,32,33,34]. In the current study, we found important differences between the EV characteristics of HCs and those from moderate and severe COVID-19 patients. While EV size and concentration were found to be similar in the study cohorts, an increasing trend was found in the percentage of EVs with a size of <150 nm and in exosome markers in severe patients compared to controls that were correlated with ACE expression on EVs. This is in line with previous study results [35,36]. COVID-19 infection results in the loss of ACE function. SARS-CoV-2 enters cells by binding to ACE2 receptors, and activating the renin–angiotensin–aldosterone (RAAS) system. The cleavage of spike proteins by a protease, such as TMPRSS2, facilitates viral entry into the cells. This process leads to shedding of host ACE2 receptors and the loss of its protective function [37]. Loss of ACE2 function leads to upregulation of the RAS/Ang II pathway resulting in vasoconstriction, microthrombosis, endothelial injury, and induction of various inflammatory cascades [6]. An increase in ACE-expressing EVs in COVID-19 patients with severe disease and a trend of increased TMPRSS2 may be indicative of the loss of ACE on the cell surface which leads to endothelial injury and facilitates inflammation. Several studies have shown that EVs which are shed from virus-infected cells contain viral components, including proteins and genetic material [38]. Together with ACE on their surface, COVID-19 patients’ EVs may be considered as viral spreading particles. ## 3.1. EV and Thrombogenicity, Inflammation, and Fibrinolysis Platelet and endothelial activation were suggested as potential mechanisms resulting in thrombotic complications among COVID-19 patients [39]. In the current study, a non-significant increase was found in endothelial markers, such as platelet PECAM-1 (CD31 + 41-), E-selectin (CD62E), an endothelial cell-specific selectin that is expressed after activation with pro-inflammatory cytokines, and VE-cadherin, which is located on endothelial gap junctions and is required for maintaining the endothelial barrier. An increase in EVs expressing endothelial markers may be indicative of vascular injury that can result in thrombotic complications. However, our study indicates only moderate effects of endothelial EVs. There is much evidence supporting the association between EV-mediated endothelial apoptosis, endothelial injury, and the inflammation state in patients with COVID-19 [31]. SARS-CoV-2 damages the vascular endothelium, disrupting key roles of the endothelial cells such as anti-inflammatory and anticoagulant functions. When bound to the endothelial protein C receptor (EPCR), the endothelial anticoagulant protein C complex (protein C and S combined and bound to thrombomodulin) is committed to anticoagulant and anti-inflammatory functions. Upon endothelial injury, the soluble form of EPCR (sEPCR) changes its function towards coagulation and inflammation [40]. The translation of the SARS-CoV-2-related endothelial injury into a process of inflammation and intravascular clotting negatively affects the course of the disease. In addition, the presence of very high plasma DD levels is suggestive of hyper-fibrinolysis in patients with severe COVID-19. We found that platelet EVs were significantly elevated in the moderate and severe COVID-19 patient subgroups compared to HCs as described previously [26], without significant changes in the activated platelet EVs. EV-TF activity was notably increased in patients with severe COVID-19 compared with mild disease patients and HCs, as previously documented [33]. However, no significant differences were found in the EV-TF expression of COVID-19 patients or HCs. TF is the main activator of the coagulation cascade. It is located in sub-endothelial tissues and is found in the blood circulation in pathological states (e.g., inflammation, sepsis, and cancer). TF is expressed on activated endothelial cells, monocytes, and their EVs and also as a soluble form [41]. TF’s structure, presentation, and expression levels do not always relate to its function [42]. A reduction in TF expression on EV surfaces in the severe group may indicate TF consumption and internalization into the cells. In contrast, EV pellets from PPP probably contained both surface TF and TF that was packaged as cargo inside the EVs, which had a sufficient amount to activate the coagulation cascade. Either way, none of the patients experienced DVT. To the best of our knowledge, we are the first to describe a significant increase in EVs expressing EPCR in COVID-19 patients with severe disease. EPCR and TM are cofactors that activate protein C (APC), which then cleaves the coagulation cofactors Va and VIIIa, thereby downregulating thrombin generation and serving as an anticoagulant [43]. EVs expressing EPCR may be considered as being part of soluble EPCR (sEPCR) which can bind to APC and reduce its availability. sEPCR is therefore considered a pro-coagulant factor. Moreover, cleavage and release of EPCR from endothelial cells reduces its anti-inflammatory intracellular pathway [43]. In addition, during vascular damage related to infections, sepsis, and inflammation, cytokines from activated leukocytes suppress cell surface expression of TM and EPCR, resulting in reduced levels of APC and an overall increase in thrombogenicity. SARS-COV2 patients display higher levels of sEPCR [44,45,46] and a downregulation of endothelial TM caused by hypoxia that contributes to severe infiltration and coagulopathy in lungs [47]. We assume that the EPCR-expressing EVs are part of the soluble fraction of circulating EPCR. This study further hints that the measured plasma components of the coagulation system have increased activity in COVID-19 patients. However, the laboratory approach used in our study was not able to show relevant differences in the pro-coagulant and anticoagulant components between the different disease severities. Although the fibrinolytic system showed that its main product, D-dimers, is high in most of the COVID-19 patients but was unrelated to their disease severity. The potent scavenger capabilities of activated plasmin, i.e., alpha2-atiplasmin, was low only in patients with mild-moderate disease severity. This finding indirectly suggests that plasmin is involved in the pathogenicity of SARS-CoV2 infectivity [48]. ## 3.2. Immune Cell EVs and Cytokine Cargo In the current study, COVID-19 patients with severe disease were characterized by high levels of EVs originating from monocytes, B cells, and activated T cells. Previous studies found that changes in COVID-19 disease severity are accompanied by changes in monocytes, macrophages, and B and T cells [3,49]. We demonstrated that changes in EV characteristics with significant increases in EVs expressing CD4, CD8, and CD14, may reflect changes in their parental immune cells. Moreover, the trend of reduction in the CD4/CD8 ratio that was found in the EVs of COVID-19 patients with severe disease was also demonstrated in studies that described the changes in the peripheral lymphocytes and inflammatory cytokines in COVID-19 patients in general [50]. Cytokines can be secreted as soluble factors or as EV-encapsulated forms [51]. We found that the EVs of COVID-19 patients contained higher levels of IL-6, TNFα, IL-2, and INFϒ compared to HCs. The SARS-CoV-2 components (spike and nucleocapsid proteins) trigger the host’s immune system. These viral antigens are recognized by B cells or by other MHC-presenting cells, resulting in antibody production, increased cytokine secretion, and cytolytic activity in the acute infection phase [52]. Clinical reports show that both the mild and severe forms of COVID-19 disease result in changes in circulating leukocyte subsets and cytokine secretion, specifically IL-6, IL-1𝛽, IL-10, TNF, GM-CSF, IP-1, IL-17, and MCP-3 [53]. In the current study, the most significant change in the EVs’ cytokine cargo was related to the IL-6 content in the EVs of COVID-19 patients with severe disease. Monocyte-derived macrophages, which are the first responders to viral infections among the immunoregulatory cells, mainly secrete IL-6 and are the main generators of the inflammatory response in COVID-19 patients [22,54]. We had earlier demonstrated that monocyte-derived microparticles and exosomes induce procoagulant and apoptotic effects on endothelial cells [55]. IL-6 and TNF are linked with fever and with constitutional symptoms, and increase in capillary permeability, hypotension, and acute respiratory failure [53]. We found that increases in IL-6 were early indicators for the progression of mild to severe COVID-19 disease. The activation of T cells and their ability to produce large amounts of effector cytokines (IL-2, IFNγ, and TNF) was also reflected by EVs obtained from COVID-19 patients with severe disease in the current study. During a SARS-CoV viral infection, T cells recognize the viral antigens presented by MHC class I, which induce cytotoxic activity of CD8+ T cells and MHC class II that present peptides to CD4+ T cells [52]. We also found a trend of increasing EVs expressing CD154+ (CD40L), which is primarily expressed on activated T cells, and in the costimulatory molecule CD28 that were correlated with the increase in CD4- and CD8-expressing EVs in patients with severe disease. These findings support the view that the cell immunity response is increased during COVID-19 infection and promote the inflammation This study has some limitations. There were no laboratory test results or BMI definitions for the healthy controls. Such criteria were available only to the hospitalized patients, but not for the HCs. We assume that this has only a minor effect on the study results. The plasma volume that could be collected from each patient was limited, and each sample was used in some but not all the experiments. As described before, studies on EVs are complicated. Their small size requires special conditions for isolation and characterization, and currently, the majority of studies on patients EVs is based on a relatively low number of subjects [12] as was the case in our study which contained a small cohort of patients. Even though COVID-19 is a global pandemic, studies on COVID-19 patients’ EVs are limited and based on small study cohorts. Krishnamachary et al. [ 32] compared the inflammatory and cardiovascular disease-related protein cargoes of circulating large and small extracellular vesicles (EVs) from 84 hospitalized patients infected with SARS-CoV-2 from different stages and disease severity. Guervilly et al. quantified the EV-TF activity in a cohort of hospitalized patients with COVID-19 ($$n = 111$$) and evaluated its link with inflammation, disease severity, and thrombotic events [33]. Future studies on large cohorts will determine if EVs can be used as biomarkers for disease severity related to COVID-19 infection and possibly to other viral infections. ## 4.1. Patient Acquisition This prospective study was conducted on COVID-19 patients that were admitted to the Internal Medicine Department of Tel Aviv Sourasky Medical Center in Tel Aviv, Israel, a university-affiliated tertiary hospital, between January–April 2021, during Israel’s third wave of the epidemic, which was dominated by the SARS-CoV-2 alpha and beta variants. The study was approved by the local IRB according to the Helsinki principles (Approval No. TLV-401157). For EV characterization, the study also included sixteen HC, age ≥ 18 years, sex- and age-matched, three weeks after receiving BNT162b2 mRNA COVID-19 vaccines, who served as the control group in the study that was registered on clinicaltrials.gov (#NCT04746092). All patients and controls provided informed consent. ## 4.1.1. Patient Population Thirty-six consecutive patients were enrolled upon their admission to our internal medicine department after having been diagnosed in the emergency department (ED) as having symptomatic COVID-19. The diagnosis of COVID-19 was confirmed by positive SARS-CoV-2 RT-PCR findings from throat and nasopharynx swabs. The enrolled patients were categorized into three groups according to their disease severity (defined according to the Israeli MOH criteria). We stopped enrollment for each group after reaching 12 patients in each group. Mild illness was defined by a variety of signs and symptoms, such as loss of smell and taste and flu-like symptoms, without shortness of breath, normal chest X-rays, and normal SpO2 in room air. Moderate illness was defined by the additional symptoms of lower respiratory diseases (clinical and chest X-ray findings), but with a SpO2 level ≥ $94\%$ in room air. Severe illness was defined by symptoms and findings similar to the moderate cases and a SpO2 level < $94\%$ in room air. Patients were excluded if they were critically ill, or had evidence of a bacterial infection, debilitating and critical illness not related to COVID-19, chronic lung disease with low SpO2 levels requiring chronic oxygen support, immune-suppressed conditions, history of clot disorders, use of anticoagulant medication, were unable to sign a consent form, diagnosed as having a thromboembolism event, or were receiving any anti-COVID-19 drugs. All patients provided a detailed medical history and underwent a physical examination, an electrocardiogram, a chest X-ray, and continuous hemodynamic monitoring, and were monitored by closed circuit television. Part of the general blood tests were performed on the ED samples and the rest were done on samples taken upon arrival to the ward, before any medical intervention. ## 4.1.2. Blood Tests All laboratory tests are detailed in Table 2. The coagulation parameters prothrombin time (PT), activated partial PT time (aPTT), factor V and factor VIII activities, von Willebrand factor (vWF) antigen, and fibrinogen were measured as described elsewhere [56]. The anticoagulant protein C and free protein S, and fibrinolytic markers (e.g., D-dimer), as well as activities of plasminogen and α2-antiplasmin of each patient were validated as described by Ali-Saleh et al. [ 57]. The results were compared to standard normal values. ## 4.2. EV Isolation and Characterization EVs were isolated as previously described [58], according to MISEV2018 [59]. Specifically, platelet-poor plasma (PPP) was obtained after two sequential centrifugations (15 min 1500× g, 24 °C) within one hour of collection and frozen in aliquots at −80 °C [60]. The size, concentration, and membrane antigen expression of the EVs were validated on thawed, diluted PPP samples. PPP EV size and concentration were validated by nanoparticle tracking analysis (NTA; Malvern Panalytical NanoSight NS300, Malvern, UK, as described in Supplementary Methods SM1). EV pellets were isolated from thawed PPP by one hour of centrifugation (Centrifuge MIKRO 220R, rotor 1189-A, Hettich, Tuttlingen Germany 20,000× g, 4 °C, braking—0). The EV samples that were washed with PBS and pelleted (1 h, 20,000× g, 4 °C) were used for transmission electron microscopy (TEM) imaging. Briefly, samples were adsorbed on carbon-coated grids and stained with $2\%$ aqueous uranyl acetate. The samples were examined using a JEM 1400 plus transmission electron microscope (Jeol, Tokyo, Japan). According to the minimal information for studies of extracellular vesicles (MISEV2018 [60]), using fixed samples for TEM is not a quantitative method, as not all particles in a given volume can be imaged, just those that adhere to the grid surface. In addition, the EV pellet cargo was analyzed by Western blot methodology for expression of SARS-CoV-2 entry proteins (ACE-2 and TMPRSS2) and cytokine content was measured by Western blot (Supplementary Method SM2). EV membrane antigen levels were assessed by flow cytometry (CytoFLEX, Beckman Coulter, Indianapolis, Indiana. USA) using fluorescent antibodies (Supplementary Table SM1). Events were collected over time at a flow rate of 10 µL per minute. The controls and samples were analyzed with the same acquisition settings and reagent conditions. Instrument configuration and settings: Gain: FSC 500; SSC 100; Violet SSC 40; PE 120; APC400; FITC 100, threshold: manual 10000 height. EV pellet coagulation activity was validated by the Tissue Factor Activity Assay Kit (Abcam, ab108906, Cambridge, UK). ## 4.3. Statistics Statistical analysis was performed using the GraphPad Prism 5 software (GraphPad Software Inc., CA, USA). The results were assessed by multivariate analysis, one-way ANOVA, a non-parametric Kruskal–Wallis test, and a Dunn’s post-test that compared all pairs of groups (* $p \leq 0.05$; ** $p \leq 0.01$; *** $p \leq 0.001$). The non-parametric Mann–Whitney U test and Student’s t test were used when only two groups were compared. A p value < 0.05 was considered statistically significant. Spearman correlations were performed, along with coefficient value (rho) and $95\%$ confidence intervals. A Fisher’s exact test was used to determine whether or not there was a significant association between two categorical variables. Effect size analysis was performed using Cohen’s d method to characterize the size of the differences between the groups. Small, moderate, and large effects were defined as 0.20, 0.40, and 0.80, respectively [61,62]. ## 5. Conclusions Here, we demonstrated that while routine coagulation blood testing (d-dimer, free protein S and fibrinogen) could distinguish between COVID-19 patients and HCs, these tests were not able to distinguish between the three levels of clinical COVID-19 patients’ disease severity. However, significant changes in the EVs were found not only between healthy controls and patients but also between patient subgroups. The differences were found in several EV membrane antigens including CD41, EPCR, CD4, CD8, and CD14. These markers together with the EV IL-6 content, can serve as biomarkers for disease severity which may better reflect the disease dynamics. 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--- title: Essential Oil Composition Analysis, Antimicrobial Activities, and Biosystematic Studies on Six Species of Salvia authors: - Azize Demirpolat journal: Life year: 2023 pmcid: PMC10054517 doi: 10.3390/life13030634 license: CC BY 4.0 --- # Essential Oil Composition Analysis, Antimicrobial Activities, and Biosystematic Studies on Six Species of Salvia ## Abstract The essential oil constituents, antimicrobial properties, and biosystematic characteristics (morphological, palynological, and anatomical features) of six Salvia species from different regions of Turkey were investigated qualitatively and quantitatively in this study. The chemical composition of the essential oils of dried aerial parts of Salvia species, i.e., S. absconditiflora, S. ceratophylla, S. multicaulis, S. verbenaca, S. viridis, and S. syriaca were analyzed by GC-MS. The main constituents of the six Salvia species studied were 1,8-cineol, caryophyllene oxide, spathulenol, and borneol in different ratios. The antimicrobial activity of the essential oil extracted from the aerial parts of species of the genus Salvia was tested by the disc diffusion method. The essential oils of Salvia species showed different antimicrobial activity against the studied microorganisms. The highest antimicrobial activity against E. coli was observed in S. multicaulis and the highest antimicrobial activity against K. pneumoniae was observed in S. verbenaca. The morphology of the stem, leaf, bract, and flower structures of the Salvia species were analyzed in this study. Anatomical investigations focused on the root, petiole, and stem in more detail. Our research has broadened the criteria of anatomical characters unique to the Salvia species. Under light microscopy, the pollen grains of the six species belonging to Salvia were isopolar and radially symmetrical. The properties of the essential oil constituents, antimicrobial properties, and biosystematic data obtained in this study contribute to the bioactive and biosystematic studies of Salvia species used for food, pharmaceutical, and cosmetic purposes. ## 1. Introduction Salvia L. gets its name from the Latin word “Salvare”, which means “to heal or treat” [1]. Salvia belongs to the Salvinae subtribe, Lamiaceae family, Lamiales order of dicotyledonous. Salvia species have been identified in the group of commercial, medicinal, and aromatic herbs and are one of the various centers in Turkey, especially the Anatolia region [2]. Therefore, Turkey exhibits the greatest expansion of sage and is also one of the countries that widely consume it for commercial purposes [3]. Salvia is an important genus in the Lamiaceae family with approximately 1000 species worldwide, which contains many species producing secondary metabolites [4]. According to the most recent Flora of Turkey, there are more than 86 *Salvia taxa* in Turkey, while other studies indicate that it has increased to about 100 species [5]. Turkish Salvia species are discussed in seven sections, including Aethiopis, Drymosphace, Hymenosphace, Horminum, Hemisphace, Plethiosphace, and Salvia. In the current study, the divisions of the sections are as follows: S. absconditiflora (Montbret & Aucher ex Benth.) ( syn. Salvia cryptantha Montbret & Aucher ex Benth), S. multicaulis Vahl. in the Hymenosphace sectionss, S. syriaca L., S. verbenaca L., and S. ceratophylla L. in the Aethiopis section, and S. viridis L. in the Horminum section [2,6,7,8]. Molecular characterization studies carried out in recent years give important ideas about the systematics of species [9,10,11,12,13]. Genetic characterization studies among Salvia species have also revealed a large genetic variation among species. Similarly, flow cytometry and genome size determination studies have shown that genetic diversity is very rich among samples collected from different locations of the same species [4]. For thousands of years, the *Salvia genus* has been used in traditional medicine and is utilized in a broad variety of commercial and pharmaceutical goods, particularly in the production of essential or volatile oils and flavoring compounds, as well as in the food and cosmetics sectors. Essential oil components of Salvia species have an important place in the medicinal, aromatic plants market. Several studies have been conducted on the essential oil of this genus [14,15,16]. The chemical composition of Salvia L. was investigated by Gas Chromatography–Mass Spectrometry system with major compounds including caryophyllene oxide, spathulenol, α-copaene, germacrene D, and β-pinene [17]. Despite the fact that the majority of Salvia species are employed in traditional herbal medicine, studies have shown that they also exhibit anti-inflammatory, antibacterial, antioxidant, anticancer, and antidiabetic properties [12,14,15,18,19,20,21]. Additionally, these essential oils have been utilized to treat eczema, psoriasis, and asthma diseases [22]. S. absconditiflora species, represented in group C in the Flora of Turkey, is an endemic species. These endemic species have been researched and consumed as herbal tea in Turkey [23]. S. absconditiflora is thought to have a strong antioxidant effect because of its high phenolic and flavonoid content. Additionally, S. absconditiflora was said to have a strong cytotoxic effect on cancer cells [15]. Furthermore, S. syriaca is utilized in the food industry, the pharmacology and cosmetic industry, and it is also used to treat animals [24]. Moreover, S. ceratophylla is traditionally consumed to cure microbial infections, cancer, and urinary tract problems in Jordan [25,26]. However, some Salvia species have antimicrobial activity when extracted from above-ground soil [27,28]. Some Salvia species were compared with anatomical, morphological, and pollen features [29] and the findings showed that there were similarities and differences among the species. Thus, several of these important features, including the form of the calyx, corolla, and stamen, may be utilized to discriminate across infrageneric categories. Calyx and corolla shape, bract morphology and structure as well as inflorescence type are important diagnostic characteristics of taxonomic value regarding the six studied Salvia species, i.e., S. absconditiflora, S. ceratophylla, S. multicaulis, S. verbenaca, S. viridis, and S. syriaca. The morphology of the stem, leaf, bract, and flower structures of the Salvia species were analyzed in this study. Pollen characteristics of the family Lamiaceae have considerable taxonomic importance and the classification of genera in Labiatae has been revised [30,31], with Salvia placed within the subfamily Nepetoideae because it had hexacolpate pollen [29]. This study aimed to contribute to both the systematics and bioactivity of the genus by investigating the qualitative and quantitative characteristics of some biosystematic features (morphological, palynological, and anatomical features) as well as the essential oil constituents and antimicrobial properties of six Salvia plants collected from different regions of Turkey. ## 2.1. Plant Material Plant samples were collected from the locations indicated in Table 1. All plants were collected during the flowering period and in the morning hours [32]. For essential oil studies, approximately 200 g of plant samples were dried in a place out of the sun. For anatomical studies, the plants were stored in $70\%$ alcohol in the area where they were collected. For morphological and palynological examinations, 20 plant samples were selected from each taxon; the samples were dried and kept as herbarium specimens at Bingol University. ## 2.2. Isolation of Essential Oils and GC-MS Analysis The plants used in this research were air-dried. The oil from the plants was extracted using the hydrodistillation technique. Using Clevenger equipment, three hours of hydrodistillation were performed on the 100 g of air-dried aerial plant materials. The organic layer in the gathering vial was transferred into the GC/GC-MS equipment once the distillation process was accomplished. The GC-MS was used to examine the essential oil. The instrument was an HP 6890 model. The mass range was between 40 and 330 m/z, and the ionization energy was 70 eV. A column HP-5 MS (30 m 0.25 mm i.d., film thickness 0.25 m) capillary column with a column flow rate (transporter gas helium) was implemented. Helium is used as the carrier gas, with a steady column flow rate of 1 mL/min. The settings for the Column Oven Temperature procedure were 40 °C and a hold time of 2 min at a temperature of 3 °C/min. 240 °C was the final degree. The flow rate was set to 1 L, and the split mode was chosen (split ratio 1:10 or 1:100). A 3.5 min buffer hold was applied to hexane samples. The mass spectrometric settings were full scan mode, 20,000 amu/s scan speed, and 50 spectra per sample frequency. Temperatures at the contact and ion source were 250 °C and 200 °C, etc. Alkanes were used as standards to compute the retention indices (RI). By comparing the retention times (RT), mass spectra, and RI of the essential oils to those described in the literature (NIST 20 and Wiley Libraries) and MS libraries (Wiley), the chemical components of the essential oils were identified. Traditional library searches just compare spectra rather than taking retention parameters into account. In this study, libraries were searched using a combination of storage indexes, which made compound identification simpler and more accurate. The device’s retention index spectrum libraries were also utilized in this study. The same analytical procedure as the identical column provided in the library was applied for better results. Table 2 details the essential oil constituents that have been identified. ## 2.3. PCA (Principal Component Analysis) Multivariate analysis was performed to determine the structure of variability and to calculate differences between groups. Complete data sets were used for these analyses. To determine the commonalities between the measurement units, the UPGMA (unweighted pair-group average linkage) clustering approach based on Pearson distances was used (Figure 1). The chemical components of the essential oils of the Salvia species were considered as variables. The chemical components of the different samples were evaluated using cluster analysis (CA) and principal component analysis (PCA). The same weight was given to the non-standardized statistics as previously reported. ## 2.4. Antimicrobial Investigations The disk diffusion technique was used to test the plant essential oil’s antibacterial activity [36]. Yeast strains (Candida albicans and Candida glabrata) were cultured in malt extract broth for 48 h at 25 ± 1 °C, whereas bacteria strains (Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Bacillus megaterium) were incubated in nutrient broth for 24 h at 35 ± 1 °C. At a rate of $1\%$, the bacteria and yeast cultures made in broth were added to Mueller Hinton Agar and Plate Count Agar, respectively (106 bacteria mL, 104 yeast mL, 104 fungi mL−1). 25 cc of the cultures were added to sterile 9 cm diameter petri plates after being well shaken. The medium’s homogeneous dispersion was accomplished. On the solidified agar medium, antimicrobial discs with a 6 mm diameter that were each impregnated with 100 μL of essential oil were lightly positioned. The plates infected with bacteria were incubated at 37 ± 0.1 °C for 24 h and the plates inoculated with yeast were incubated at 25 ± 0.1 °C for 72 h after being kept the petri dishes generated in this manner at 4 °C for 1.5 to 2 h. Different standard discs were used as controls for yeasts (Nystatin 100 mg/disc) and bacteria (Streptomycin sulfate 10 mg/disc). Inhibitory zones were measured in millimeters (Figure 2). ## 2.5. Morphological Investigations The taxonomic characters of the Salvia species were prepared in 20 samples according to Flora of Turkey and some significant articles [2,5,6]. The morphological and morphometrical characters are presented in the result section. Morphological measurements were taken with calipers. All of the morphological measurements were performed using Hierarchical clustering analysis using SPSS software version 21, and the resulting dendrogram was shown. ## 2.6. Anatomical Investigations Anatomical investigations were conducted using an average of twenty specimens unbroken in $70\%$ alcohol. The cross-sections of stem, root, and petiole organs were cut with a razor, and sections were stained with Alcian blue for cellulose substances and safranine O for polymer substances within the quantitative relation of 3:2. For staining, the sections were placed in the ready dye for five minutes [37,38]. Furthermore, sections were examined and measured using a Euromex CMEX-10 PRO light microscope. ## 2.7. Palynological Investigations Pollens were generated using the Ertman technique, using samples from the light microscopy [30]. A few changes were made to the acetolysis procedure after then. Plant matter was cursed for one to two minutes using a glass rod and one to two drops of acetic acid in the slide. A needle was used to clear the particles off the slide. A coverslip was placed over the slide after applying a drop of glycerin jelly. Each specimen received 4–5 prepared slides in total. Polar axis (P), equatorial axis (E), colpus length (Clg), colpus width (Clt), exine thickness (Ex), and aperture width (Ap) were measured from at least 20 completely evolved grains according to the pattern beneath a Euromex CMEX-10 PRO light microscope (100×). These measurements are reported in Table 3, and micrographs in Figure 3. The terminology used is mainly from Faegri & Iversen, Ertman, and the study of Kılıç et al. [ 39,40,41]. For scanning electron microscopy (SEM) Salvia species pollen slides were prepared using the techniques of Majeed et al. [ 42]. Pollen was acetolyzed before being suspended in $90\%$ ethanol for SEM. They were then placed on metallic stubs that had been gold-palladium coated. Pollen electron micrographs are taken with an SEM (Model JEOL JSM5910). Results from pollen SEM are summarized in Figure 4. All of the pollen measurements were performed using Hierarchical clustering analysis performed using SPSS software version 21 and the resulting dendrogram was shown in Figure 5 and Figure 6. ## 3.1. Essential Oil Components Qualitative and quantitative differences were found in the essential oil analysis of the six Salvia species the essential oils of S. absconditiflora, and S. ceratophylla 29, and 28 components were identified representing $100\%$ and $98.62\%$ of the oils, respectively. The aerial part of S. absconditiflora and S. ceratophylla were hydrodistilled, obtaining yields of $0.97\%$ and $0.75\%$ (w/w) of yellowish oils, respectively. The aerial parts of the S. multicaulis and S. verbenaca were hydrodistilled, obtaining yields of $0.97\%$ and $0.95\%$ (w/w) of yellowish oils, respectively. In the essential oils of this species, 27 and 25 components were identified representing $92.60\%$ and $94.26\%$ of the oils, respectively. S. viridis has 30 components (0.78 w/w). The essential oils of S.viridis have 29 components and S. syriaca was identified with 31 components. Additionally, this species was representing $91.54\%$ and $91.02\%$ of the oils, respectively. The major compounds were 1,8-cineol ($17.94\%$), borneol ($10.40\%$), caryophyllene oxide ($10.14\%$), spathulenol ($9.09\%$), and caryophyllene ($8.45\%$) in S. absconditiflora; spathulenol ($20.13\%$), caryophyllene oxide ($14.68\%$), 1,8-cineol ($12.98\%$), and caryophyllene ($8.36\%$) in S. ceratophylla; spathulenol ($18.10\%$), caryophyllene oxide ($17.20\%$), 1,8-cineol ($11.99\%$), bicyclogermacrene ($5.89\%$), borneol ($5.74\%$), and caryophyllene ($8.51\%$) in S. multicaulis; caryophyllene oxide ($16.15\%$), spathulenol ($13.18\%$), 1,8-cineol ($11.45\%$), bicyclogermacrene ($11.03\%$), and borneol ($11.00\%$) in S. verbeneca; caryophyllene oxide ($16.18\%$), caryophyllene ($15.01\%$), 1,8-cineol ($14.06\%$), spathulenol ($11.42\%$), β-pinene ($7.21\%$), and borneol ($7.02\%$) in S. viridis; caryophyllene oxide ($17.54\%$), spathulenol ($9.35\%$), borneol ($9.65\%$), bicyclogermacrene ($6.93\%$), and 1,5-epoxysalvial-4[14]-ene ($6.83\%$) in S. syriaca. The compositions of six of the Salvia essential oils are listed in Table 2. Based on other research that has been published, multivariate analysis was employed [43]. The chemicals for the various samples were identified using principal component analysis (PCA) and cluster analysis (CA). The PCA was then carried out using the matrix correlation setup and Varimax rotation. PC1 ($48.13\%$) and PC2 ($10.04\%$) were the primary components in the principal component analysis. The total load of PC1 and PC2 was $58.17\%$. The Kaiser-Meyer-Olkin (KMO) approach was used to investigate the correlation of the variables. KMO was 0.613, which is considered satisfactory. Barlett’s test of sphericity indicated statistical significance at alpha 0.06 for the data set. PCA analysis was explained in two ways, which revealed the link between the six Salvia species and their essential oil concentration (Figure 1). ## 3.2. Antimicrobial Activity Studies In this step of the study, the antimicrobial activity of the essential oil obtained from the above-ground parts of six species belonging to the genus Salvia was tested by the disc diffusion method. Antimicrobial activity was tested against E. coli, K. pneumoniae, B. megaterium, S. aureus bacteria, C. albicans, and C. glabrata yeasts. Streptomycin sulphate 10 µg/disc for bacteria and Nystatin 100 µg/disc for yeasts were used as controls. Essential oils of Salvia species showed varying antimicrobial activity against the microorganisms studied. The highest antimicrobial effect against E. coli was observed in S. multicaulis (25 mm), while the lowest antimicrobial effect was observed in S. absconditiflora (19 mm). The highest antimicrobial effect against K. pneumoniae was observed in S. verbenaca (25 mm), while the lowest antimicrobial effect was observed in S. syriaca (13 mm). The highest antimicrobial effect against B. megaterium was observed in S. multicaulis (28 mm), while the lowest antimicrobial effect was observed in S. absconditiflora (22 mm). The highest antimicrobial effect against S. aureus was observed in S. ceratophylla (22 mm), while the lowest antimicrobial effect was observed in S. viridis (10 mm). The highest antimicrobial effect against C. albicans was observed in S. verbenaca (28 mm), while the lowest antimicrobial effect was observed in S. syriaca (15 mm). The highest antimicrobial effect against C. glabrata was observed in S. multicaulis (25 mm), while the lowest antimicrobial effect was observed in S. syriaca (10 mm). According to these results, S. multicaulis and S. verbenaca species had the strongest antimicrobial activity, while S. absconditiflora and S. syriaca had the lowest activity. The antimicrobial activity of the plant samples against the test microorganisms is shown graphically in Figure 2. ## 3.3. Morphology Properties Morphological observations and measurements of the studied Salvia species were made from herbarium specimens. Stem lengths, leaf measurements and characters, calyx and corolla characteristics and measurements, petiole measurements, inflorescence types, and hair conditions of the studied six Salvia species were determined. The endemic species S. absconditiflora was a perennial herb with elliptical cordate leaves, whose habitats were roadsides, uncultivated fields, slopes, and rocky limestone. The habitat of S. ceratophylla is mud and inactive, limestone rocky areas. The stem of this biennial species is erect and strong and has dense glandular hairs. The two perennial species S. multicaulis and S. verbenaca are very similar to each other (Figure 7), but differ in that S. verbenaca is densely hairy. S. multicaulis have hair on the body pilose to villous, rarely glabrous, sometimes dendroid hairy. S. viridis was an annual plant and its habitats were rocky slopes. S. syriaca was a perennial herb, rhizomatous. The stem was upright branches, and glandular feathers are quite dense. Descriptions of morphological and morphometric characters are described in Table 4, Figure 7 on the six Salvia species. All of the morphological measurements were performed using hierarchical clustering analysis and the resulting dendrogram was shown in Figure 7. Two large clusters were formed as a result of clustering analysis. S. absconditiflora, S. multicaulis, and S. verbenaca species are located on one side of the cluster (Figure 7). S. multicaulis, which is in the outermost clade, and S. absconditiflora, which is the closest to it, are species located in the same section in the Flora of Turkey [6] and can be distinguished morphologically by their leaf sizes and the color status of the calyx. The cluster tree in this study confirms these results in terms of morphology in Figure 8. ## 3.4. Anatomical Properties The stem epidermis of S. absconditiflora has a layer of collenchyma embedded in the cortex, usually below a single-layered epidermis. In section through the stem, the pith covered a large area. In the stem cross-section, most of the cells in the periderm were crushed. Xylem rails were obvious. In the cross-section of the petiole of S. absconditiflora, there were two areas named abaxial surface and adaxial surface. The adaxial surface has a convex shape. A cuticle surrounded the petiole. A single row of rectangular and oval cells made up the epidermis. The epidermis was covered with trichomes. The stem of S. ceratophylla have located single-layered and made up of cells with an oval-oblong shape. Sclerenchymatic cells consisted of 3–7 layers and were usually stained red color on sections. The root of S. ceratophylla a periderm located at the outermost part was dark-colored. Most of the periderm was crushed and its cell structure was disrupted. In the petiole’s cross-section of this species, the adaxial surface was convex. The stem epidermis of S. multicaulis has a single-layered epidermis and is made up of cells that were typically oval-oblong and sometimes square-like in shape. The stem epidermis of S. verbenaca consisted of oval-oblong, sometimes square-like cells and was single-layered. There was a layer of collenchyma in the cortex under the epidermis in certain spots, and both adaxial and abaxial surfaces were convex and twisted in a petiole cross-section. The stem epidermis of S. viridis and S. syriaca were single-layered and consisted of mostly ovoidal rectangular. When we took a cross-section of the petiole S. viridis, the epidermis consisted of a single row of rectangular and oval cells. The epidermis was covered with trichomes. The petiole’s cross-section of S. syriaca has an abaxial surface and the adaxial surface were procumbent and D-shaped. Petiole was covered with a cuticle. The epidermis consisted of a single row of rectangular and oval cells. The epidermis was covered with trichomes. Descriptions of anatomical characters are expanded with the detailed investigations on six Salvia species in Table 5 and Figure 8 and Figure 9. ## 3.5. Palynological Properties All morphological parameters determined have been shown in Table 3 and Figure 3, Figure 4, Figure 5 and Figure 6. Under LM, the pollen grains of the 6 belonging to Salvia were isopolar and radially symmetrical. The pollen was symmetrical relative to the equatorial diameter. Pollen grains of all Salvia species found in this study were hexacolpat and also reticulated ornamentation was observed. The polar axis (P) ranged from 34.2 ± (0.6) μm to 57.2 ± (2.7) μm and the equatorial axis (E) ranged from 29.2 ± (1.2) to 55.3 ± (1.2) μm. The polar axis was longest in S. multicaulis 57.2 ± (2.7) μm and shortest in S. verbenaca 34.2 ± (0.6) μm (Figure 4). The equatorial axis was longest in S. multicaulis 55.3 ± (1.2) μm and shortest in S. verbenaca 29.2 ± (1.2) μm. Clt ratios of all Salvia species examined were similar. Exine thickness ranged from 1.2 to 1.9 ± ($\frac{0.6}{0.2}$) μm. Colpus length varied from 23.2 ± (0.9) μm in S. verbenaca to 38.6 ± (3.10) μm in S. multicaulis. Colpus width varied from 2.5 ± (1–2) μm in S. verbenaca to 6.4 ± (0.9) μm in S. multicaulis (Table 3). The length of the colpus and the length of the polar axis are linked in a controlled manner (Figure 3). S. absconditiflora, S. ceratophylla, and S. viridis species are closest to each other in cluster analysis in Figure 4. S. multicaulis species is the most in the outermost clade. A P/E ratio of 1.03 prolate-spheroidal has the largest pollen in this study. This cluster analysis has been carried out correctly to provide this data. ## 4. Discussion The essential oil constituents and antimicrobial properties as well as some biosystematic characteristics (morphological, palynological, and anatomical features) of Salvia samples from different regions of Turkey were studied qualitatively and quantitatively. In morphological examinations, calyx and corolla shape, bract structure, and inflorescence status are important characters in determining the species included in the six Salvia species. No new characters other than those described in the literature concerning the morphological traits of the species that served as the focus of this study were discovered. It was observed that the morphological measurement values of the samples belonging to the Salvia species were in great agreement with the findings of the literature [6], as well as some deviations in the minimum and maximum limits of the measurement values. For example, when morphologically examined, the bracts and leaves of the S. viridis species were measured smaller than the Flora of Turkey [6] in this study. S. multicaulis stem length was measured as smaller and leaves were larger in this study when compared to the Flora of Turkey. The species we collected were taken from a higher altitude compared to the Flora of Turkey. These differences are also observed in Figure 4 and the morphological distinction of the species from each other is indicated in the cluster analysis. When the morphological measurements were compared with the literature, the reason for these differences can be attributed to the difference in the number of samples examined and the place and time of collection. Baran reported that leaf size was 1.2–6 × 0.6–2.8 cm and the corolla size was 0.9–1.5 cm in *Salvia viridis* [44]. The findings obtained in this study showed that the leaves were 1.5–2.5 × 1–3 cm in size and simple, oblong-ovate; corolla size 8–10 mm. The result of this study is important regarding the usability of 1,8-cineol, caryophyllene oxide, spathulenol, and borneol, which are the major components of Salvia species. In a study, γ-muurolene ($11.4\%$) and α-pinene ($7.6\%$) were determined as the main compounds in S. ceratophylla essential oil [45]. According to the results of this study, no γ-muurolene compound was found in S. ceratophylla, while the α-pinene ratio was determined as ($3.76\%$). As a result of essential oil component analyses of S. multicaulis samples carried out by different researchers, different components were reported [46,47,48]. The essential oil obtained from the flowering shoots of S. multicaulis was found to be very valuable. The main components of this essential oil were reported to be bornyl acetate, β-caryophyllene, α-pinene, camphor, α-copaene, myrtenol, sabinyl acetate, 1,8-cineole, limonene, borneol [48,49,50]. In this study, the major components found in the essential oil obtained from S. multicaulis were spathulenol ($18.10\%$), caryophyllene oxide ($17.20\%$), 1,8-cineol ($11.99\%$), bicyclogermacrene ($5.89\%$), borneol ($5.74\%$), and caryophyllene ($8.51\%$). In a previous study, the major constituents of the essential oil of S. cryptantha S. absconditiflora, collected from different locations, were 1,8-cineole ($21\%$), camphor ($19.1\%$), α-pinene ($12.5\%$), and camphene ($8.7\%$), while S. syriaca contained spathulenol ($24.96\%$), borneol ($12.73\%$), camphene ($9.95\%$), and caryophyllene oxide ($8.7\%$) [23,51]. It is thought that ecological, climatic, plant collection periods and methodological differences are effective in different results in different areas. In this study, although the basic components were similar, their amounts varied. In this study, 1,8-cineole, which is highly present in Salvia essential oils, is used as a component of many medicines such as antiseptics, nasal sprays, mouthwashes, cough syrups, medicated lozenges, and as an additive in personal care products such as toothpaste and aromatherapy oils. Due to the pleasant flavor and aroma of the compound, it is used as a sweetener in products such as confectionery, pastry, bakery products, beverages, and meat products [52]. In a study, the efficacy of 1,8-cineole on the antimicrobial effect against some microorganisms was investigated. As a result of the study, it was concluded that the use of 1,8-cineole in combination with chlorhexidine may facilitate the elimination of some resistant bacteria by increasing antimicrobial activity [53]. The primary sesquiterpene in hops, caryophyllene, or its derivatives, are used in soaps and scents for cosmetic purposes [54]. Hops’ modest sedative effects in herbal medicine are caused by the compound caryophyllene. Furthermore, investigations conducted in vitro showed that caryophyllene has lethal effects on breast cancer cells [55]. The caryophyllene oxide levels in this research showed that as follows; S. absconditiflora $10.14\%$, S. ceratophylla $14.68\%$, S. multicaulis $17.20\%$, S. verbenaca $16.15\%$, S. viridis $16.18\%$, and S. syriaca $17.54\%$ (Table 2). The detailed oil composition characterization carried out in this study revealed the presence of various valuable compounds in the chosen Salvia species demonstrating their applicability for medicinal and pharmaceutical purposes as well as in the cosmetic beverages industry. Spathulenol, which was determined as the major compound in the study, is a sesquiterpene component found in essential oils. It has been reported to play a major role in antimicrobial, antiproliferative, anti-inflammatory, and immunomodulatory activities [56,57]. It was also found to have a repellent effect against mosquito species [58]. According to the results of this study, all studied species showed high amounts of spathulenol. Borneol, the other major component, is a colthisless, crystalline monoterpene occurring in essential oils. Borneol has been proven to have antibacterial, antifungal, antispasmodic, choleretic, and sedative effects [59,60]. Recent studies have shown that the blood-brain barrier improves drug delivery and increases efficacy [61]. At the same time, it was determined that borneol showed antiapoptotic, antioxidative, and neuroprotective effects in human neuroblastoma cells [62]. The biochemical contents of Salvia species, the solvents used and the differences of microorganisms affect the antimicrobial results. This study reveals that the antimicrobial effect of Salvia essential oils is very important. In a previous study, the ethanol extract of the species S. absconditiflora (S. cryptantha) was tested by the disk diffusion method. As a result of the study, the antimicrobial effect of the plant extracts against “gram+” bacteria was found, while the same effect against “gram-” bacteria and C. albicans yeast was not found [63]. In this study, the essential oil of S. absconditiflora was effective against both “gram+” and “gram-” bacteria. In an antimicrobial study of S. ceratophylla extract, it was observed that it showed a strong antimicrobial effect [64]. Previous studies reported that the essential oils of S. multicaulis were effective against S. aureus, K. pneumoniae, E. coli, and *Streptococcus mutants* [65]. In another study, the essential oils of S. multicaulis were found to be effective against Bacillus sp., Enterococcus sp., Staphylococcus sp., and *Saccharomyces cerevisiae* [66,67]. In another study, disc diffusion of the essential oil of S. verbenaca species showed antimicrobial activity against Bacillus sp. and Staphylococcus sp. [ 68]. The essential oils obtained in this study were included in antimicrobial activity studies by the disk diffusion method. This is the first study on the antimicrobial activity of S. absconditiflora, S. ceratophylla, and S. viridis species using this method. In the present study, it was determined that the six Salvia species could be considered as a natural antimicrobial source against the tested microorganisms. In an anatomical study on S. forskaohlei L., it was determined that there was a sclerenchymatous ring with sclerenchyma clusters under the parenchymatic cortex cells in the root of S. forskaohlei [69]. Çobanoğlu mentioned these sclerenchyma clusters in the root cortex of the species in his study on S. palestina Bentham [70]. These findings showed that, in anatomical examinations, sclerenchyma clusters in the root cortex of the species were found in S. ceratophylla and S. multicaulis species and not in other species. Metcalfe and Chalk [71] stated that the typical feature of the family is the presence of a well-developed collenchyma tissue at the corners of the stem. Thickening of the collenchyma tissue was observed and photographed in the examined Salvia species. Kahraman reported that S. absconditiflora, S. viridis, S. ceratophylla, S. syriaca, and S. viridis, had a very large cortex and the epidermis consisting of a single subcaste of nearly rectangular, square, or round cells [72]. In this study, a large cortex was observed in the stem sections of the species. In addition, the shape of the epidermis was observed in the cross-sections of the stem in this study, usually ovoidal rectangular and sometimes square. In his study, Kahraman was able to categorize the petiole anatomy of Salvia species in a cross-section into seven types. He reported that U-shaped with obtuse or erect margins (S. viridis), D-shaped with more or less procumbent margins (S. syriaca), triangular (S. absconditiflora, S. multicaulis) or open crescent-shaped. Özler et al. pronounced that the Salvia section’s pollen suboblate to subprolate and aperture circumstance is hexacolpate and octacolpate [73]. In another study, Özler et al. pronounced that the S. multicaulis pollen grain is prolate spheroidal. In this study of the Hymenosphace section, S. absconditiflora pollen grain is prolate spheroidal, and S. multicaulis pollen grain is suboblate [73,74]. The findings obtained in this study showed that S. syriaca, S. verbenaca, and S. ceratophylla in the Aethiopis section species pollen are subprolate, subprolate, and suboblate, respectively. Kiliç reported that S. syriaca pollen is suboblate [75]. Moon et al. [ 76] reported bireticulate ornamentation in pollen of the Aethiopis section, and another study discovered that S. syriaca was characterized by reticulate-perforate [73,74]. In this study, the S. viridis pollen grain in the Horminum section is oblate-spheroidal. When this study is evaluated regarding palynological results, it was concluded that pollen morphology characteristics of species were generally similar to each other. Pollen morphological characteristics were not distinguishable in taxonomy in the identification of Salvia species observed in this study since there was no discernible variation in the palynological characteristics of the taxa analyzed. This view is supported by some other studies [73,74,75,76]. ## 5. Conclusions The chemotaxonomic study showed that the essential oil of Salvia species varies slightly depending on ecological, climatic, plant collection periods, and location. However, it is also a fact that the amounts of major common constituents in Salvia species vary depending on the species of the species. In other words, the fact that the constituents in Salvia species are generally similar, without the effect of harvest time and locality, makes it possible to standardize the essential oils of Salvia species. The detailed characterization of oil composition carried out in this study has revealed the existence of various valuable compounds in the selected Salvia species, demonstrating their applicability for medicinal and pharmaceutical purposes as well as in the cosmetic and beverage industries. According to the experimental results, it was found to have antimicrobial activity against all tested microorganisms at certain rates. It is believed that the strong antimicrobial effect is due to these valuable chemical components. 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--- title: Association of Heart Rate Variability with Obstructive Sleep Apnea in Adults authors: - Yen-Chang Lin - Jui-Kun Chiang - Chih-Ming Lu - Yee-Hsin Kao journal: Medicina year: 2023 pmcid: PMC10054532 doi: 10.3390/medicina59030471 license: CC BY 4.0 --- # Association of Heart Rate Variability with Obstructive Sleep Apnea in Adults ## Abstract Background and Objectives: Heart rate variability (HRV) analysis is a noninvasive method used to examine autonomic system function, and the clinical applications of HRV analysis have been well documented. The aim of this study is to investigate the association between HRV and the apnea–hypopnea index (AHI) in patients referred for polysomnography (PSG) for obstructive sleep apnea (OSA) diagnosis. Materials and Methods: Patients underwent whole-night PSG. Data on nocturnal HRV and AHI were analyzed. We determined the correlation of time- and frequency-domain parameters of HRV with the AHI. Results: A total of 62 participants (50 men and 12 women) were enrolled. The mean age, body mass index (BMI), neck circumference, and AHI score of the patients were 44.4 ± 11.5 years, 28.7 ± 5.2, 40.2 ± 4.8 cm, and 32.1 ± 27.0, respectively. The log root mean square of successive differences between normal heartbeats (RMSSD) were negatively correlated with BMI ($$p \leq 0.034$$) and neck circumference ($$p \leq 0.003$$). The log absolute power of the low-frequency band over high-frequency band (LF/HF) ratio was positively correlated with the AHI ($$p \leq 0.006$$). A higher log LF/HF power ratio (β = 5.01, $$p \leq 0.029$$) and BMI (β = 2.20, $p \leq 0.001$) were associated with a higher AHI value in multiple linear regression analysis. Conclusions: A higher log LF/HF power ratio and BMI were positively and significantly associated with the AHI during whole-night PSG in adult patients. ## 1. Introduction Sleep occupies almost one-third of our lives. The American Academy of Sleep Medicine and the Sleep Research Society recommend ≥7 h of sleep per night for adults to ensure optimal health [1]. Sleep is a highly complex phenomenon regulated partly by the autonomic nervous system. Both short and long sleep durations and sleep disorders, mainly OSA, adversely affect cardiovascular and metabolic disorders [2]. OSA is a severe sleep disorder that may deteriorate the quality of life and lead to hypertension and cardiovascular and cerebrovascular diseases [3]. The OSA severity is evaluated based on the AHI determined through PSG. AHI, by definition, is the sum of the numbers of “apnea” and “hypopnea” events per hour during sleep. As for “apnea” and “hypopnea”, respectively, the former is delimited by cessation of airflow for at least 10 s, while the latter by reduction in airflow by at least $30\%$ for at least 10 s with decrease in oxygen saturation. AHI values of 5–15, 15–30, and >30 with associated symptoms (e.g., excessive daytime sleepiness, fatigue, impaired cognition, or a spouse’s report of disruptive snoring) indicate mild, moderate, and severe OSA, respectively [4]; or OSA is defined as an AHI ≥ 15, regardless of the associated symptoms [5]. Meta-analyses have reported that OSA is associated with diabetes mellitus [6], stroke [7], total cardiovascular diseases [7], and all-cause mortality [8]. Autonomic dysfunction is associated with various pathological conditions [9], including hyperglycemia, high blood pressure, high triglyceride levels, low high-density lipoprotein cholesterol levels, high BMI, incident diabetes, cardiovascular disease (CVD), and high mortality [10,11,12]. Three tests, namely the RR variation, Valsalva maneuver, and postural blood pressure testing, have been recommended for the longitudinal testing of the cardiovascular autonomic system since 1992 [13]. HRV analysis is a noninvasive method to examine autonomic system function. One meta-analysis reported that lower HRV was associated with a $46\%$ higher risk of cardiovascular events, which was significant for patients with acute myocardial infarction, and a $112\%$ higher risk of all-cause death [14]. Another meta-analysis demonstrated that lower HRV was associated with a 32–$45\%$ increased risk of a first cardiovascular event in individuals without known CVD [15]. Studies have reported the association of HRV with higher hemoglobin A1C (HbA1c) levels in young adults with diabetes and patients with diabetic autonomic neuropathy [16]. HRV analysis has been the most commonly used to monitor autonomic changes during sleep, and HRV was associated with OSA [17,18]. Ischemic cardiovascular events in OSA have multifactorial etiology, including high sympathetic activity, endothelial dysfunction, inflammation, and oxidative stress [18,19,20,21], with the primary contributor being sympathetic overactivity [22]. The sympathetic activity was synchronized with the repetitive episodes of apnea occurring continuously throughout the sleep of patients with OSA [21]. One study reported that using HRV analysis in OSA provides insights into cardiac autonomic control across sleep stages [18]. Another systemic review reported that adults with OSA had higher sympathetic components and lower parasympathetic tone [23]. However, the parasympathetic tone, RMSSD, was not significantly lower in adults with OSA in some previous studies [23]. Because snoring and sleep apnea were found during sleeping in the night, the association between HRV and OSA might be better investigated during sleep. The aim of this study was to investigate the association between HRV and OSA severity by considering frequency and time domains during whole-night PSG. ## 2.1. Ethical Considerations The study protocol was reviewed and approved by the institutional review board of the Tainan Municipal Hospital (Managed by Show Chwan Medical Care Corporation) (SCMH_IRB No: 1090508) and the Research Ethics Committee of the Buddhist Dalin Tzu Chi Hospital, Taiwan (No. B10901020). ## 2.2.1. Data Collection from PSG Patients underwent PSG (EMBLA N7000 system, Embla Inc., Broomfield, CO, USA). We examined electrophysiological signals for heart activity analysis, pulse oximetry readings, and airflow by using nasal pressure and oronasal thermal sensors, body position, actigraphy data, and thoracic and abdominal movements [24]. ## 2.2.2. HRV Measurement Time- and frequency-domain analyses were performed to evaluate HRV. The time-domain measurement indices included the standard deviation of normal-to-normal (NN) intervals (SDNN), the standard deviation of average NN intervals for each 5-min segment of an HRV recording (SDANN), percentage of successive RR intervals that differ by >50 ms (pNN50), baseline width of the RR interval histogram (TINN), the standard deviation of successive RR interval differences (SDSD), and the root mean square of successive differences (RMSSD). The RMSSD was converted by logarithmic transformation (log RMSSD), as suggested by Nakamura et al. ( Nakamura et al., 2015). Both the RMSSD and log RMSSD are the recognized markers of parasympathetic activity [25]. Frequency-domain analysis was performed in a 1024 sample (8.5 min) window by using the fast Fourier transform applied to three overlapping 512 sample sub-windows within the 1024 coherence windows. For each time segment, the algorithm estimated the power spectral density. The spectrum resulted from the sampling and Hamming windows. The power spectrum was quantified by integrating it into frequency-domain indices with a high-frequency (HF) power (0.15–0.4 Hz), low-frequency (LF) power (0.04–0.15 Hz), and the ratio of LF power to HF power (log LF/HF ratio). ## 2.3.1. Data Design and Setting We recruited 62 (50 men and 12 women) consecutive participants referred to the sleep unit of a southern teaching hospital in Taiwan for clinically suspected OSA after excluding 5 individuals who failed to meet the inclusion criteria of this current program. Most patients were referred from ENT and the internal medical department in the same hospital from July 2020 to June 2021. The inclusion criteria were patients who received PSG due to snoring or the severity of OSA. We excluded the subjects with severe cardiovascular disorders, severe neuromuscular disorders, previous surgery for snoring and sleep apnea, or taking medications that affect the sympathetic nervous system (e.g., beta-blockers, alpha-blockers, and centrally acting drugs). We obtained informed consent from all patients prior to their enrollment in the study. ## 2.3.2. Study Outcome Heart rate variability analyses including time- and frequency-domain measurements from PSG, and demographic factors were collected to evaluate the independent factors associated with the apnea–hypopnea index as the measures of OSA severity. Since the American Academy of Sleep Medicine has long established a threshold of 5 events of apnea/hypopnea per hour with OSA symptoms (unintentional sleep episodes during wakefulness; daytime sleepiness; unrefreshing sleep; fatigue; insomnia; waking up breath-holding, gasping, or choking; or the bed partner describing loud snoring, breathing interruptions, or both during the patient’s sleep) or 15 events per hour (with or without OSA symptoms) as criterion for OSA cases [4], we would set the cutoff of AHI ≥ 15 events/h as the criteria for the OSA cases in our current study regardless of the associated symptoms. ## 2.4. Statistical Analysis The PSG could record several channels of data including the electroencephalogram, electrooculogram, and electrocardiogram. Electrocardiogram data were downloaded, Hilbert transformed and analyzed using R with the ebm, seewave, pracma and RHRV packages. Data files were visually inspected for artifacts, and corrections were made manually or by using the software if necessary. Some HRV indices were naturally logarithmically transformed to reduce the skewness of data distribution [26]. Pearson’s correlation (r) was calculated to determine the relationship between two continuous variables. The correlation was considered to be strong if r > 0.5, moderate if $r = 0.3$–0.5, and weak if $r = 0.1$–0.3 [27]. Multiple linear regression analysis was performed to analyze the association between HRV indices and the AHI after adjustment for covariates [28]. All factors listed in Table 1 and Table 2 were included during the regression analysis. Data entry and analysis were performed using the free R software, version 4.0.3 (R Foundation for Statistical Computing, Vienna, Australia). All statistical assessments were two-sided, and statistical significance was set at the 0.05 level. ## 3. Results A total of 62 participants (50 men and 12 women) referred for PSG were enrolled in this study, and the mean recording time of PSG was 6.9 ± 0.3 h. The mean age, BMI, neck circumference, and AHI score of the patients were 44.4 ± 11.5 years, 28.7 ± 5.2, 40.2 ± 4.8 cm, and 32.1 ± 27.0, respectively. Thirty-nine patients ($62.9\%$) were classified as OSA with AHI ≥ 15. Additionally, neck circumference, hypoxemia index and arousal index were all significantly higher in the AHI ≥ 15 group than the AHI < 15 group (41.2 ± 5.1 cm vs. 38.5 ± 3.8 cm, $$p \leq 0.016$$; 12.5 ± 9.7/hour vs. 5.0 ± 2.5/hour, $$p \leq 0.004$$; 25.2 ± 14.9/hour vs. 10.4 ± 3.8/hour, $p \leq 0.001$, respectively) (Table 1). The HRV data handling and analysis is shown in Figure 1. As shown in Table 2, the mean log SDNN was 4.8 ± 0.5 log (ms) and negatively correlated with BMI ($$p \leq 0.036$$) and neck circumference ($$p \leq 0.014$$). The mean log RMSSD was 4.5 ± 0.6 log (ms) and negatively correlated with BMI ($$p \leq 0.034$$) and neck circumference ($$p \leq 0.003$$). The log LF/HF ratio was 0.1 ± 0.5 and was positively correlated with AHI ($$p \leq 0.006$$; Figure 2), neck circumference ($$p \leq 0.040$$) and hypoxemia index ($$p \leq 0.031$$) (Table 2). The log RMSSD values were negatively correlated with AHI; however, this correlation was nonsignificant ($$p \leq 0.191$$; Figure 3). Notably, AHI was positively correlated with arousal index ($r = 0.70$, $p \leq 0.001$) and hypoxemia index ($r = 0.41$, $$p \leq 0.001$$). The collinearity was also checked for variables selection. The results of the multiple linear regression analysis revealed that a higher log ratio of LF/HF power (β = 15.01, $$p \leq 0.029$$) and BMI (β = 2.20, $p \leq 0.001$) were associated with a higher AHI value (Table 3). The R2 value for this final model was 0.314. To better illustrate the effect of arousals and their associated sympathetic activation on heart rate variability, we further yield a model of the multiple linear regression analysis showing that only hypoxemia index (β = 0.019, $$p \leq 0.032$$) but not AHI (β = 0.005, $$p \leq 0.151$$) or arousal index (β = −0.003, $$p \leq 0.662$$) was significantly correlated with higher log ratio of LF/HF power. ## 4. Discussion A higher log value indicates a higher original value. Accordingly, we observed that a higher log LF/HF power ratio and BMI were positively and significantly associated with the AHI in the adult patients who underwent whole-night PSG; that is, the patients with OSA had a higher log LF/HF power ratio during sleep. However, adults with OSA had no significantly lower parasympathetic tone, RMSSD. HRV, which refers to fluctuations in time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operates on different time scales to adapt to environmental and psychological challenges [29]. In this study, Ultra-Low Frequency (ULF), VLF, LF power, HF power, and the log LF/HF power ratio were examined in the frequency-domain analysis. Only the log LF/HF power ratio was significantly related to the AHI. The HF power component corresponded to respiratory sinus arrhythmia and is modulated only by the parasympathetic nervous system. The LF power component is jointly modulated by the sympathetic and parasympathetic nervous systems. The log LF/HF power ratio was determined to evaluate sympathovagal balance. A low log LF/HF power ratio reflects parasympathetic dominance, whereas a high log LF/HF power ratio indicates sympathetic dominance and low vagal activation [27]. A significantly decreased overall HRV exhibits a pattern of parasympathetic loss (lower RMSSD, PNN50, and HF power) with sympathetic overdrive (higher LF) and sympathovagal imbalance (higher log LF/HF power ratio) [16]. HRV can increase the risks of diabetes, obesity, osteoporosis, arthritis, Alzheimer’s disease, periodontal disease, cancer, frailty, and disability [9]. We observed that a higher log LF/HF power ratio was strongly associated with the AHI, which is an indicator of OSA. One study reported that a higher log LF/HF power ratio increased sympathetic tone and discordance in sympathovagal activity in patients with moderate OSA [17]. Thus, patients with OSA might have an increased risk of cardiovascular and cerebrovascular diseases. The SDNN, SDANN, SDNNIDX, pNN50, TINN, SDSD, and RMSSD were included in the time-domain analysis. The RMSSD is the primary time-domain measure used to estimate vagally mediated changes reflected in HRV [30]. Compared with the pNN50, the RMSSD more favorably reflects changes in HRV [31]. One study reported that the RMSSD was measured to examine tonic vagal activity and was strongly correlated with HF power [32]. We analyzed the RMSSD and observed that it was negatively and significantly correlated with the log LF/HF power ratio (correlation: −0.633, $p \leq 0.001$) but was not significantly correlated with the AHI (correlation: −0.179, $$p \leq 0.234$$). Similar results were also found in the previous studies [23,33,34,35]. Other studies reported that RMSSD was lower in the OSA during night time, but it was not significantly lower in records from the daytime and 24 h recording [36]; and RMSSD was lower while patients with severe OSA. The explanations included different designs and sizes of samples. Another explanation might be the sympathetic components might be more sensitive than the parasympathetic components for adults with OSA. Yet, more studies should be warranted to demonstrate the rationale. In time-domain analyses, we noted that the log value of the SDNN was 4.8 ± 0.5. A study reported that a log SDNN value of >4.6 was a satisfactory predictor of patients’ survival after acute myocardial infarction [37]. Additional studies should be conducted to verify the association between the parameters included in the time-domain analysis and OSA. We noted that BMI was positively associated with OSA; this finding is consistent with that of another study [38]. Studies have identified classical risk factors for OSA including age, male sex, obesity (BMI > 30), snoring, high blood pressure, metabolic syndrome, and sleep duration of ≥8 h [38,39,40,41]. The strength of this study was that AHI (an indicator of OSA severity) was significantly associated with higher log LF/HF power ratios (a surrogate of sympathetic tone) in the adult patients who underwent whole-night PSG, but it was not significantly associated with the parasympathetic tone, RMSSD. This current study has the following limitations. First, a small number of participants referred for PSG were included in this study ($$n = 62$$). Second, the recordings were performed during whole-night PSG. Thus, the sympathetic and parasympathetic tones might be different between the sleep and awake stages. ## 5. Conclusions This study demonstrated that a higher log LF/HF power ratio, a frequency-domain parameter HRV, and BMI were positively and significantly associated with the AHI in the adult patients who underwent whole-night PSG. The higher log LF/HF power ratio indicated increased sympathetic nervous system activity. 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--- title: 'A Multifunctional Trypsin Protease Inhibitor from Yellow Bell Pepper Seeds: Uncovering Its Dual Antifungal and Hypoglycemic Properties' authors: - Juliana Cotabarren - Brenda Ozón - Santiago Claver - Florencia Geier - Martina Rossotti - Javier Garcia-Pardo - Walter David Obregón journal: Pharmaceutics year: 2023 pmcid: PMC10054557 doi: 10.3390/pharmaceutics15030781 license: CC BY 4.0 --- # A Multifunctional Trypsin Protease Inhibitor from Yellow Bell Pepper Seeds: Uncovering Its Dual Antifungal and Hypoglycemic Properties ## Abstract Fungal infections are a growing public health concern worldwide and the emergence of antifungal resistance has limited the number of therapeutic options. Therefore, developing novel strategies for identifying and developing new antifungal compounds is an active area of research in the pharmaceutical industry. In this study, we purified and characterized a trypsin protease inhibitor obtained from Yellow Bell Pepper (*Capsicum annuum* L.) seeds. The inhibitor not only showed potent and specific activity against the pathogenic fungus Candida albicans, but was also found to be non-toxic against human cells. Furthermore, this inhibitor is unique in that it also inhibits α-1,4-glucosidase, positioning it as one of the first plant-derived protease inhibitors with dual biological activity. This exciting discovery opens new avenues for the development of this inhibitor as a promising antifungal agent and highlights the potential of plant-derived protease inhibitors as a rich source for the discovery of novel multifunctional bioactive molecules. ## 1. Introduction In the last decade, the increase in antifungal resistance among pathogenic fungi has become a serious concern worldwide. Recent studies have suggested that pathogenic fungi are responsible of over 150 million severe fungal infections and about 1.7 million infectious-disease related deaths annually [1]. Fungi, which can be unicellular or multicellular eukaryotic organisms, can survive in a wide range of environmental conditions. Due to their eukaryotic nature, the number of currently available drugs to treat invasive fungal infections is limited to a reduced number of chemical entities [2]. These compounds perform their actions via three different main mechanisms: (I) inhibiting ergosterol biosynthesis and/or its availability, (II) inhibiting the DNA/RNA biosynthesis, and (III) inhibiting fungal cell wall biosynthesis and membrane sterols. The irresponsible use of antifungals has led to the emergence of increasingly resistant pathogenic strains, leaving very few therapeutic options to treat aggressive fungal infections. Therefore, developing novel strategies for identifying and developing novel antifungal compounds is an active area of research in the pharmaceutical industry. One promising strategy to develop novel antifungals is targeting their virulence factors [3]. Many pathogenic fungi produce molecules that facilitate the adhesion to the host tissues. Another common virulence strategy is the production and secretion of proteases, such as aspartic and serine proteases, which allows pathogenic fungi to survive and penetrate host tissues during infection. Given the relevant role of extracellular fungal proteases, it has been speculated that specific protease inhibitors (PIs) may be a promising strategy for the development of novel efficient antifungal drugs. Plants have traditionally been a crucial source for identifying and developing new molecules with antifungal properties. In recent years, medicinal plants and plant-derived extracts have been used as important sources for antifungal drug discovery [4,5]. Higher plants possess the ability to produce a wide variety of secondary metabolites with high chemical diversity, including proteins, peptides, sugars, and nucleosides. Many of these compounds, such as plant-derived proteins and peptides, are PIs with demonstrated antibacterial [6,7] and antifungal properties [8]. Plants are rich in small proteinaceous PIs as these molecules are involved in plant defense mechanisms against pathogens and predators [5,9,10]. In addition, plant proteins contain a relatively high content of disulfide bridges, which allows plant-derived PIs to effectively slow or inhibit the catalytic action of their target enzymes, even under extreme environmental conditions [5]. Compared to small chemical molecules, natural inhibitors are often less toxic, which leads to better tolerability. In addition, these proteins have showed a remarkable multifunctionality. Such properties can be exploited for antifungal drug development. In this study, we report the isolation and characterization of a thermostable trypsin protease inhibitor obtained from Yellow Bell Pepper (*Capsicum annuum* L.) seeds. We have evaluated the inhibitory capacity against a set of pathogenic bacteria and fungi. Ultimately, this inhibitor showed both potent and specific activity in vitro against pathogenic Candida albicans and hypoglycemic activity. Furthermore, our studies also suggest that this naturally occurring molecule is safe and has no toxicity against human cells. Taken together, the current results demonstrate that this novel inhibitor could effectively be used as an antifungal agent in pharmaceutical preparations to prevent invasive candida infections. ## 2.1. Materials The seeds of the Yellow Bell Pepper (Capsicum annuum) were hand-collected from local farmers around La Plata, Buenos Aires, Argentina. The seeds were processed as previously described elsewhere [11]. The reagents sodium chloride, Coomassie Blue G-250, N,N,N′,N′-tetramethylethylenediamine (TEMED), tris (hydroxymethyl) aminomethane, sodium dodecyl sulphate (SDS), bovine serum albumin (BSA), β-mercaptoethanol (β ME), Nα-benzoyl-DL-arginine-p-nitroanilide (BApNA), and 4-nitrophenol-α-D-glucopyranoside (PNPG) were purchased from Sigma-Aldrich (San Luis, MO, USA). The proteases used in this study, such as Trypsin and α-Glucosidase, were obtained from Sigma-Aldrich. To perform PI purification, a Glyoxyl-agarose resin was obtained from FlukaTM. Fluconazole was purchased from Signa-Aldrich. All chemicals and reagents used in this study were of analytical grade, unless otherwise specified. ## 2.2. Cell Lines and Pathogenic Microbial Strains Escherichia coli (ATCC 25923), *Pseudomonas aeruginosa* (ATCC 27853), *Staphylococcus aureus* (ATCC 29213), *Klebsiella pneumoniae* (ATCC 700603), *Enterococcus faecalis* (ATCC 29212), Candida albicans (CIPROVE), *Candida tropicalis* (CIPROVE), *Candida glabrata* (CIPROVE), Candida krusei (CIPROVE), Rhodotorula spp. ( CIPROVE) and *Saccharomyces cerevisiae* (CIPROVE) were obtained from CIPROVE. ## 2.3. Crude Extract Preparation To prepare the extracts, *Capsicum annuum* seeds were washed with distilled water and stored at −20 °C until PI extraction. Capsicum annuum dry seeds (about 30 g) were ground using a mechanic blender. The sample was grounded with 100 mL of 0.01 M phosphate buffer, 0.1 M NaCl, pH 7.4 placed in an ice bath to avoid possible protein denaturation. Afterwards, the mixture was incubated 3 h at 4 °C and filtered using a gauze. The resultant homogenate was centrifuged at 7000× g for 30 min at 4 °C, and the supernatant (from now on: YBPCE) was collected and frozen at −20 °C until further processing. The total protein content present in the sample was as described in our previous publication [12] using the Bradford’s assay [13]. Bovine serum albumin (BSA) was used as standard (0.1 mg/mL). Next, the trypsin inhibitory activity present in the clarified homogenate was determined as described below. ## 2.4. Trypsin Inhibition Measurements Trypsin inhibitory activity of the different samples was determined using Nα-benzoyl-DL-arginine-p-nitroanilide (BApNA) as a substrate. To perform the inhibitory activity experiments, we adapted the method of Erlanger, Kokowsky and Cohen [14] to 96- well plate measurements. To perform the experiments, trypsin (0.25 mg/mL) was pre-incubated with increasing concentrations of the extract (concentrations ranging from 0 to 50 μg/mL) in 100 mM Tris-HCl buffer (pH 7.5) with 50 mM CaCl2. The samples were pre-incubated for 10 min at 37 °C, and then the BApNA substrate was added to each well at a final concentration of 1 mM. The hydrolysis of BApNA was monitored by recording increases in the absorbance at 410 nm using a Tecan Infinite M200 PRO spectrophotometer (Männedorf, Switzerland). The plates were incubated at 37 °C for 10 min. One trypsin inhibitory unit (1 TIU) was defined as the decrease of 0.01 unit of absorbance at 410 nm per 10 min assay, at 37 °C. All experiments were carried out in triplicate. ## 2.5. Heat Treatment and Affinity Chromatography Purification According to our previous studies, it is common that protease inhibitors present high physicochemical stability with minimal loss of inhibitory activity [5]. Accordingly, in the first purification step, the crude extract (named here as YBPCE) was subjected to 100 °C for 5 min. After cooling at room temperature, thermally denatured proteins were removed by centrifugation for 30 min at 7000× g and 4 °C. Afterwards, the total protein content and the inhibitory activity of the non-treated crude extract and heat-treated sample (named hereafter as YBPHT) were evaluated. For protein purification, a sample of YBPHT containing 40.4 ± 0.1 μg/mL of protein was loaded to a Trypsin-glyoxyl-agarose column (1.5 × 10 cm) previously equilibrated with 0.1 M Tris-HCl buffer (pH 8.0) containing 0.2 M NaCl. This protocol was optimized previously by our group [15]. In the first step of purification, the unbound proteins were eluted with equilibration buffer, and then affiliated proteins were eluted with HCl pH 2.0. The eluted fractions were adjusted to pH 7.0 with 0.1 M NaOH, and the fractions exhibiting trypsin inhibitory activity were pooled (see previous Section 2.3 Trypsin inhibition measurements). ## 2.6.1. Inhibitory Assays and Ki Determination The inhibition constant (Ki) of YBPTI was determined by performing a Dixon plot analysis (1/v vs. [I], where [I] is the inhibitor concentration). Previously, the inhibition of trypsin activity in the presence of different concentrations of the inhibitor and two different substrate concentrations was evaluated. The inhibition experiments were performed with increasing concentrations of the inhibitor YBPTI (0–3.2 μg/mL) and BApNA (1.0 and 2.0 mM). Bovine trypsin was assayed at a fixed concentration of 0.25 mg/mL, similarly to that described in [16]. The Ki was determined from a Dixon plot, where the reciprocal of the enzyme reaction rate was expressed as 1/v. The Ki value was derived from the intersection of the two lines plotted for two different BApNA concentrations. All the reactions were performed in triplicate. ## 2.6.2. YBPTI Stability Studies The physico-chemical stability of the purified YBPTI was evaluated. First, the effect of the protease inhibitor under extreme temperatures was evaluated as previously described [12]. In brief, YBPTI aliquots were incubated at 100 °C for different periods of time (i.e., 30, 60, 90, 120, 150 and 180 min). After incubation, the samples were cooled at room temperature and the residual trypsin inhibitory activity was determined as described in Section 2.4. Second, the effect of pH on YBPTI stability was studied. To perform the experiments, the residual activity after incubation at extreme pHs (pH 2 and pH 12) for 30 and 60 min at 25 °C was determined. The residual trypsin inhibitory activity of YBPTI was measured as detailed above. ## 2.7.1. Antimicrobial Activity against Pathogenic Bacterial and Fungal Strains The antifungal activity of the YBPCE, YBPHT, and purified YBPTI against a set of and pathogenic microbial strains (see Section 2.2) was evaluated using the agar diffusion assay. This method was based on the Kirby–Bauer test with slight modifications [17]. In essence, for the preparation of cell cultures of C. albicans, an inoculum from a fungal stock was transferred to a Petri dish containing Sabouraud agar and allowed to grow at 36 °C for 2 days. The fungal suspension was adjusted with physiological solution to 0.3 McFarland scale (105 cells/mL). To perform the assays, 10 µL of each test sample was placed over the previously inoculated Sabouraud agar plates. Once the drop placed in the plate was dried, the plates were then incubated at 36 °C for 24 h to allow fungal growth. After incubation, the diameters of the fungal growth inhibition were measured. ## 2.7.2. Antimicrobial Activity against Pathogenic Candida Albicans To further investigate the antifungal activity of YBPCE, YBPHT, and purified YBPTI on Candida albicans growth, the minimal inhibitory concentration (MIC) and minimal fungicidal concentration (MFC) for all these samples was determined. To perform the experiments, C. albicans was seeded at a concentration of 105 cells/mL onto 96-well plates. The plates were then incubated at 36 °C in 200 µL microplates in the absence and presence of different sample concentrations (i.e., YBPCE: 1653.1–2.3 µg/mL; YBPHT: 687.6–0.9 µg/mL; YBPTI: 51.1–0.07 µg/mL). Fluconazole (3.5 µg/mL) was also evaluated as reference drug with known antifungal properties. The absorbance of all the wells was measured (at 620 nm) at different time points of incubation (0, 2, 4, 16, 18 and 20 h) using a Tecan Infinite M200 PRO spectrophotometer (Männedorf, Switzerland) plate reader. All the growth inhibition experiments were performed in triplicate. The MIC was determined for each sample as the minimum sample concentration required to reduce yeast growth on $50\%$. The MFC was determined as the minimum sample concentration required to produce complete growth inhibition. After 20 h of incubation in the presence of these compounds, yeast cells were visualized using an optical microscope at 1000× magnification (Nikon Eclipse OPT-01514) by direct observation and with 30 min incubation with methylene blue (1:1 relation). The yeast cells grown in the absence of YBPTI were also determined as the control condition. ## 2.7.3. Plasma Membrane Permeabilization Experiments Plasma membrane permeabilization experiments were performed by investigating SYTOX Green (Molecular Probes Invitrogen, EUA) uptake, as described previously by [18] with some modifications. Briefly, a culture of C. albicans (105 cells/mL) was incubated in the absence or in the presence of YBPTI at the concentration of 5.7 µg/mL for 20 h. Aliquots of the suspension of yeast cells were incubated with 0.2 µM SYTOX Green (1:1 ratio) for 20 min at 25 °C. Afterwards, the cells were observed in an optical microscope (IMLD Biosystems) equipped with a fluorescence filter set for fluorescein detection (excitation wavelengths: 450–490 nm; emission wavelength: 500 nm). Both negative and positive in the absence of peptide or with 3.5 µg/mL fluconazole, respectively, were performed as control conditions. ## 2.7.4. Hypoglycemic Activity The α-Glucosidase inhibitory activity was evaluated by the [19] method, with slight modifications. The original protocol was adapted to a 96- well plate measurements, using the substrate 4-nitrophenol-α-D-glucopyranoside (PNPG). In brief, a fixed amount of α-glucosidase (0.5 U/mL) was preincubated with different concentrations of the inhibitor (ranging from 0 to 689 ng/mL) in 100 mM sodium phosphate buffer (pH 7.4). After 10 min pre-incubation at 37 °C, the substrate was added to each reaction mixture at a final concentration of 0.2 mM. The hydrolysis of PNPG was recorded through the increase in the absorbance at 405 nm at 37 °C every minute for 20 min. All the measurements were carried out in triplicate. ## 2.7.5. Cytotoxicity Assays The cytotoxicity of the purified trypsin inhibitor toward Hela (ATCC CCL-2) cells was evaluated using a MTT assay, similarly as described elsewhere [20,21]. To perform the experiments, the cells were seeded in 96-well plates at a concentration of 1.0 × 104 cells per well and incubated for 24 h. Afterwards, the cells were treated with the indicated inhibitor concentrations. After 24 h of incubation, aliquots of an MTT solution (0.5 mg/mL) were added to each well. The plates were then incubated for an additional 3 h at 37 °C. After incubation, the supernatant was removed and 100 µL of DMSO were added to each well. The absorbance at 540 nm of each well was measured using a UV-vis microplate reader MultiSkan FC (Thermo fisher Scientific, Waltham, MA, USA). ## 3.1. Isolation and Purification of YBPTI The yellow bell pepper (*Capsicum annuum* L.) belongs to the genus Capsicum (vegetable pepper). Different species from this genus are commonly used as food products, either as fresh vegetables or as processed foods [22]. During the last few years, different reports have suggested that *Capsicum annuum* seeds are a rich source of protease inhibitors [11,23,24,25,26]. These reports demonstrated the presence of mainly serine proteinase inhibitors such as trypsin and chymotrypsin. Examples of such inhibitors are: PSI-1.1 and PSI-1.2, which have been isolated from paprika seeds [23], CaTI isolated from chilli pepper seeds [24,25], and CapA1 and CapA2 obtained from the leaves of *Capsicum annum* var. Phule Jyoti. More recently, PIJP was isolated from jalapeño pepper [26]. Since yellow bell pepper is a rich source of protease inhibitors, we prepared a crude extract of *Capsicum annuum* L. seeds (hereafter named as YBPCE) to evaluate its trypsin inhibitory capacity. The protein concentration of the sample was 802.4 ± 1.12 mg/mL (see Table 1), which is in agreement with previous studies [11]. We have next evaluated the trypsin inhibitory activity of the crude extract. The presence of the extract in the reaction caused a rapid decrease in the trypsin activity, showing the specific inhibitory activity of 0.55 TIU/mg. The effect of temperature (100 °C) on the trypsin inhibitory activity of YBPCE is shown Table 1. After treatment, we observed a significant increase in the specific inhibitory activity of the sample between the heated to 100 °C and unheated extract, suggesting that such a trypsin inhibitor is a thermostable molecule. In agreement, we observed a 2.1-fold of purification after heat treatment, suggesting that other non-thermostable proteins have been removed. After the initial characterization, we decided to perform further purification of the trypsin inhibitor found in the yellow pepper seeds. For this purpose, we selected the heat-treated fraction, and we performed a high-speed centrifugation step to clarify the sample (see Materials and Methods for details). The resultant sample was applied to single-step purification based on a glyoxyl-agarose matrix prepared in house, containing the target enzyme covalently immobilized on the resin. After purification by affinity chromatography, the trypsin inhibitory activity of the eluted fractions was evaluated. As shown in Figure 1A, the purified inhibitor eluted in a single sharp peak with a specific inhibitory activity against trypsin of 77.29 TIU/mg (Table 1). The high specificity and efficiency of the purification method allowed us to obtain a highly purified sample of the trypsin inhibitor from yellow pepper seeds suitable for further inhibition kinetics characterization. ## 3.2. Inhibition Kinetics and Physicochemical Properties of YBPTI Inhibition kinetic studies of YBPTI against trypsin activity was carried out following a protocol developed in our laboratory [12]. Analysis of the data revealed that YBPTI has an IC50 value of 3.9 µg/mL (2.05 × 10−7 M) and a Ki value of 1.7 × 10−6 M (see Figure 1B). The Ki value obtained for this inhibitor is in the range of other previously described trypsin inhibitors purified from natural sources, such as the protease inhibitor isolated from B. microplus larvae (Ki = 1.20 × 10−7 M) [27], the Kunitz inhibitor isolated from *Boophilus microplus* (Ki = 1.08 × 10−7 M) [28], or the TcTI trypsin inhibitor obtained from *Torresea cearensis* (Ki = 1.4 × 10−6 M) [29], among others. To evaluate the stability of YBPTI at different temperatures and pHs, the protein was incubated at 100 °C for various amounts of time and at pH 2 and 12 for 30 and 60 min at 25 °C. The residual trypsin inhibitory activity was then assessed. As shown in Figure 2A, after incubating for 30 min at 100 °C, the residual trypsin inhibitory activity of the YBPTI was 99.67 ± $5.55\%$; that is, almost all of its activity was maintained. Interestingly, after one hour of exposure to this extreme temperature, the YBPTI sample maintained 74.65 ± $4.03\%$ of its trypsin inhibitory activity, which makes this peptide inhibitor a remarkable, highly stable molecule. Based on these findings, we can conclude that YBPTI was found to be stable at extreme pHs, retaining approximately $60\%$ of its activity after 1 h of incubation at both pH 2 and 12. There are very few studies that have investigated the thermal stability of proteins at 100 °C. Previously, a reduced number of PIs with high stability at extreme temperatures and pHs have been studied. Most of these inhibitors showed interesting biological activities, such as potential as biopesticides, with inhibitory activity on insect intestinal proteases or inhibition of larval growth: HSTI [30], C11PI [31], CFPI [32] and RsBBI1 [33]. Other previously reported biological activities for these inhibitors include antibacterial activity against S. aureus by LzaBBI [34] and anticoagulant activity in the extrinsic coagulation pathway by MpBBI [35]. Despite the great pharmaceutical potential of these highly stable plant-derived inhibitors, the biological activities of these PIs have been little explored. Overall, our results show that YBPTI is a highly stable trypsin inhibitor, with few reports of other proteins with similar stability at extreme temperatures and pHs. This stability, combined with its trypsin inhibitory activity, makes YBPTI a potentially useful protein for pharmaceutical applications. ## 3.3. Antifungal Activity of YBPTI The antifungal activity of YBPTI was evaluated against a set of fungal strains. As shown in Figure 3, a clear area of growth inhibition was observed for C. albicans and S. cerevisiae, tested with 5 µg of YBPTI, and an inhibition halo of 21 mm was observed for C. albicans, when 66 µg of YBPTI were added to the plate. Interestingly, no inhibitory effect of the *Capsicum annuum* L. inhibitor was observed for other fungal or bacterial strains (Figure 3 and Table S1). Given that C. albicans is a pathogen of great importance in clinics, we decided to further investigate the inhibitory activity of YBPTI against this microorganism. The effect of the purified YBPTI was evaluated using serial dilutions in SB broth by adding increasing sample concentrations. The minimum inhibitory concentration (MIC) was determined to be 5.7 µg/mL, showing a fungicidal effect of MFC/MIC < 4 against this pathogen. Under similar experimental conditions, fluconazole showed a MIC of 3.5 μg/mL, which is certainly close to the MIC observed for YBPTI obtained from yellow pepper seeds. Next, we performed a morphological analysis by light microscopy to confirm the toxic effect of the YBPTI on C. albicans (Figure 4). Through direct observation it was possible to demonstrate the presence of agglomerated and darkened cells (Figure 4B), unlike the control cells that showed normal fungal growth and morphology (Figure 4A). Then, SYTOX Green was used to confirm that YBPTI is able to disrupt the plasma membrane of yeast cells and cause cell death. Overall, these results suggest that YBPTI from *Capsicum annuum* L. has the potential to be developed as a natural drug for treating infections caused by C. albicans. As mentioned above, many pathogenic fungi produce extracellular proteases that can play an active role in the development of diseases. Virulence and optimal growth of fungi depend on several secreted extracellular proteases, among which serine proteases are of particular interest. This proteolytic system allows fungi to survive and penetrate tissues. One of the first examples of this phenomenon was studied for the first time in tomatoes infected with Phytophthora infestans [36], in which the increase in trypsin levels and trypsin inhibitors were correlated with plant resistance to the pathogen. In recent years, an increasing number of antimicrobial peptides rich in cysteine residues have been isolated from plants, particularly from seeds, such as *Abelmoschus moschatus* [37]. Indeed, previous studies on other varieties of *Capsicum annuum* L. have also shown that they have peptide inhibitors with antifungal activity due to their plasma membrane permeabilizing capacity [24,25]. Similarly, other serine and metalloprotease inhibitors have been studied and have been reported to possess antimicrobial activities [10]. ## 3.4. Hypoglycemic Activity of YBPTI Among the risk groups that are more susceptible to infection by Candida spp. are patients with diabetes mellitus (DM) [38], whose infections are aggravated in cases of uncontrolled hyperglycemia [39]. For this reason, it has been previously suggested that regulating blood glucose levels may be an important factor for the prevention and treatment of comorbid invasive candida infections. In this study, we have further investigated the inhibitory activity YBPTI against α-1,4-glucosidase. As shown in Figure 5, YBPTI was able to inhibit the enzyme α-1,4-glucosidase with an IC50 value of 75.33 ± 1.17 ng/mL. It is expected that inhibiting the activity of α-1,4-glucosidase leads to a decrease in the release of free glucose from complex carbohydrates, thereby lowering local blood glucose levels [40]. Indeed, hypoglycemic-lowering activity tests have been rarely described for PIs, being mostly reported for peptides derived from protein hydrolysates [41,42]. In this regard, peptides from whey protein hydrolysates have been shown to have strong α-1,4-glucosidase inhibitory activity, with an IC50 of 3.5 mg/mL, according to research by Konrad et al. [ 41]. Similar levels of inhibition of α-1,4-glucosidase were reported by Matsui et al. [ 43] and Yu et al. [ 44] for different peptides. ## 3.5. Cytotoxicity of YBPTI against HeLa Cells To evaluate the toxicity of YBPTI against human cells, in vitro cytotoxicity assays with HeLa cells was carried out, similarly to those described previously for other bioactive molecules [45,46]. These assays were performed using the range of concentrations where YBPTI inhibited the growth of Candida albicans in the range 0.15 µg/mL to 40 µg/mL. As shown in Figure 6, a value of around 5 µg/mL would maintain almost $90\%$ cell viability while a value of 40 µg/mL would maintain close to $80\%$ cell viability. Thus, the approximated IC50 is certainly higher than 50 µg/mL, a value almost 10-fold over the observed MIC determined against C. albicans. On the basis of these findings, we can state that our inhibitor did not show a reduction in cell viability at the assayed inhibitor concentrations in the range 0.15 to 40 μg/mL, which demonstrates the safety of this natural compound for the potential treatment of C. albicans infections, as well as other pharmaceutical applications. ## 4. Conclusions The increasing antifungal resistance among pathogenic fungi is a serious global concern. The limited number of currently available drugs to treat invasive fungal infections has led to the emergence of increasingly resistant strains, leaving few therapeutic options. Targeting virulence factors, such as extracellular proteases, is a promising strategy for the development of novel antifungal drugs. Herein, we report the purification and characterization of a thermostable trypsin inhibitor from *Capsicum annuum* L. seeds with dual antifungal and hypoglycemic properties. This natural inhibitor was obtained from Yellow Bell Pepper (*Capsicum annuum* L.) seeds by heat-treatment and affinity purification with immobilized trypsin. The purified inhibitor showed potent and specific activity in vitro against pathogenic Candida albicans, and was found to be safe and non-toxic against human cells. Additionally, the inhibitor also exhibited α-1,4-glucosidase inhibition activity, positioning this inhibitor as one of the first plant-derived molecules with such a particular dual combination of biological activities. 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--- title: Genome-Wide Identification and Characterization of Bovine Fibroblast Growth Factor (FGF) Gene and Its Expression during Adipocyte Differentiation authors: - Hui Sheng - Junxing Zhang - Fen Li - Cuili Pan - Mengli Yang - Yuan Liu - Bei Cai - Lingkai Zhang - Yun Ma journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054561 doi: 10.3390/ijms24065663 license: CC BY 4.0 --- # Genome-Wide Identification and Characterization of Bovine Fibroblast Growth Factor (FGF) Gene and Its Expression during Adipocyte Differentiation ## Abstract Fibroblast growth factor (FGF) family genes are a class of polypeptide factors with similar structures that play an important role in regulating cell proliferation and differentiation, nutritional metabolism, and neural activity. In previous studies, the FGF gene has been widely studied and analyzed in many species. However, the systematic study of the FGF gene in cattle has not been reported. In this study, 22 FGF genes distributed on 15 chromosomes were identified in the *Bos taurus* genome and clustered into seven subfamilies according to phylogenetic analysis and conservative domains. Collinear analysis showed that the bovine FGF gene family was homologous to Bos grunniens, Bos indicus, Hybrid-Bos taurus, Bubalus bubalis, and Hybrid-Bos indicus, and tandem replication and fragment replication were the key driving forces for the expansion of the gene family. Tissue expression profiling showed that bovine FGF genes were commonly expressed in different tissues, with FGF1, FGF5, FGF10, FGF12, FGF16, FGF17, and FGF20 being highly expressed in adipose tissue. In addition, real-time fluorescence quantitative PCR (qRT-PCR) detection showed that some FGF genes were differentially expressed before and after adipocyte differentiation, indicating their diverse role in the formation of lipid droplets. This study made a comprehensive exploration of the bovine FGF family and laid a foundation for further study on the potential function in the regulation of bovine adipogenic differentiation. ## 1. Introduction Beef is rich in protein, and its amino acid composition is close to the needs of the human body, so it is deeply loved by consumers. With the improvement in living standards, consumers pay more attention to the taste and flavor of beef products, and these factors are affected by the content and distribution of intramuscular fat (IMF) [1]. At the cellular level, adipocyte proliferation (increased number of adipocytes) and differentiation (adipocyte hypertrophy, increased triglyceride accumulation) are the main ways to increase fat content. It is of great significance to increase the intramuscular fat content and improve beef quality by studying and revealing the molecular regulation mechanism of proliferation and differentiation of bovine adipocytes. Adipogenesis is a biological process closely coordinated by a series of transcriptional cascades and a large number of transcriptional regulatory factors [2]. At present, the most widely studied regulatory factors of adipogenesis are the CCAAT/enhancer-binding protein (C/EBP) and peroxisome proliferator-activated receptor (PPAR) families, which play an important role in the cascade of adipogenesis [3,4]. In addition, varieties of regulatory factors and signaling pathways are involved in the directional differentiation of pluripotent stem cells into precursor adipocytes, including WNT proteins [5], bone morphogenetic protein (BMP), and members of the fibroblast growth factor (FGF) proteins [6,7]. Here, the main purpose of this study is to explore the regulatory role of the FGF gene family in the process of adipocyte differentiation. The FGF family consists of 22 members that not only closely relate to embryonic development, tissue regeneration, angiogenesis, metabolic activity, and neurological function but also play an important role in cell proliferation, differentiation, migration, apoptosis, and chemotaxis [8,9]. Mitochondrial brown fat uncoupling protein-1 (UCP1) plays a key role in regulating the energy balance of brown adipose tissue (BAT). It has been found that FGF6 and FGF9 can regulate energy metabolism by inducing the expression of UCP1 in adipocytes and preadipocytes [10]. FGF2 not only acts on muscle growth but also promotes fat and angiogenesis [11,12]. FGF10 can not only stimulate the proliferation of preadipocytes through the Ras/MAPK pathway but also promote the expression of retinoblastoma protein (pRb), and the complex of pRb and C/EBPα can induce adipogenesis [13]. In rodent models with obesity and type 2 diabetes, FGF21 has the effect of reducing blood sugar and lipidemia and can increase energy consumption leading to weight loss [14]. Although the functional studies of some FGF family members have been reported in many species, their expression patterns and regulatory mechanisms during adipogenic differentiation of bovine adipocytes have not been systematically studied and elucidated. Therefore, in this study, the characteristics and function of the FGF gene family members are analyzed. Furthermore, we detect the expression profile of FGF family members during the adipogenic differentiation in cattle. Our results lay a foundation for further exploring the molecular mechanism of the FGF genes on bovine adipogenesis. ## 2.1. Identification of Members of the Bovine FGF Family In this study, 49 verified FGF protein sequences of humans (Homo sapiens, 22), mice (Mus musculus, 22), and cattle (Bos taurus, 5) were used to identify members of the FGF family. Through the HMM analysis and BLASTP alignment of these 49 protein sequences, 22 non-redundant FGF protein sequences were identified in cattle, including FGF1–FGF14 and FGF16–FGF23 (Table 1). Meanwhile, the corresponding FGF family proteins (Additional file S1) were identified in *Bos indicus* [19], Hybrid-*Bos taurus* [21], Hybrid-*Bos indicus* [20], Bos grunniens [20], *Bubalus bubalis* [22], *Bos mutus* [16], and Bison bison bison [18]. All FGF protein sequences can be seen in Additional file S2. Isoelectric point (PI), molecular weight (Mw), and the number and sequence of amino acids (AA) are shown in Additional file S3. The results showed that the amino acid sequences of 22 bovine FGF proteins ranged from 155 (FGF1) to 270 (FGF5), while the molecular weight (Mw) ranged from 17249.83 to 29640.87 Da, which was consistent with the corresponding protein length. FGF1 and FGF21 showed acidity with PIs of 6.51 and 6.08, respectively. FGF9 was neutral (7.06), and all other protein members were basic, with PIs between 7.7 and 11.48. All the 22 FGF proteins of bovine contained FGF/FGF superfamily conserved domain (Additional file S4). ## 2.2. Structural Characteristics of Members of the Bovine FGF Family In this study, the phylogenetic relationships of bovine FGF family members were analyzed to predict their conserved motifs and gene structure (Figure 1). The results showed that the FGF family members of cattle were mainly clustered into eight subfamilies according to the different evolutionary branches. The FGF1 subfamily consisted of FGF1 and FGF2, the FGF4 subfamily consisted of FGF4-6, the FGF7 subfamily consisted of FGF7, FGF10, and FGF22, the FGF8 subfamily consisted of FGF8, FGF17, and FGF18, the FGF9 subfamily consisted of FGF9, FGF16, and FGF20, the FGF19 subfamily consisted of FGF19, FGF21 and FGF23, FGF11-14 was from a subfamily, and FGF3 was divided into a separate subfamily. All FGF family proteins contained motif 1 and motif 2, which consisted of 21 and 20 amino acids, respectively (Additional file S5). The FGF8 subfamily had the same six motifs, FGF1-4 and FGF6 had the same four motifs, FGF11-14 had the same six motifs, and FGF9, FGF16, and FGF20 had the same five motifs. The coding sequence (CDS), untranslated region (UTR), and intron of FGF family members were different. The number of CDS varied from 2 to 13, and the position and length of 3′ UTR and 5′ UTR were also different, but the members of the FGF family in the same evolutionary branch showed similar conservative patterns and gene structures. ## 2.3. Phylogenetic Analysis of Bovine FGF Protein On the basis of exploring the evolutionary relationship of the bovine FGF gene, we constructed a phylogenetic tree based on a total of 202 FGF members, including human, mouse, and eight bovine subfamily species (Figure 2). Phylogenetic analysis showed that FGF family proteins were mainly clustered into eight groups, and the number of genes in each group was different. Group IV was the largest with 37 genes, followed by Group III with 30, both Groups I and IV with 28, both Groups II and VII with 26, and Group VIII with 19 and Group VI with 8. ## 2.4. Chromosome Distribution and Collinearity Analysis of FGF Gene We analyzed the location of FGF family members on the chromosomes of six bovine subfamily species, and the 22 FGF genes in cattle were unevenly distributed on 15 chromosomes (Figure 3). Compared to Bos taurus, *Bos indicus* (FGF3, FGF5, and FGF17), Hybrid-*Bos taurus* (FGF13 and FGF16), Hybrid-*Bos indicus* (FGF13), and Bos grunniens (FGF17 and FGF19) are missing several FGF genes. Meanwhile, the order of FGF1 and FGF22 of *Bos taurus* (Chr7) on chromosomes was opposite to that of Hybrid-*Bos taurus* (Chr7), Hybrid-*Bos indicus* (Chr7), and *Bubalus bubalis* (Chr9). In addition, the sequence and position of three tandem genes (FGF19, FGF4, and FGF3) located on *Bos taurus* chromosome 29 changed on Hybrid-Bos taurus, Hybrid-Bos indicus, and Bos grunniens chromosomes. In addition, we found two pairs of tandem repeat genes on the chromosomes of Bos taurus. FGF3, FGF4, and FGF19 were located on chromosome 29, only 35 and 63 kb apart, respectively. On chromosome 5, FGF6 and FGF23 were also located within 50 kb of each other. Meanwhile, eight pairs of fragmented repeat genes were also found (Figure 4). *These* gene replication events may be one of the drivers of FGF gene evolution. ## 2.5. Collinear Analysis of FGF Gene in Several Bovine Subfamily Species To further explore the phylogenetic mechanisms of the FGF gene, we studied homology in six bovine subfamily species. The results of the collinear analysis showed that there were multiple collinear gene pairs between *Bos taurus* and *Bos indicus* [31691], Hybrid-*Bos taurus* [34495], Hybrid-*Bos indicus* [33570], Bos grunnines [32378], and *Bubalus bubalis* [33327] (Figure 5). There was a one-to-one correspondence between *Bos taurus* chromosomes (2N = 60) and Hybrid-Bos indicus, Bos grunnines, Hybrid-Bos taurus, and Bos indicus, and there was also great homology between *Bos taurus* chromosomes and *Bubalus bubalis* chromosomes (2N = 50), indicating that these collinear gene pairs are relatively conservative in the evolution of bovine species (Table 2). ## 2.6. Expression Analysis of FGF Gene in Different Tissues The expression patterns of genes can provide an important reference for studying their function, so we explored the expression patterns of FGF gene family members in eight tissue types (heart, liver, spleen, lung, kidney, muscle, adipose, rumen) of cattle. ( Figure 6, Table S4). The results showed that the expression of FGF1, FGF5, FGF10, FGF12, FGF16, FGF17, and FGF20 was the highest in adipose tissue, while the expression of FGF4, FGF7, FGF8, FGF11, FGF14, FGF18, FGF19, FGF21, FGF22, and FGF23 in adipose tissue was lower than that in lung tissue but higher than that in other tissues. In addition, all the members of the FGF gene family were generally expressed in various tissues, indicating that they may play a wide range of roles in life activities. ## 2.7. Expression Analysis of FGF Gene during Differentiation of Bovine Adipocytes This study explored the expression pattern of the FGF gene family using bovine subcutaneous adipocytes. The results of Oil Red O staining showed that the number of lipid droplets formed by adipocytes on the 10th day was significantly higher than that of uninduced adipocytes. The results of qRT-PCR detection showed that the expression levels of adipogenic marker genes FABP4 and PPARγ increased significantly after cell induction, indicating that the induced differentiation model of bovine adipocytes was successfully established (Figure 7, Table S2). Then, the expression pattern of the FGF gene was detected by cell model, and it was found that except for FGF4, FGF13, FGF16, FGF21, and FGF22, the FGF family genes had relatively high expression levels in bovine adipocytes. In addition, with the increase in induction days, the expression levels of FGF1, FGF2, FGF3, FGF10, FGF11, and FGF18 increased significantly. The expression levels of FGF5, FGF10, and FGF20 were highest on the second day of differentiation and then decreased rapidly. The expression of FGF14 was the highest on the 4th day of differentiation and then decreased to the lowest on the 10th day of differentiation. The expression levels of FGF12 did not change significantly on the 2nd to 8th day of differentiation but decreased significantly on the 10th day of differentiation. The expression level of other FGF family members decreased significantly with the increase in adipocyte differentiation time (Figure 8, Table S2). ## 3. Discussion Beef is one of the most important meat products in daily life, and the content of IMF directly affects its taste and flavor, so it is of great significance to explore the molecular mechanism affecting IMF deposition. In recent years, with the completion of whole genome sequencing of animals and plants, a large number of studies on gene families have been reported. Fibroblast growth factor (FGF) transduces signals through fibroblast growth factor receptor (FGFR) tyrosine kinase, which mainly regulates the development and morphogenesis of many tissues by paracrine or autocrine actions [15,16,17]. Considering the potential role of FGF family members and the fact that only a small number of FGF family members have been reported in other species [17,18], we believe that it is very important to identify and analyze the FGF gene family in cattle. ## 3.1. Identification and Phylogenetic Analysis of Bovine FGF Family Proteins In this study, we used the 49 identified human, mouse, and bovine FGF protein sequences as references to retrieve FGF genes in the *Bos taurus* [22], *Bos indicus* [19], Hybrid-*Bos taurus* [20], Hybrid-*Bos indicus* [21], Bos grunniens [20], *Bubalus bubalis* [22], *Bos mutus* [16], and Bison bison bison [18] genomes based on sequence similarity and conserved structural domains. The difference in the number of FGF gene family members may be related to the genome size and ploidy level [19]. Previous studies have found that Caenorhabditis elegans has only two FGF genes, whereas 22, 22, 27, and 35 FGF genes were identified in the genomes of human, mouse, zebrafish, and common carp, respectively, indicating that the massive expansion of FGF gene family members occurred during the evolution of primitive metazoans into vertebrates and aquatic organisms [17,18,19,20,21]. In addition, a new FGF gene, FGF24, has been identified in zebrafish, but direct homologs of FGF24 have not been identified in humans, mice, or bovids, and it is speculated that it may have been lost during the evolution of these animals [17,22]. The phylogenetic study showed that the FGF genes identified in humans, mice, and eight species of the Bovine subfamily were clustered into eight main branches (Figure 2), and the FGF members with close evolutionary distance would gather together. For example, *Bos taurus* FGF1, FGF13, and FGF23 clustered first with *Bos indicus* and then with FGF genes from other species. Studies have shown that the FGF family has experienced at least two major extensions: The first expansion increased the number of FGFs from one or more primitive FGF genes to eight primitive FGF genes, forming the prototype of eight subfamilies. The second amplification occurred in the process of allelic evolution, which was mainly caused by genome replication [23]. In this study, a phylogenetic tree was constructed using 22 bovine fibroblast growth factor protein sequences, and it was found that they could be clustered into eight subfamilies (FGF1, FGF3, FGF4, FGF7, FGF8, FGF9, FGF11, and FGF19 subfamilies), while the 22 FGF genes in the human and mouse genomes were clustered into seven subfamilies, with FGF3 identified as a member of the FGF7 subfamily [17,21]. In all the current studies, FGF3 genes in vertebrates are always divided into the FGF4 subfamily or FGF7 subfamily, but in fact, the clustering classification of FGF3 is still controversial [17,23,24]. Oulion proposed a new evolutionary scenario for FGF genes based on the results obtained by studying gene content, phylogenetic distribution, and the conservation of commonalities between amphioxus and vertebrates, namely that FGF3 forms a new subfamily, which is consistent with the results of the present study [25]. This evolutionary scheme is demonstrated for the first time in this study based on the results of analyzing the phylogenetic relationships of bovine FGF family members, and it contributes to reconciling different evolutionary hypotheses proposed in previous studies. ## 3.2. Analysis of Physicochemical Properties and Structural Characteristics of the Bovine FGF Protein Molecular weight and isoelectric point play an important role in determining molecular and biochemical functions [26]. We studied the size and isoelectric point of bovine FGF protein and found that, except for FGF1, FGF9, and FGF21, the isoelectric point of most FGF proteins was more than seven, indicating that there was a high proportion of basic amino acids. In order to gain insight into the structural diversity of bovine FGF proteins, the intron-exon organization was analyzed (Figure 1). Some similar FGF gene pairs showed different intron/exon arrangements, which indicates that the bovine FGF gene may have a more complex gene structure evolution. We identified 10 conserved motifs in bovine FGF proteins, of which motif 1 and motif 2 were present in almost all FGF proteins (Additional file S5). There were some differences in the arrangement of conserved motifs among members of the FGF family, but the members of the same subfamily were composed of similar motifs, which indicates that their structures and biological functions are similar. These results confirmed the characteristics of the bovine FGF protein family and laid a foundation for further study of the function of the FGF gene. ## 3.3. Chromosome Distribution, Replication, and Collinearity Analysis of Bovine FGF Protein The chromosome map of the bovine FGF gene showed that 22 FGF genes were unevenly distributed on 15 chromosomes (Figure 3). The number of genes on each chromosome varied from one to three, including two genes on chromosomes 5, 7, 12, 20, and X, three genes on chromosome 29, and only one gene on most other chromosomes. Gene replication (tandem replication and fragment replication) and transposable events are the main driving forces leading to the complexity of eukaryotic genomes and the expansion of family members [27]. In the study of the human FGF gene family, it was found that FGF3, FGF4, and FGF19 were located on chromosome 11, and the distances were 40 and 10 kb, respectively. FGF6 and FGF23 were within 55 kb on chromosome 12. In the mouse study, it was found that FGF3, FGF4, and FGF19 were located in the 80 kb range of chromosome 7, and FGF6 and FGF23 were closely linked on chromosome 6 [28]. Like humans and mice, we identified FGF3, FGF4, and FGF19 on bovine chromosomes within the range of 35 to 63 kb on chromosome 29, while FGF6 and FGF23 were also located within 50 kb on chromosome 5 (Figure 3). *These* gene positions suggest that the FGF gene family arose through the duplication and translocation of genes and chromosomes during evolution, which would have contributed to the diversification of gene functions [28]. To investigate the evolutionary relationships of the FGF genes, we performed genomic collinearity analysis on cattle and five other bovine subfamily species and found multiple collinearity gene pairs, indicating that the FGF genes are highly conserved. ## 3.4. FGF Gene Affects Adipocyte Differentiation In order to understand the expression of FGF family members, the expression profiles of the FGF gene in eight tissue types of cattle were analyzed. The results showed that FGF family members were expressed in all these tissues, with FGF1, FGF5, FGF10, FGF12, FGF16, FGF17, and FGF20 being highly expressed in adipose tissue. Studies have shown that FGF1 can promote the differentiation of human preadipocytes into mature adipocytes by regulating the dependent network of BMP protein and activin membrane binding inhibitor (BAMBI)/PPARγ [29]. FGF2 can activate PI3K/AKT signal pathway and promote the proliferation and adipogenic differentiation of adipose stem cells [30]. FGF10 can promote adipogenic differentiation of goat intramuscular preadipocytes [31]. This is consistent with our qRT-PCR results, the expression levels of FGF1, FGF2, and FGF10 are significantly increased in induced adipocytes, and other FGF family members have different expression levels. Fibroblast growth factor receptors (FGFRs) are tyrosine kinase receptors (TRKs) that include four genes, FGFR1, FGFR2, FGFR3, and FGFR4 [32]. Four FGFR genes in vertebrates produce seven FGFR proteins with different ligand binding specificity (FGFRs 1b, 1c, 2b, 2c, 3b, 3c, and 4) according to the difference of immunoglobulin-like domain III, and the biological function of typical FGFs is mediated by the interaction with FGFRs [33,34,35]. Therefore, we performed an expression analysis of FGFRs, which showed that FGFR2 and FGFR4 were most highly expressed in adipose tissue and FGFR1 and FGFR3 were less expressed in adipose tissue than in lung and kidney tissue but higher than in other tissues (Figure 9A, Table S3). Previous studies on the binding specificity of FGFs-FGFRs found that members of the FGF7 subfamily were able to strongly activate FGFR2b, members of the FGF8 and FGF9 subfamilies showed high relative activity toward FGFR3c, members of the FGF19 subfamily showed consistent activity toward FGFR1c, 2c, 3c and FGFR4, and members of the FGF4 subfamily specifically activated the c receptor splice form [34,35]. Our analysis of the expression of FGFRs during adipocyte lipogenic differentiation also showed that the expression trends of FGFRs were similar to the expression trends of their specifically bound FGF subfamily members, and the findings strongly suggest that FGF–FGFR signaling plays an important role in adipose tissue development and adipocyte lipogenic differentiation (Figure 6, Figure 8 and Figure 9, Table S1). The interaction between proteins can reveal their regulatory relationship, which helps us to understand the potential function of these proteins. We used Cytoscape’s Agilent plug-in to mine the literature about FGF family members and their interaction genes to build a complete interaction network (Figure 10) [36]. For example, the FGF signal can regulate the metabolism of endothelial cells through MYC-dependent HK2 expression, which in turn affects the development of blood vessels and lymphatic vessels [37]. Knockout of the FGF21 gene in liver tissue can activate glucose-6-phosphatase and phosphoenolpyruvate carboxykinase through STAT3/SOCS3 pathway, thus increasing gluconeogenesis and glycogen decomposition, resulting in the aggravation of liver insulin resistance [38]. In addition, studies correlating single nucleotide polymorphisms (SNPs) in the 3′ untranslated region (UTR) of the FGF21 gene with metabolic syndrome, obesity, and diabetes showed that genetic variants in the 3′ UTR region of the FGF21 gene were associated with obesity and not with metabolic syndrome and diabetes [39]. The opening of Piezo1 ion channels in mature adipocytes leads to the release of FGF1, which activates FGFR1 and induces precursor adipocyte differentiation [40]. *In* general, these results showed that the FGF gene family plays a role in regulating vascular development, metabolism, and adipose differentiation by interacting with other genes. ## 4.1. Identification and Phylogenetic Analysis of FGF Gene We downloaded the genome files and annotation information of related species from the Ensembl database (https://asia.ensembl.org/info/about/species.html, accessed on 11 May 2022) and NCBI database (https://www.ncbi.nlm.nih.gov/genome/?term=BOS, accessed on 13 May 2022), respectively. The hidden Markov model (HMM) of the FGF gene (PF0048) was downloaded from the Pfam database (http://pfam-legacy.xfam.org/, accessed on 25 May 2022), and the HMMER 3.0 software (version 3.0) was used to build a multiple comparison model based on structural domain similarity to retrieve possible FGF proteins according to default parameters [41]. Meanwhile, according to the same template protein sequence, the possible FGF protein was obtained by Protein Basic Local Alignment Search Tool (BLASTP) analysis [42]. Then, the final protein sequences of FGF were obtained by manual examination of the two analysis results, and these protein sequences were submitted to NCBI CD-Search (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi, accessed on 5 June 2022) to determine the conserved protein domain [43]. Basic information, such as PI and Mw of genes, is predicted by ExPASy website (https://web.expasy.org/compute_pi/, accessed on 16 June 2022) [44]. The amino acid sequence alignment of the FGF gene was completed by ClustalW software (version 2.1). The results were analyzed by MEGA software (version 7.0.26), and the phylogenetic tree was constructed by using default parameters and setting 1000 repeats [45,46]. The evolutionary tree was adjusted and embellished using Figtree software (version 1.4) [47]. ## 4.2. Conservative Motif and Gene Structure Analysis Motif analysis of the amino acid sequence of FGF through the MEME database (https://meme-suite.org/meme/tools/meme, accessed on 2 July 2022) was conducted. In the parameter setting, the maximum number of motifs was 10, the optimal width was 6–50 amino acids, and the motifs with e values less than 1 × 10−10 were retained to identify the conservative motifs in these sequences [48]. The structure of the FGF gene was analyzed using TBtools software (version 1.108), and the structure of the gene was located through CDS and genome sequencing [49]. ## 4.3. Chromosome Distribution, Gene Replication, and Collinearity Analysis Using the genome annotation information obtained, the FGF genes of several bovine subfamily species were mapped to the corresponding chromosomes. MCScanX tool was used to analyze the replication events of the bovine FGF gene, and the collinearity analysis of homologous genes between cattle and five other bovine subfamily species was conducted [50]. All the above results were visualized using TBTools [49]. ## 4.4. Culture and Induced Differentiation of Bovine Primary Adipocytes The subcutaneous adipocytes of cattle were provided by the Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia University. Adipocytes stored in liquid nitrogen were resuscitated and inoculated in culture dishes to grow to about $80\%$, the differentiation medium was changed to induce differentiation of the cells, and after 2 days of induction, the maintenance medium was changed to continue the culture. The adipocytes that were not induced and induced for 10 days were stained with Oil Red O and photographed and preserved under a microscope. The specific content is carried out with reference to the method [51,52]. ## 4.5. RNA Extraction and qRT-PCR Tissue samples of the heart, liver, spleen, lung, kidney, muscle, adipose, and rumen of cattle were provided by the Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia University. The total RNA of cultured cells was extracted with TRIZOL reagent (American Invitgen), and the purity, concentration, and integrity of RNA were detected by ultraviolet spectrophotometer and $1.0\%$ agarose gel electrophoresis. The first strand cDNA was prepared using a cDNA synthesis kit (Takara, China), and the gene expression level was detected by real-time fluorescence quantitative PCR reaction (qRT-PCR). Primer information is included in Additional file S6. ## 4.6. Statistical Analysis In the qRT-PCR experiment, the mRNA of GAPDH was used as the endogenous control at the basic level, and the relative gene expression level was measured using the 2−ΔΔCt method [53,54]. Visualization of statistical results was performed using GraphPad Prism software (version 7.0). ## 5. 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--- title: Characteristics of Patients with Heart Failure and Advanced Chronic Kidney Disease (Stages 4–5) Not Undergoing Renal Replacement Therapy (ERCA-IC Study) authors: - Sandra Valdivielso Moré - Miren Vicente Elcano - Anna García Alonso - Sergi Pascual Sanchez - Isabel Galceran Herrera - Francesc Barbosa Puig - Laia C. Belarte-Tornero - Sonia Ruiz-Bustillo - Ronald O. Morales Murillo - Clara Barrios - Joan Vime-Jubany - Nuria Farre journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054565 doi: 10.3390/jcm12062339 license: CC BY 4.0 --- # Characteristics of Patients with Heart Failure and Advanced Chronic Kidney Disease (Stages 4–5) Not Undergoing Renal Replacement Therapy (ERCA-IC Study) ## Abstract Background: Despite the frequent coexistence of heart failure (HF) in patients with advanced chronic kidney disease (CKD), it has been understudied, and little is known about its prevalence and prognostic relevance. Methods: A retrospective study of 217 patients with advanced CKD (stages 4 and 5) who did not undergo renal replacement therapy (RRT). The patients were followed up for two years. The primary outcome was all-cause death or the need for RRT. Results: Forty percent of patients had a history of HF. The mean age was 78.2 ± 8.8 years and the mean eGFR was 18.4 ± 5.5 mL/min/1.73 m2. The presence of previous HF identified a subgroup of high-risk patients with a high prevalence of cardiovascular comorbidities and was significantly associated with the composite endpoint of all-cause hospitalization or need for RRT ($66.7\%$ vs. $53.1\%$, HR $95\%$ CI 1.62 (1.04–2.52), $$p \leq 0.034$$). No differences were found in the need for RRT ($27.6\%$ vs. $32.2\%$, $$p \leq 0.46$$). Nineteen patients without HF at baseline developed HF during the follow-up and all-cause death was numerically higher (36.8 vs. $19.8\%$, $$p \leq 0.1$$). Conclusions: Patients with advanced CKD have a high prevalence of HF. The presence of previous HF identified a high-risk population with a worse prognosis that required close follow-up. ## 1. Introduction Chronic kidney disease (CKD) and heart failure (HF) are prevalent diseases with high morbidity and mortality rates [1]. Both entities share a common burden of traditional cardiovascular risk factors, such as hypertension and diabetes, which are known to cause or worsen CKD and HF [2]. Moreover, the presence of one of the two may precipitate or exacerbate the other [3,4]. This has led to the concept of the cardio-renal syndrome [5]. The cardio-renal syndrome is a term used to describe a condition in which there is an intricate interplay between the heart and the kidneys, resulting in one or both organs being affected. It is classified into five types of cardio-renal syndrome, depending on which organ causes the initial damage: Type 1 and Type 2 in heart disease; Type 3 and 4 in kidney disease; and Type 5, where both coexist, especially in patients with diabetes mellitus. However, this distinction between the different types of cardio-renal syndrome can be challenging and, frequently, clinically irrelevant [6,7]. The high burden of shared cardiovascular disease and the clear worsening of the patient’s prognosis when both organs are affected make joining efforts in a multidisciplinary approach for cardiorenal patients mandatory. Extensive evidence shows that CKD is frequent in HF and associated with a worse prognosis in both acute and chronic HF [8,9]. However, most studies have focused on patients with CKD in stages 1–3. Hence, information about advanced CKD (stages 4–5) in HF is scarce. Conversely, studies on CKD looking at HF also focus on the less severe CKD stages (mean estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2) [3] or in advanced CKD already in renal replacement therapies [10]. Therefore, little is known about the interaction between HF and advanced CKD in patients not receiving renal replacement therapies. Although the percentage of patients with both HF and advanced CKD is low, the absolute number of patients is not irrelevant. Moreover, this group of patients poses a clinical challenge because most of the medications studied and approved for the treatment of HF are limited to patients with CKD in stages 1 to 3b (i.e., eGFR ≥ 30 mL/min/1.73 m2) [11]. Therefore, this study aimed to analyze the prevalence of HF in patients with advanced renal disease (stages 4 and 5) and to assess whether the presence of HF conferred a worse prognosis than in patients without HF. ## 2. Materials and Methods This was a retrospective analysis of adult patients with advanced CKD (stages 4 and 5) who were followed up at the Nephrology outpatient clinic. We included all patients with an estimated glomerular filtration rate (eGFR) below 30 mL/min/1.73 m2 CKD-EPI formula. Patients were included from the Nephology outpatient clinic on 1 January 2020 and were followed up until 31 December 2021, or they died. We excluded patients on RRT programs or who had undergone a kidney transplant. Follow-up and treatment were performed according to local protocols and the treating physician’s criteria. The chronic kidney was classified as stage 4 Severe CKD (GFR = 15–29 mL/min/1.73 m2) and stage 5 End Stage CKD (GFR < 15 mL/min/1.73 m2) [12]. Heart failure diagnosis was made according to the European Society of Cardiology HF guidelines [11]. HF with preserved ejection fraction (EF) (HfpEF) was defined as an EF greater than or equal to $50\%$, HF with reduced EF (HfrEF) as an EF less than or equal to $40\%$, and HF with mildly reduced EF (HFmrEF) as an EF between $41\%$ and $49\%$. At the inclusion date, we analyzed baseline characteristics, including cardiovascular risk factors, comorbidities, cardiac and renal history, baseline laboratory tests, and medical treatment. If available, we collected the presence of previous heart failure (HF) and ejection fraction data from the most recent echocardiogram. The primary endpoint was to analyze the clinical differences and outcomes between patients with advanced CKD with and without a history of HF. The primary outcome was all-cause mortality or the need for renal replacement therapy. Our secondary endpoints were to characterize the patients with HF history and to analyze the baseline characteristics and outcomes of patients without HF at baseline but who developed HF during the follow-up. Due to its retrospective nature, the local Ethics Committee (CEIm number $\frac{2021}{10008}$) approved the study and waived the need for written informed consent. ## Statistical Analysis Continuous variables are described as the mean and standard deviation and, when they do not follow a normal distribution, as the median and the 25–75 percentile, and categorical variables as frequency and percentage. Clinical differences were analyzed using the X2 test and Fisher’s exact test when appropriate for qualitative variables. Continuous variables were analyzed using the unpaired t-student test or Mann–Whitney U test, as appropriate. A Cox proportional hazard model was developed, adjusting for age, sex, diabetes, previous myocardial infarction, atrial fibrillation, valve disease, history of HF, eGFR, use of loop diuretic, beta-blockers and RAS inhibitor (ACEi, ARB2, INRA). A simultaneous adjustment was chosen for all variables included in the model through the Enter procedure. These variables were selected either because they presented statistically significant differences in the bivariate analysis or because they had been identified as potential confounding factors according to the literature. NT-proBNP levels were not included because of the higher number of missing data. Kaplan–Meier curves were constructed to compare the results between patients who presented decompensated HF and those who did not. The results were expressed in the hazard ratio (HR) with a confidence interval of $95\%$. Statistical significance was set at $p \leq 0.05.$ *Statistical analysis* was performed with SPSS version 22.0 software (SPSS, IBM, Chicago, IL, USA). ## 3.1. Baseline Characteristics A total of 217 patients with advanced renal disease (stages 4 and 5) were included. Eighty-seven patients ($40\%$) had a previous diagnosis of HF (Table 1). These patients were older, more frequently female, and diabetic. There was a high prevalence of cardiovascular risk factors in both groups. The mean eGFR was 18.0 ± 5.5 mL/min/1.73 m2, and $73.3\%$ of patients were on stage 4, without difference between groups. Non-cardiac comorbidities were not different between groups, but cardiac comorbidities were significantly more frequent in patients with a history of HF. The median time from diagnosis of heart failure to inclusion in the study was four years (IQR 2–7.75). One-fourth of the patients received an ACEI/ARB2/ARNI treatment. Beta-blockers were given to $49.8\%$ of patients and were more frequently used in patients with HF ($p \leq 0.001$). Mineral receptor antagonists (MRA) and SGLT2 inhibitors were used in a few patients ($2.3\%$ and $1.8\%$, respectively). Loop diuretic use was frequent. NT-proBNP and US-troponin T levels were measured in 88 and 63 of 217 patients, respectively. NT-proBNP levels were higher in the HF group (median 4480 vs. 1344 pg/mL, $p \leq 0.001$), while US-Troponin T levels were similar. In patients with a history of HF, $41.4\%$ had an HF hospitalization the previous year, and $39.1\%$ had required ambulatory intravenous loop diuretic treatment. The mean left ventricular ejection fraction was 56.2 ± $10.8\%$. Most of the patients (66 patients, $76.7\%$) had HFpEF, while ten patients ($11.6\%$) had HFrEF and ten patients ($11.6\%$) had HFmrEF. The mean ejection fraction was 61 ± $5\%$, 45 ± $2\%$, and 33 ± $5\%$, respectively. Among patients with HFrEF, $90\%$ were treated with beta-blockers and $30\%$ with ACEI/ARB2 or ARNI. None of the patients received MRA or iSGLT2. ## 3.2. Outcomes Hospitalization for HF and the need for ambulatory intravenous diuretics were frequent, especially in patients with HF (Table 2). There were no differences in the hospitalization rate due to impaired renal function or in the need for RRT, which was needed in $30.4\%$ of the population. However, in patients with previous HF, hemodialysis was the primary RRT used (79,$2\%$), whereas in patients without HF, peritoneal dialysis or kidney transplantation were more frequently used ($$p \leq 0.008$$). The composite of all-cause death or need for RRT (Figure 1A) was more frequent in patients with previous HF. Patients with previous HF had almost twice the mortality compared to those patients with no HF history ($40.2\%$ vs. $22.3\%$; $$p \leq 0.005$$) (Figure 1B). A history of HF was independently associated with the composite endpoint (Table 3). ## Patients without HF History Of the 130 patients with advanced CKD and no history of previous HF, only 19 ($14.6\%$) developed HF during the 2-year follow-up period. Patients who developed HF were older (77.2 ± 7.4 vs. 71.2 ± 13.6; $$p \leq 0.007$$), and there were no differences in sex and cardiovascular risk factors except for a higher prevalence of diabetes mellitus ($68.4\%$ vs. $40.5\%$; $$p \leq 0.024$$). There were no differences in extracardiac and cardiac comorbidities. Medical treatment was similar, except for a higher use of insulin and anti-vitamin K anticoagulants in patients with HF onset (16.2 vs. $47.4\%$, $$p \leq 0.002$$, and 6.3 vs. $26.3\%$, $$p \leq 0.016$$, respectively). Of the patients who developed HF, 15 ($78.9\%$) required hospitalization due to HF, and 11 ($57.9\%$) required ambulatory intravenous diuretic treatment (Table 2). NT-proBNP levels were reported in 30 patients. It was significantly higher in patients who developed HF (3070 [1130–5888] vs. 658 [336–1760] pg/mL; $$p \leq 0.035$$). No differences in Troponin T levels ($$n = 20$$) were observed. The all-cause death rate was numerically higher (36.8 vs. $19.8\%$, $$p \leq 0.1$$). The composite of death or renal replacement therapy ($53.1\%$ of patients), hospitalization due to renal cause ($26.9\%$), and the need for renal replacement therapy ($32.3\%$) were similar between groups. ## 4. Discussion In this cohort of patients with advanced renal disease (stages 4 and 5), $40\%$ had a history of HF. The presence of previous HF identified a subgroup of high-risk patients, which was significantly and independently associated with the composite endpoint of all-cause hospitalization or the need for renal replacement therapy (HR $95\%$ CI 1.62 (1.04–2.52), $$p \leq 0.034$$). Nineteen patients without HF at baseline developed HF during the 2-year follow-up. These patients were older and more frequently had diabetes; all-cause death was numerically higher (36.8 vs. $19.8\%$, $$p \leq 0.1$$). The prevalence of HF in patients with end-stage kidney disease has been estimated to be between $35.8\%$ [10] and $44\%$ [13], similar to our study. It is worth noting that very few studies have analyzed this group of patients since studies have focused on patients on renal replacement therapies [14] or in less advanced CKD stages [3]. Patients with a history of HF were older and, more frequently, female. The prevalence of traditional cardiovascular risk factors was extremely high in our cohort, with $98.1\%$ of patients having hypertension and $86.6\%$ having dyslipidemia. More than half of the patients had diabetes mellitus, which was significantly higher in patients with HF ($70.1\%$). Although the prevalence we observed is higher than in other series [15], a similar rate of cardiovascular risk factors has been described in patients with advanced chronic kidney disease, particularly those requiring renal replacement therapy or those with diabetic kidney disease [16,17]. Older age and high prevalence of cardiovascular risk factors, particularly diabetes mellitus, might explain the higher prevalence of cardiovascular diseases in patients with previous HF. Non-cardiac comorbidities did not differ between the groups. Although patients with previous HF had a higher prevalence of coronary artery disease and diabetes mellitus, $76.7\%$ had HF with preserved ejection fraction. This high proportion of patients with HFpEF is consistent with previous studies, which have also reported a high prevalence of HF with preserved ejection fraction [18]. However, our findings contrast with other studies, in which HF with preserved ejection fraction accounted for only approximately $38\%$ of HF patients. It is worth noting, though, that the ejection fraction was not measured in almost $20\%$ of HF patients [10]. RAS inhibitor use was low in our series, with only $26.7\%$ of patients receiving it. In contrast to our data, a Swedish registry with 24,283 patients with HFrEF, nearly $10\%$ of whom had advanced CKD (stages 4 and 5), showed that $66\%$ used RAS antagonists [9]. Although RAS inhibitors have a class I indication in the latest HF guidelines [11], the same document advises using ACE inhibitors, angiotensin II receptor blockers, sacubitril/valsartan, and mineralocorticoid receptor antagonists are contraindicated or should be used with caution or seek specialist advice. However, in a recent review, Beldhuis et al. conclude that in patients with HFrEF and CKD stage 4, there is evidence of the safety and efficacy of SGLT2 inhibitors, and with less evidence, ACE inhibitors, vericiguat, digoxin, and omecamtiv mecarbil. There is a lack of data on efficacy and safety for any HFrEF therapies in CKD stage 5 (eGFR < 15 mL/min/1.73 m2 or dialysis) [19]. Finally, a recent study in patients with advanced and progressive CKD showed that discontinuing RAS inhibitors was not associated with significant between-group differences in the long-term rate of decrease in eGFR [20]. Thus, a more aggressive approach to using RAS inhibitors should be adopted, especially in patients with HF and reduced ejection fraction, where they have a class I level of evidence A [11]. Overall, patients with HF were a high-risk group, with frequent HF hospitalization and the need for ambulatory intravenous diuretics. This group had nearly four times more risk of having a new HF hospitalization or ambulatory endovenous diuretic treatment than patients without baseline heart failure. Little information is available on patients with advanced CKD. In the ARIC study 3, which included more than 14,000 patients with CKD, the relative risk of developing HF was 1.94 in patients with eGFR < 60 mL/min/1.73 m2 compared to patients with FG > 90 mL/min/1.73 m2. However, only $2.7\%$ ($$n = 403$$) had an eGFR < 60 mL/min/1.73 m2. In an analysis of three community-based cohort studies [21], the adjusted risk difference ($95\%$ CI) for HF was 4.6 (2.4, 6.7); $p \leq 0.001.$ However, again, only $2.8\%$ of patients had eGFR < 45 mL/min/1.73 m2. Kottgen et al. reported that the incidence of de novo HF was between 17 to $21\%$, similar to the $15\%$ of patients without HF at baseline that developed HF in our study. The only differences between patients who developed HF and those who did not were older age and diabetes mellitus. Therefore, patients with diabetes and older patients should be identified as extremely high-risk. All-cause death was numerically higher (36.8 vs. $19.8\%$, $$p \leq 0.1$$). However, this data should be interpreted cautiously as only 19 patients developed HF during follow-up. The composite endpoint of all-cause death and the need for renal replacement therapies was $66.7\%$ in the previous HF group compared with $53.1\%$, $$p \leq 0.046.$$ The presence of previous HF was independently associated with the composite endpoint in multivariable analysis (HR 95CI 1.62 (1.04–2.52), $$p \leq 0.034$$). Studies on mortality in patients with advanced CKD have focused on patients undergoing dialysis or requiring a kidney transplant. The two-year survival rate reported in Medicare patients with HF and end-stage renal disease that received dialysis or had a functioning kidney transplant was $60.8\%$ and $81.1\%$, respectively. This survival rate was lower than in patients without HF ($76.9\%$ and $92\%$, respectively) [10]. The mortality rate was also high in patients not undergoing renal replacement treatment. In the Swedish Register of patients with HF, the one-year mortality rate in patients with eFGR < 60 mL/min/1.73 m2 was about $23\%$, reaching $67\%$ in HFpEF patients at the 5-year follow-up [9]. In our study, the two-year survival rate in patients with and without previous HF was $59.8\%$ and $79.8\%$, which is higher than in patients without advanced CKD but lower than in patients already on renal replacement therapy. Although the use of any renal replacement therapy was similar between groups, the type of therapy used differed. Notably, in patients with previous HF in whom renal replacement was indicated, only $20.8\%$ were started on peritoneal dialysis. However, this method should be considered a first-line treatment in patients with HF [22]. Overall, this excess of risk highlights the need for specialized cardiorenal units, where cardiologists and nephrologists work together to improve the management and treatment of these patients [23,24]. Finally, previous studies showed that elevated NT pro-BNP and hs-TnT levels were significantly associated with cardiovascular events and higher HF risk [25,26]. Consistent with these studies, we found that NT-proBNP levels in patients with previous HF were significantly higher than those without HF. Moreover, patients who developed HF during follow-up also had significantly higher NT-proBNP levels. Nonetheless, only $40\%$ and $30\%$ of patients in our study had available NT-proBNP and US-troponin T levels, respectively. ## Limitations The main limitation of our study is that it was a retrospective study, which means that we relied on data collected for clinical purposes rather than for research purposes. This meant that some important data, such as cardiac biomarkers and echocardiography, were unavailable for some patients, which may have limited our ability to characterize the study population fully. Additionally, as a hospital-based registry, there is a risk of selection bias, as patients who were not considered candidates for renal replacement therapies due to age, frailty, or comorbidities may not have been included in our study. It is important to note that at the time of our study, the use of SLGT2 inhibitors for treating heart failure or chronic kidney disease was not yet approved. As a result, the number of patients in our study taking these medications was extremely low. Despite these limitations, we believe that our study provides valuable insights into the prevalence and clinical characteristics of heart failure in patients with chronic kidney disease and adds to the growing body of literature on this crucial topic. ## 5. Conclusions Patients with advanced CKD who are not on renal replacement therapy have a high prevalence ($40\%$) and incidence ($15\%$) of HF. Patients with a history of HF have a remarkably high prevalence of cardiovascular risk factors and cardiovascular comorbidities such as myocardial infarction or atrial fibrillation. The prognosis was poor, with a significantly higher composite of all-cause death or need for renal replacement therapy in patients with previous HF ($66.7\%$, vs. 53.1 %, HR ($95\%$ CI) 1.62 (1.04–2.52), $$p \leq 0.034$$). 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--- title: Polylactic Acid/Poly(vinylpyrrolidone) Co-Electrospun Fibrous Membrane as a Tunable Quercetin Delivery Platform for Diabetic Wounds authors: - Francesca Di Cristo - Anna Valentino - Ilenia De Luca - Gianfranco Peluso - Irene Bonadies - Anna Di Salle - Anna Calarco journal: Pharmaceutics year: 2023 pmcid: PMC10054567 doi: 10.3390/pharmaceutics15030805 license: CC BY 4.0 --- # Polylactic Acid/Poly(vinylpyrrolidone) Co-Electrospun Fibrous Membrane as a Tunable Quercetin Delivery Platform for Diabetic Wounds ## Abstract Diabetic wound infections (DWI) represent one of the most costly and disruptive complications in diabetic mellitus. The hyperglycemic state induces a persistent inflammation with immunological and biochemical impairments that promotes delayed wound healing processes and wound infection that often results in extended hospitalization and limb amputations. Currently, the available therapeutic options for the management of DWI are excruciating and expensive. Hence, it is essential to develop and improve DWI-specific therapies able to intervene on multiple fronts. Quercetin (QUE) exhibits excellent anti-inflammatory, antioxidant, antimicrobial and wound healing properties, which makes it a promising molecule for the management of diabetic wounds. In the present study, Poly-lactic acid/poly(vinylpyrrolidone) (PP) co-electrospun fibers loaded with QUE were developed. The results demonstrated a bimodal diameter distribution with contact angle starting from 120°/127° and go to 0° in less than 5 s indicating the hydrophilic nature of fabricated samples. The release QUE kinetics, analyzed in simulated wound fluid (SWF), revealed a strong initial burst release, followed by a constant and continuous QUE release. Moreover, QUE-loaded membranes present excellent antibiofilm and anti-inflammatory capacity and significantly reduce the gene expression of M1 markers tumor necrosis factor (TNF)-α, and IL-1β in differentiated macrophages. In conclusion, the results suggested that the prepared mats loaded with QUE could be a hopeful drug-delivery system for the effective treatment of diabetic wound infections. ## 1. Introduction Nowadays, diabetic wound/foot ulcer infections (DWI), common multifactorial long-term complications in diabetes mellitus, represent a substantial economic burden to patients and the healthcare system due to a significant impact on patient’s health, quality of life, and life expectancy [1]. Patients suffering from diabetes experience metabolic disorders that affect the normal wound healing process. As a consequence, DWI may take a longer time to heal, leading sometimes, to amputation of limbs and often loss of life [2]. The hyperglycemic environment, typical of DWI, promotes bacterial colonization and biofilm formation, attending to abnormal immune function [3]. The proliferation of bacteria drives the wound into a long-lasting inflammatory phase, which induces neutrophils and macrophages to continuously produce inflammatory cytokines and reactive oxygen species (ROS), leading to the overexpression of metalloprotease (MMP-2 and MMP-9). MMPs secretion is responsible for extracellular matrix degradation, which impairs fibroblast adhesion and keratinocytes migration, resulting in slow wound healing [4,5,6,7]. Standard DWI treatment includes surgical debridement and dressings to facilitate a moist wound environment and exudate control. Moreover, due to the complexity of DWI pathophysiology, additional therapies such as negative pressure wound therapy, biological dressing, and hyperbaric oxygen treatment are recommended to achieve rapid wound healing [8,9,10]. In recent years, the use of natural-derived bioactive molecules has gained a significant increase in the management of DWI due to their low toxicity, and multiple pharmacological activities [11,12]. Among these, quercetin (QUE) due to its antioxidants, anti-bacterial/antibiofilm, and anti-inflammatory properties, represents an interesting therapeutic option to explore [13,14,15]. It is well-known, in fact, that QUE can improve common wound healing by increasing fibroblast proliferation, while decreasing fibrosis and scar formation, as well as ROS levels and bacterial adhesion and proliferation [16,17,18]. Nevertheless, the poor water solubility of QUE hampers its bioavailability, limiting the clinical application of this potent dietary bioflavonoid. Therefore, the development of nanotechnology-based strategies able to augment the local drug delivery of QUE represents a promising approach for better DWI management [19,20]. In this scenario, advanced nanofibrous dressings are essential to ensure a neutral and safe wound environment, achieving a better and faster wound closure. Thanks to the large surface area, small pore size, and gas permeability, nanofibrous electrospun membranes can simulate the structure of extracellular matrix, propelling and promoting cell proliferation, differentiation, and anti-bacterial effects [21,22]. Several polymers have been used for electrospun membrane manufacture, such as Poly lactic acid (PLA), Polyvinyl Alcohol (PVA), Poly-caprolactone (PCL), Polyethylene Oxide (PEO), and Polyvinylpyrrolidone (PVP) [23,24,25,26,27]. PLA is Food and Drug Administration (FDA)-approved synthetic polymer widely used for pharmaceutical and biomedical applications [28,29]. PVP is another non-toxic, biodegradable and fast-dissolving hydrophilic polymer highly applicable for the fabrication of drug-delivery systems [30,31,32]. Despite their proper characteristics, their applications in wound healing are restricted. Therefore, in the present study, the favorable properties of PLA-PVP co-electrospun nanofibers (PP mats) were combined with the biological activities of QUE. Recently, Zhou et al. fabricated a novel electrospun nanofiber membrane consisting of PCL, chitosan oligosaccharides (COS), and Quercetin/Rutin, with a good antioxidant and antibacterial activity, as promising wound dressings and drug delivery carriers for wound management [33]. Moreover, Gallelli and co-workers evaluated both the clinical efficacy and safety of hyaluronic acid nano-hydrogel embedded with QUE and oleic acid in the treatment of lower limb skin wound in 28 patients with diabetes mellitus [34]. The synthetized nano-hydrogels demonstrated a statistically significant reduction in the wound healing time without adverse effects. In another study, Jee et al. fabricated an enhanced topical delivery system featuring a combination of highly skin-permeable growth factors (GFs), QUE, and oxygen to accelerate re-epithelialization and granulation tissue formation in diabetic wounds [35]. In this work, the release kinetic of PP nanofibers loaded with three different concentrations of QUE (namely, PP/Q5, PP/Q10 and PP/Q15 mats) was analyzed in simulated wound fluid (SWF), miming the wound environment solution at human body temperature. The biological effect in terms of antioxidant and anti-inflammatory capacity of released QUE was also evaluated on an in vitro-induced inflammatory environment mimicking diabetic ulcers. Moreover, the effect of QUE on the macrophage switch from the M1 to M2 phenotype has been analyzed. To the best of our knowledge, a suitable local delivery platform that simultaneously elicits the QUE beneficial effect on inflammation, macrophage polarization and biofilm maturation has been rarely reported. The results presented herein suggest that the newly fabricated mats containing both hydrophobic and hydrophilic properties can be successfully used to meet the requirements of an ideal wound dressing in the treatment of DWI pathology. Indeed, the demonstrated biomimetic multifunctional features due to the presence of two unmixed polymers allow an ideal moist environment, simultaneously controlling biofilm formation at the wound site, promoting re-epithelization and tissue regeneration, eliminating, at the same time, the need for frequent dressing changes due to a sustained QUE release over a prolonged period of time. ## 2.1. Materials Polylactic acid (PLA) (Ingeo 4032D) with 0.7 mol% L-isomer, Mw = 2.1 × 105 g mol−1 and the polydispersity (PDI) = 1.7 was supplied by NatureWorks LLC. Poly(vinyl pyrrolidone) $K = 90$ (PVP, average Mw = 360,000 Da) was purchased from Sigma-Aldrich Chemie GmbH (Schnelldorf, Germany). Chloroform (CHL), N,N-Dimethylformamide (DMF), ethanol (EtOH) and acetone with a purity ≥ $99.8\%$, Quercetin (QUE), Lipopolysaccharide (LPS, 8630), 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), phorbol 12-myristate 13-acetate (PMA, P8139), and IFN-γ (SRP3058) were purchased from Sigma-Aldrich (Milan, Italy). Staphylococcus aureus (ATCC 29213) and *Pseudomonas aeruginosa* PAO1 (ATCC® BAA-47™) were purchased from the American Type Culture Collection (ATCC, Milan, Italy) and cultured following the ATCC’s guidelines. Human dermal fibroblasts (HDF) and human leukemia monocytic (THP-1) cell lines were obtained from ATCC and cultured following the ATCC’s guidelines. HDF were cultured in Dulbecco Modified Eagle Medium (DMEM) supplemented with $10\%$ Fetal Bovine Serum (FBS), 2 mM L-glutamine, 100 IU/mL penicillin and 0.1 mg/mL streptomycin at 37 °C in $5\%$ CO2 atmosphere. THP-1 were maintained in RPMI 1640 medium supplemented with $10\%$ heat-inactivated FBS, 100 ng/mL of streptomycin, 100 U/mL of penicillin, and 2 mM L-glutamine. Mycoplasma testing was performed regularly to check for cell contamination. ## 2.2. Preparation of PP/Qx Mats To obtain PP/Qx mats, PLA and PVP solutions containing different amounts of QUE were prepared. Neat PLA solutions (coded as PLA) were prepared by dissolving $10\%$ wt. PLA in chloroform/dimethylformamide (CHL/DMF, $\frac{80}{20}$ v/v). Neat PVP solutions (coded as PVP) were prepared by dissolving $15\%$ wt. PVP in ethanol. QUE loaded fibers were prepared with different amount of QUE with respect to the polymer mass (coded as PP/Q5, PP/Q10, and PP/Q15, respectively). First, QUE was dissolved in solvents, DMF for PLA ($5\%$ w/w–$10\%$ w/w–$15\%$ w/w respect to PLA) and EtOH for PVP ($3.3\%$ w/w–$6.6\%$ w/w–$10\%$ w/w respect to PVP); then the PLA polymer solution in chloroform and PVP powder were added to each QUE-based solution, respectively. All the solutions were stirred before use for at least 6 h. Each solution was loaded in a syringe and both of them were electrospun at the same time with NANON01 equipment (MECC Co., Ltd., Fukuoka, Japan), using a dual jet nozzle and a plate collector at room temperature and $10\%$ relative humidity. After optimization of the process parameters for each solution, the flow rates for each solution were fixed at 2 mL h−1. The applied voltage and the distance between the dual jet nozzle and the collector, which was covered with aluminum foil, were adjusted to 25 kV and 30 cm, respectively, for both solutions to obtain defect-free fibers for further characterizations. To evaporate any residual solvent, electrospun fibers were kept under a fume hood for 24 h prior to characterization. ## 2.3. Physico-Chemical Characterization of the Membranes Scanning Electron Microscope (SEM). The morphology of the membranes was evaluated using a FEI Phenom Desktop SEM (Eindhoven, The Netherlands). Before analysis, the samples were sputtered/coated with an Au-Pd alloy using a Baltech Med 020 Sputter Coater System and then mounted on aluminum stubs. The average fiber-diameter distribution was analyzed using ImageJ software (NIH, Bethesda, MD, USA). By using energy-dispersive X-ray spectroscopy coupled with scanning electron microscopy (SEM-EDX), the atomic percentages were obtained. Fourier-Transform Infrared Spectroscopy (FTIR). Chemical composition of membranes was investigated by means of FTIR coupled with attenuated total reflectance technique (ATR-FTIR). The spectra were acquired in the spectral region between 4000 and 400 cm−1. The analysis was performed using Origin software (Origin2020, OriginLab Corporation, Northampton, MA, USA). QUE spectrum was considered as positive control. Water contact angles (WCA). The water contact angles of the fibrous materials were measured using a FTA1000 (First Ten Angstroms, Inc., Newark, CA, USA) equipment. Drops of distilled water with a volume of 10 μL were deposited on the surface of the test specimens. The mean contact angle value was determined after averaging at least 5 measurements for each specimen. Stability test. The degradation study was determined by in vitro tests run in distilled water (pH 7). Small samples of PP and PP/Qx mats (5 mm × 5 mm) were immersed in 1.5 mL of medium and at different time intervals removed for analysis. Samples were kept under a fume hood for 24 h prior to morphological investigation by scanning electron microscopy. Mechanical analysis. Mechanical properties of the obtained mats were analyzed by tensile tests performed at room temperature by using a 5564 Instron equipped with a 100 N cell load, at a crosshead speed of 5 mm/min. Tests were performed on 3 rectangular-style specimens cut from the electrospun mats. A micrometer screw gauge was used to determine the thickness of each sample (in the range between 30 and 40 µm). ## 2.4. In Vitro QUE Release In vitro release of the QUE was investigated using static Franz diffusion cells (diffusion area 2.54 cm2, volume 12 mL) at 32 ± 0.5 °C to mimic skin surface temperature. Circular pieces of QUE loaded nanofiber mats (ø 1.6 cm) were mounted into a regenerated cellulose membrane (Spectra/Por® MWCO 6–8 kDa, Spectrum Laboratories, Inc., Rancho Dominguez, CA, USA) and placed between the donor and receptor donor compartments. The receptor medium was simulated wound fluid (SWF, $2\%$ BSA, 0.02 M calcium chloride, 0.4 M sodium chloride, 0.08 M tris(hydroxyl) aminomethane in deionized water, pH 7.5 adjusted using dilute HCl). At predetermined times, the sink conditions were met by replacing the amount of the solution removed from the cell by the fresh SWF of the same volume. The cumulative amount of QUE released in the medium was detected by HPLC-UV, as reported by Di cristo et al. [ 36]. Residual QUE was determined by immersing mats in chloroform/methanol solution (1:1 v/v). The amount of QUE was determined using HPLC-UV as reported before. ChemStation software 4.03 27 January 2020 (Agilent Technologies, Milan, Italy) was used as System control and for data acquisition. Finally, the QUE release data were fitted to Korsmeyer–Peppas semi-empirical mathematical model, using Equation [1] [37,38] [1]QUEtQUE∞=k×tn where QUEt/QUE∞ is the fraction of QUE released at time t, k represents the release rate constant and consider the structural and geometric characteristics of the carrier, and n is the release exponent that indicates the drug-release mechanism. ## 2.5. Biofilm Analysis The effect PP/QUE membranes on biofilm formation were evaluated by crystal violet (CV) biofilm assay as described by Di Salle et al. with some modifications [39]. Briefly, mats with similar weight were sterilized by 15 min exposure to UV radiation and then covered with 750 μL of liquid medium broth containing S. aureus and PAO1 (1 × 107 CFU/mL). Bacteria were incubated at 37 °C in a humid atmosphere until 16 h. PP mat incubated in liquid medium broth was used as a negative control, whereas 750 μL of PAO1 (1 × 107 CFU/mL), and S. aureus (1 × 107 CFU/mL), were used as positive controls. After 6, 12 and 24 h, the surface-adhered biofilm was gently washed with sterile PBS, air-dried for 30 min, stained with $0.1\%$ w/v CV and finally dissolved in $96\%$ ethanol. The absorbances at 570 nm (OD570) were measured using a microplate reader (Cytation 3, AHSI, Milan, Italy). Biofilm-viable bacterial cells were determined using the LIVE/DEAD® Biofilm viability kit (Molecular Probes, Life Technologies Ltd., Milan, Italy), according to Bonadies et al. [ 40]. Images were acquired by using a Cytation 3 microscope (AHSI) equipped with a 10× objective. Viable bacteria emit green fluorescence (Ex/Em $\frac{510}{530}$) due to the MycoLight Green fluorophore, whereas the dead ones, whose cellular membranes are damaged, incorporate propidium iodide and emit red fluorescence (Ex/Em $\frac{600}{660}$). ## 2.6.1. Macrophages Polarization to M2 Phenotype The PMA-differentiated THP-1 macrophages were obtained as described by Wang et al. [ 41]. Briefly, cells were seeded on plates or Petri dishes at 5 × 105 cells/mL and incubated for 48 h with 50 ng/mL of phorbol 12-myristate 13-acetate (PMA, Sigma, Milan, Italy). Then, the PMA-differentiated THP-1 macrophages were washed with PBS and further treated with 100 ng/mL and 20 ng/mL IFN-γ (Sigma) for 4 h to induce M1 phenotype macrophages [42]. Then, M1 macrophages were cultured for 3 days in presence of PP/Qx conditioned medium. ## 2.6.2. Enzyme-Linked Immunoabsorbent Assay (ELISA) Cytokines released in macrophages culture supernatant were quantified by ELISA technique according to Valentino et al. [ 43]. Antibody specific for IL-6, IL-12, or IL-10 were added to each well in 96-well plate and incubated at 4 °C overnight. Avidin conjugated Horseradish Peroxidase (HRP) solution was added into each well, incubated at room temperature for 30 min in orbital shaker and absorbance was measured by the Cytation 3 Microplate Reader at 450 nm. ## 2.6.3. Real-Time Quantitative PCR (RT-qPCR) Macrophage polarization and anti-inflammatory activity was evaluated by Real-Time Quantitative PCR (RT-qPCR) according to the manufacturer’s protocols. For RT-qPCR, total RNA was extracted from cells through TriFast (EuroClone, Milan, Italy), and cDNA was synthesized using Wonder RT cDNA synthesis Kit (EuroClone). Then, gene expressions of TNF-α, IL-1β, CCL18, CD206, IL-6, IL-12, and IL-10 were evaluated by 7900 HT fast Real-Time PCR System, (Applied Biosystem, Foster City, CA, USA) with SYBR Green PCR Master mix (EuroClone). Gene expression was quantified by the 2−ΔΔCt method and normalized against 𝛽-actin used as the internal reference gene. Results were expressed as fold changes versus control. Primers used for RT-qPCR are reported in Table S1. ## 2.6.4. Human Dermal Fibroblasts (HDFs) Proliferation and Migration Assays To mimic the hyperglycemia environment, HDFs were cultured in DMEM supplemented with normal (5.5 mM) or high-glucose (25 mM) concentrations as reported by Sorooshian et al. [ 44], whereas cells cultured in 5.5 mM glucose-containing medium supplemented with 25 mM mannitol (as an osmotic control) were used as controls (CTL). The proliferation and migration of HDFs incubated with PP/Qx mats were investigated using the insert systems (Corning, Milan, Italy). For proliferation, cells were incubated overnight in low-serum media ($0.1\%$ FCS) prior to conducting the experiment at 37 °C with $5\%$ CO2. Then, dermal fibroblasts were subsequently exposed to media containing 5 mM or 25 mM glucose concentrations in presence of PP/Qx membrane for 24, 48 and 72 h. 3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide (MTT) assay was carried out as reported by Calarco et al. [ 45]. Cells Absorbance was measured at 570 nm using a microplate reader (Cytation 3; AHSI). For scratch migration assay, cells were seeded on a 96-well plate (8 × 103/well) and cultured to $90\%$ confluence using the above-described protocol. Then, a standardized scratch wound was inflicted (T0) using sterile pipette tips (200 µL) [40]. Following PBS wash, cells were incubated with PP/Qx mats in 5 mM or 25 mM glucose containing medium for 24 h (T24). $0.1\%$ mM mitomycin c (Merck Millipore, Milan, Italy) as a proliferation inhibitor was added. Fibroblast migration was photographed using an inverted phase-contrast microscope (Zeiss, Milan, Italy) and the percentage of wound closure was calculated according to the following equation: [2]Wound closure (%)=A0− AtA0×100 where A0 represent the wound area recorded at h 0 and At the wound area recorded at h 24 measured with ImageJ software. Experiment was conducted in triplicate. ## 2.7. Intracellular Antioxidant Activity Total SOD-like and CAT activities were evaluated as reported by Valentino et al. [ 43] according to the manufacturer’s protocol. The mRNA levels of the oxidative markers superoxide dismutase 1 (SOD1) and catalase (CAT) were quantified by qRT-PCR as reported in Section 2.6.3. ## 2.8. Statistical Analysis Student’s t-test was used for the quercetin release. For antimicrobial investigations assay, and quantitative real-time PCR, one-way analysis of variance (ANOVA) with Tukey’s post hoc test for statistical comparison were used. The difference was considered as statistically significant when $p \leq 0.05.$ GraphPad Prism version 6.01 statistical software package (GraphPad, San Diego, CA, USA) was used to analyze all data. Results were expressed as mean ± standard deviation (SD). ## 3.1. Characterization of Electrospun Membranes The use of electrospun fibers for drug delivery is widely investigated and one of the major challenges still remains to realize mats with tunable properties in order to have a more precise control of drug delivery and to focus on target applications [46]. Multi-spinneret electrospinning represents itself an excellent method to fabricate multiphase materials with specific and different characteristics such as degradation rate, mechanical properties, diffusivity and so on by utilizing the different properties of each component [47]. Du et al. prepared a bicomponent mat for wound healing by using PVA to keep moist environment promoting cell adhesion and proliferation and PCL to maintain structural integrity [48]. In another study, Scaffaro et al. reported the preparation and characterization of PCL/PLA co-mingled mats and their stability in three different buffered media (pH 4, pH 7 and pH 10): at the highest pH, the fastest degradation rate was observed, whereas in the alkaline medium, PLA was more sensitive than PCL [49]. Green tea extract (Cat) was incorporated using the double-nozzle electrospinning technique in gelatin (Gel)/PLA [50]. The authors demonstrated that the presence of Cat increased the diameter of fibers, whereas it decreased the contact angle of samples. Moreover, Cat elicits antibacterial activity toward S. aureus and E. coli, increasing the diameter of the inhibition zone. Finally, the hydrophilic nature of the Gel-Cat/PLA-Cat fibers improves the L929 fibroblast attachment, demonstrating a potential application of fabricated membranes for wound dressing. Our previous work demonstrated that QUE-loaded PLA nanofibers were able to counteract biofilm maturation in an oral acid environment (below 5.5) [40]. Moreover, it was demonstrated on an in vitro induced inflammatory model, that the released QUE showed a strong antioxidant and anti-inflammatory effect, suggesting that PLA-QUE fibers could be delivered into the periodontal pocket to simultaneously control inflammation and oral microbiome maturation. The results highlighted how PLA-QUE could be used as promising local adjuvants in periodontal disease. Despite the good properties demonstrated by our previous materials, wound dressing needs to maintain adequate dampness and a shield around the wound. For this reason, in the present work, PVP was chosen as the second polymer in addition to PLA to realize bi-component membranes because of its ideal properties such as inertness, chemical stability, no or low toxicity, lack of irritation to biological systems, biocompatibility and processability [51]. A hydrophilic nanofiber surface will be helpful for cells attachment and could provide a moist environment to accelerate drug permeation and the wound healing. However, a hydrophilic nanofiber surface may result in poor fiber stability. Therefore, the independent use of both polymers permits to obtain a bi-component mat with a sustainable degradation able to guarantee a different drug release behavior and improved membrane stability. Hence, PP electrospun fibers loaded with different concentrations of QUE were prepared. As reported in Figure 1, the micrographs of electrospun mat reveal defect-free fibers, uniform and quite homogenous in size for all their length except for PP sample that shows some beaded nanofibers. In particular, it is possible to observe a bimodal distribution of the diameter of fibers (one < 1 μm and another > 1 μm) related to the presence of two different fibers (one is PLA-based and the other is PVP-based) for each composition. As reported in our previous paper [30], the QUE-loaded PLA fibers have a diameter distribution centered at 0.4 ÷ 0.6 μm; for this reason, it is plausible to assume that the lowest diameters correspond to the PLA fibers, whereas the highest ones correspond to the PVP fibers. By adding QUE in PP samples, the morphologies of fibers became uniform and homogeneous in size above all for PP/Q5 and PP/Q10 samples. As expected, since the co-mingled mats are a microscopic physical mixture of non-interactive fibers, the EDX results (Figure S1) and the FTIR-ATR spectrum showed bands that are typical of all components. From the EDX analysis, the increasing amount of carbon with respect to oxygen by adding QUE is noticeable, whereas in the FTIR-ATR spectra, the presence of QUE is not detectable because the peaks of PLA and PVP and QUE overlap in the characteristic region (1500–1600 cm−1) (Figure 1C). However, the analysis proves the existence of a uniform co-mingled system as in the portion analyzed there are no zones with the presence of only one of the two polymeric phases. The representative mechanical response of each sample (Figure S2A) exhibits a first linear segment where low deformation occurs due to the random and interlacing arrangement of the fibrous network. In fact, fibers act as an elastic material and undergoes uniform stretching throughout the length; thereafter, the formation of a neck region is noticeable; fibers breakage at the lateral side of the sample occurs (Figure S2B). This failure area enlarges with the strain due to the progressive breaking of the fibers until to failure. The mechanical behaviour recorded is similar for all compositions, by adding QUE the stress and deformation at peak slightly decrease and only at high additive concentration the stress at peak is reduced. These results can be explained considering a plasticizing effect of QUE; however, taking into account the composition and morphology of the mat, they require a more thorough investigation elsewhere. ## 3.2. Surface Wettability and Drug Release Surface membrane wettability can affect the interaction between the biological fluids and the material surface [52]. Indeed, passage of the nutrients to the wound bed and membrane biocompatibility could be improved by material wettability. Furthermore, humid environment around the wound bed accelerates tissue restoration, alleviates pain and resists microbial attack [53]. The water contact angles (WCA) measurement confirmed the co-existence of the two different polymer matrices with opposite affinity for water (Figure 2A). It is well known that values of contact angles ≤ 90° are relate to hydrophilic surface, contact angles > 90° corresponding to hydrophobic surfaces and contact angle values > 150° are consistent to super-hydrophobic surfaces [54]. It is possible to observe for PLA neat membrane an initial WCA value of 130° ± 2° that did not change significantly by the time thus confirming a hydrophobic character. Whereas for PVP neat membrane the strong hydrophilic character is noticeable as soon the water drop is in contact with the surface since it is immediately absorbed. As PP membrane, the WCA value has an initial value of 124° ± 3° that goes to 0° in almost 2 h. The decreasing trend in water contact angles indicates that surface wettability of co-mingled mat appears as a hydrophobic one but by the time, it is strongly affected by the presence of PVP. On the contrary, for PP/Qx samples, WCA values start from 120°/127° and reach 0° in less than 5 s, indicating the hydrophilic nature of these samples. By the morphological analysis of wet surfaces (Figure 2B), after 60 s of contact with the water drop, it is possible to detect for PP samples the PLA fibers and the partially fusion of PVP fibers (Figure 2B). This behaviour is more evident for the PP/Q15 sample where, due to its solubility, the PVP phase cover the surrounding PLA fibers. This behavior is accountable to the presence of hydrophilic PVP and QUE affecting the overall comportment of the mat. In fact, the presence of quercetin inside the PLA matrix does not affect greatly the hydrophobic and stable behaviour of the membrane (WCA values of PLA/Qx membranes are in the range 120° ÷ 130°). The presence of PVP fibers inside the membrane, instead, reduces the WCA value by forming a compact phase surrounding PLA fibers and the additional presence of QUE amplify this behaviour due to its amphiphilic character [55]. Since wounds exhibit different extents of exudation, it is expected that wound healing process can be achieved by combining swelling, erosion and subsequent drug diffusion kinetics as part of the controlled drug release mechanism. In fact, most of the recently researched materials intended for wound dressings (either natural or synthetic) release incorporated drugs by a combined mechanism of either two or three above mentioned principles [56,57]. Based on the literature data, PLA has a low water absorption capacity, due to the large number of hydrophobic groups in the chemical structure, which develop strong intermolecular hydrogen bonds between the PLA molecules. Consequently, their availability to form hydrogen bonds with water ensures that the detachment of the PLA molecules rarely takes place and occurs very slowly. However, the addition of PVP, which contains a large number of oxygen functional groups, leads to increased polar groups. Interaction of water with the functional group of PVP conduces to disintegration of molecular chains of the polymer. This behaviour was investigated by a stability test in aqueous medium. The morphological analysis of mats after immersion in water at pH7 for different time intervals. ( Figure S3) revealed that the PVP fibers disappear; in fact, a monomodal distribution of diameters is noticeable. Only small residues of PVP are visible among fibers. The residual fibers, corresponding to PLA, as confirmed by spectroscopy (Figure S4), kept their original morphology and homogenous surface without any evidence of deterioration. In vitro drug release profiles of PP/Q5, PP/Q10 and PP/Q15 mats were evaluated in simulated wound fluid (SWF) at human body temperature. As depicted in Figure 3A, all samples exhibited a strong initial burst release, followed by a constant and continuous QUE release. In comparison to the previous reported mats loaded with QUE [40], the use of PVP accelerates the release rate in the initial stage mainly for the PP/Q15, followed by PP/Q10 and PP/Q5. In particular, PP/Q15 exhibited ~$33\%$ of QUE release in the first hour, corresponding to almost 16 µM, and reaching a plateau at the end of the experiment at ~37 µM (about $75\%$ of QUE). As reported by Yu et al. [ 58] this behaviour can be attributed to the high PVP hydrophilicity. Indeed, the increase in the polymer–solvent interactions produce polymer matrix volume enhancement, which will ultimately result in the loosening of the polymer chains, causing the release of the bioactive molecules. The reported release data of PP/Q5, PP/Q10 and PP/Q15 mats fitted the Korsmeyer–Peppas semi-empirical mathematical model, generally used to describe the drug release from polymeric nanofibers [59]. As showed in Table 1, a typical Fickian diffusion mechanism of QUE from PP fibers was identified by a value of the release exponent ≤ 0.45. This kind of release kinetic is essential in wound healing treatment, to both reduce the possibility of biofilm maturation and progression and provide an initial QUE concentration sufficient to elicit antioxidant and anti-inflammatory effect. Then, the sustained release throughout the experimental period will provide a good environment over the long term to obtain a beneficial effect. The release profile is confirmed by membranes morphology after 6 h of immersion in SWF (Figure 3B). SEM observation reveals that although the membranes retain their fibrous structure, the fibers distribution is varied (monomodal distribution centered at lowest diameters), showing that the PVP is completely dissolved after immersion. ## 3.3. Antibiofilm Activity Diabetic wounds are susceptible to bacterial colonization, leading to systemic infection, which delays the wound healing process, resulting in prolonged inflammation [60]. To be an effective wound dressing, a nanofibrous mats have to efficiently protect the wound against the bacteria growth and infections, providing suitable wound breathing and also efficient handling of wound exudates and eventually accelerate the wound healing process [61]. To ascertain the antibiofilm properties of PP/QUE membranes, the S. aureus and P. aeruginosa (PAO1) strains were used. These biofilm-producing bacteria play an important role in cutaneous chronic infected wounds. Two different biofilm analysis tests were used: a Crystal violet biofilm formation assay and a Live/Dead Bacterial Viability assay. Inhibition of biofilm development was assessed at different incubation times (6–12–24 h) using PAO1 and S. aureus bacteria in order to evaluate quercetin’s effectiveness. As shown in Figure 4, PP/Qx mats membranes inhibited the formation of biofilms in both bacterial strains in a dose-dependent manner. A significant reduction ($p \leq 0.001$) in biofilm formation was observed already after 6 h of incubation, in particular PP/Q15 membrane induced a reduction of about $47\%$ and $60\%$ in PAO1 and S. aureus, respectively. Notably, after 24 h of incubation PP/Q15 strongly reduced biofilm development in both bacterial strain, exhibiting the maximum effect, with a reduction of about $56\%$ against PAO1, and $73\%$ against S. aureus (Figure 4A,B). These results are in line with the data of J. Ouyang et al. [ 62], which reported that QUE markedly impacted on PAO1 biofilm formation at a concentration of 8–64 μg mL−1. Moreover, Jin-Hyung Lee et al. [ 63] reported the antibiofilm activity of QUE against three different strains of S. aureus already at a very low concentration (1 μg mL−1). The susceptibility of PAO1 and S. aureus to QUE-loaded mats was further evaluated via the Live/Dead BacLight Bacterial Viability Kit. This assay allows to differentiate between live and dead cells thanks to propidium iodide staining (red), able to selectively enters damaged bacteria membrane, whereas the fluorescent dye Syto9 (green) penetrates the membrane in both live and dead bacteria. As shown in Figure 4C,G, PP membranes permitted unperturbed biofilm formation, with a weak live/dead cell ratio, indicative of a bacterial population in stationary phase growth. Changes in viability of biofilm formed by PAO1 (Figure 4D) and S. aureus (Figure 4H) were found with PP/Q5 membrane respects to PP. The biofilm formed by both bacterial strains on PP/Q10 membranes (Figure 4E,I) presents a decrease in biofilm mass/architecture, with a substantial proportion of dead cells. Notably, biofilm formed on PP/Q15 mat (Figure 4F,J) showed the highest live/dead cell ratio respect to PP membranes for both the microorganisms analyzed, with a drastically altered biofilm architecture. These qualitative findings confirmed the inhibitory effect of the new synthesized mats on the biofilm formation as well as their ability to induce bacteria cell membrane damage. ## 3.4. QUE-Loading Membranes Modulate the Macrophage Polarization Wound healing is a very orderly and highly controlled process that requires the integration of complex cellular and molecular events characterized by distinct but overlapping phases: homeostasis, inflammation, cell proliferation, cell migration, angiogenesis and re-epithelialization [64]. During the initial phase, the role of macrophages is essential both to eliminate non-functional host cells and bacteria and create a favorable environment for tissue regeneration and repair [65]. Two distinct types of macrophages can be recognized: M1 macrophages, which function as pro-inflammatory mediators, and M2 macrophages, which act as natural feedback regulators from M1 macrophages. Based on their biological functions and phenotypes (secreted cytokines and surface markers), M2 can be further classified into four subtypes, i.e., M2a, M2b, M2c, and M2 [66,67]. M1-type activation is strictly related to ROS upregulation resulting in the production of pro-inflammatory cytokines (e.g., interleukin IL-6, tumor necrosis factor (TNF)-α, and IL-1β) [67]. Conversely, the activation of M2-polarized macrophages induces the secretion of anti-inflammatory cytokines, such as interleukin (IL)-10, and transforming growth factor-β (TGF-β), which leads to anti-inflammatory effects [68]. The macrophage M2a and M2c subtypes are both considered pro-healing and pro-remodeling. Their presence induces fibroblast and keratinocytes migration and proliferation, as well as the recruitment of endothelial stem cells leading to the development of granulation tissue and neovascularization. Therefore, in order to obtain a rapid wound healing process, the polarization of macrophages to anti-inflammatory M2 phenotype is necessary. Several studies report the potential activity of QUE in improving common wound healing by increasing fibroblast proliferation, while decreasing fibrosis and scar formation. Fu et al. showed that QUE was able to modulate the polarization of macrophages from M1 to M2 phenotype accelerating wound healing in the condition of diabetes [69]. In another study, Kim and coworkers demonstrated that QUE supplementation to high-fat-diet-fed C57BL/6 mice decreased the levels of inflammatory cytokines (TNFα, IL-6) and increased that of the anti-inflammatory cytokine (IL-10). Moreover, the hepatic inflammation reduction was accompanied by the upregulation of M2 macrophage marker genes (Arg-1, Mrc1) and downregulation of M1 macrophage marker genes (TNF-α, iNOS) [70]. In order to investigate the effect of PP/Qx on macrophage polarization, LPS/IFN-γ stimulation was used to mimic the biological microenvironment of body in responses to injury inducing M1 macrophage polarization [71]. As shown in Figure 5A, LPS/IFN-γ stimulated THP-1 cells strongly enhanced TNF-α and IL-1β expression (3.3- and 1.9-fold, respectively), whereas no significant expression of CCL18 and CD206 genes as M2 markers was detected, indicating the successfully polarization of the macrophages to M1 phenotype. ELISA results (Figure 5B) showed that the production of pro-inflammatory cytokines (IL-6 and IL-12) secreted from macrophages after LPS/INF-γ stimulation was significantly higher than that of the control group. As the QUE contents increased, a release reduction in these cytokines was observed in the cell culture supernatants, whereas the secretion of IL-4 and IL-10 increased. Accordingly, the expression levels of IL-6 and IL-12 in LPS/INF-γ stimulated cells were dramatically reduced in presence of PP/Qx membranes (relative to the housekeeping gene), whereas the anti-inflammatory factor IL-10 was significantly higher in QUE-treated groups than those in the control group (Figure 5C). As expected, the ability of QUE to modulate the anti-inflammatory response trigging macrophage polarization in the M2 phenotype was more evident in the presence of PP/Q15 with respect to PP/Q10 and PP/Q5. These results together suggest that PP/Qx membranes could promote macrophages polarization to M2 macrophages creating a microenvironment prone to promoting diabetic wound healing. With the purpose to obtain vascular tissue regeneration, Gui and colleagues manufactured a polycaprolactone (PCL) vascular graft incorporated with quercetin (PCL/QCT graft) [72]. In vitro studies demonstrate that released QUE was able to reduce the expressions of pro-inflammatory genes while increasing the expressions of anti-inflammatory genes in macrophages. Furthermore, the in vivo implantation in a model of rat abdominal aorta replacement led to the endothelial layer formation along the lumen of the vascular grafts at four weeks. More importantly, the presence of QUE stimulated the infiltration of a large amount of M2 phenotype macrophages into the grafts. Together, the reported data corroborated the hypothesis that the release of QUE may modulate the inflammatory microenvironment improving vascular tissue regeneration and remodeling in vascular grafts. Croitoru et al. discovered, via electrospinning, novel micro-scaffold matrices with triggered delivery capacity [73]. These fibrous scaffolds, based on PLA and graphene oxide (GO), were able to release QUE much faster (up to 8640 times compared with traditional drug-release approaches) when an appropriate electric field is applied. The QUE release from the PLA/GO matrix stimulated the production of IL-6 in fibroblast cells, which could be linked to an acute inflammatory response. ## 3.5. QUE Restores HDF Cells Proliferation and Migration under Hyperglycemic Condition Glucose-rich environment typical of diabetic status leads to a reduction in collagen synthesis, growth factor production, migration and proliferation of fibroblast and keratinocyte. Moreover, a continuous release of pro-inflammatory cytokines induces fibroblasts to secrete excess matrix metalloproteinases (MMPs) causing an imbalance between MMP (prevalently MMP-1 and MMP-8) and tissue inhibitory metallic proteinase (TIMP). This dysregulation results in the breakdown of collagen components and reduction in tissue mechanical strength [74]. In fact, dermal fibroblasts proliferate and migrate in the wound bed to produce collagen-rich matrix providing a scaffold for the migration of inflammatory cells [75,76]. Non-healing wounds associated with diabetes exhibit an interruption in the normal healing process. Several studies report that fibroblast cells isolated from diabetic foot ulcer patients showed impaired proliferation and migration suggesting dysregulated functional activity of fibroblasts in diabetic status [77]. Moreover, diabetes-derived dermal fibroblasts exhibited a reduced capacity to produce extracellular matrix proteins. In addition, the restoration of the epidermal barrier is compromised by the impair of keratinocytes proliferation and migration [78]. To mimic the hyperglycemic state typical of diabetes, dermal fibroblasts were cultured in media with a high concentration of glucose (25 mM). As shown in Figure 6A, fibroblast proliferation is dramatically reduced (about 1.3-fold) in high-glucose condition with respect to cells cultured in the presence of QUE at all points tested. The obtained results are in line with previous studies, which showed that free radicals generated by hyperglycemia delay cell replication time, triggering cell-cycle abnormalities independent of the osmotic mechanism [79,80,81,82]. Evidence suggests that antioxidants, such as QUE, might revert high glucose-impaired proliferation of HDFs possibly through a reduction in free radicals and activation of endogenous antioxidant systems via genetic modulation [83]. To confirm the involvement of ROS in the functional impairment of HDFs, the antioxidant effect of PP/Q15 was investigated. The expression of the anti-oxidative genes superoxide dismutase (SOD) and catalase (CAT) were analyzed by qRT-PCR. As shown in Figure 6B-C, high-glucose medium significantly induces a downregulation of both SOD1 and CAT with respect to cells cultured in normal glucose-containing medium. Interestingly, pre-treatment with PP/Q15 results to a consistent increase in the expression of these genes, confirming ROS involvement in high glucose-induced impairments in HGFs. Wound-healing assay demonstrated that under the normal condition, the untreated cells migrate healing the wound after 24 h (Figure 6C). In contrast, the presence of high glucose concentration induced no cell migration toward the center with a significant reduction ($p \leq 0.001$) in wound closure. As expected, the cell migration rate under high-glucose concentration was accelerated in presence of PP/Q15 mat. In particular, released QUE promoted a significant ($p \leq 0.001$) migration of cells with a recovery of wound closure of about $89\%$ respect to $26\%$ of high-glu cells (Figure 6C). Mi et al. demonstrated that QUE obtained from O. falcata promotes both the proliferation and migration of fibroblasts, inhibiting pro-inflammatory cytokine secretion. Moreover, mice treated with QUE showed a restored dermal structure with high content of collagen fiber [84]. In another study, Irfan et al. showed a synergistic effect of human-umbilical-cord-derived MSCs and bioactive compounds of M. azedarach in treating cold burn wounds in both in vitro and in vivo wound models [85]. Preconditioned cells with 20 μM of QUE or Rutin, the main bioactive components of M. azedarach, enhance wound healing by reducing the inflammation, mitigating oxidative stress and enhancing neovascularization. Moreover, histological examinations revealed enhanced regeneration of skin layers along with hair follicles in the quercetin group. Taken together, the reported results reveal the ability of prepared mats to recover the capability of fibroblasts to migrate toward the wound and fill the gap, increasing the wound contraction also in the presence of hyperglycemic condition. ## 4. Conclusions Impaired wound healing represents one of the most costly and disruptive complications in patients affected by diabetes mellitus, leading to extended hospitalization and limb amputations. In the present study, PLA-PVP-based mats loaded with quercetin were successfully prepared using the dual-jet electrospinning technique. The results of the SEM evaluation confirmed the formation of nanostructured and defect-free fibers. The fabricated fibers also exhibited a desirable wettability and biphasic QUE release with a rapid burst in the first hours, followed by a sustained release for a prolonged period. Antibiofilm studies showed that the mats prepared had good antibiofilm properties against PAO1 and S. aureus. Furthermore, the adopted formulation showed a significantly reduced toxic effect on dermal fibroblasts, and cell migration assays showed an increased migration of cells to the wound site. 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--- title: The Impact of a Lockdown for the COVID-19 Pandemic on Seasonal HbA1c Variation in Patients with Type 2 Diabetes authors: - Yu-Cheng Cheng - Yu-Hsuan Li - Hsiu-Chen Liu - Chiann-Yi Hsu - Wan-Jen Chang - I-Te Lee - Chin-Li Lu journal: Life year: 2023 pmcid: PMC10054572 doi: 10.3390/life13030763 license: CC BY 4.0 --- # The Impact of a Lockdown for the COVID-19 Pandemic on Seasonal HbA1c Variation in Patients with Type 2 Diabetes ## Abstract Glycemic control in patients with type 2 diabetes may be disrupted due to restricted medical service access and lifestyle changes during COVID-19 lockdown period. This retrospective cohort study examined changes of HbA1c levels in adults with type 2 diabetes 12 weeks before and after May 19 in 2021, the date that COVID-19 lockdown began in Taiwan. The mean levels of HbA1c-after were significantly lower than HbA1c-before in 2019 (7.27 ± $1.27\%$ vs 7.43 ± $1.38\%$, $p \leq 0.001$), 2020 (7.27 ± $1.28\%$ vs 7.37 ± $1.34\%$, $p \leq 0.001$), and 2021 (7.03 ± $1.22\%$ vs 7.17 ± $1.29\%$, $p \leq 0.001$). Considering the seasonal variation of HbA1c, ΔHbA1c values (HbA1c-after minus HbA1c-before) in 2020 (with sporadic COVID-19 cases and no lockdown) were not significantly different from 2021 (regression coefficient [$95\%$ CI] = $0.01\%$ [−$0.02\%$, $0.03\%$]), while seasonal HbA1c variation in 2019 (no COVID-19) was significantly more obvious than in 2021 (−$0.05\%$ [−0.07, −$0.02\%$]). In conclusion, HbA1c level did not deteriorate after a lockdown measure during the COVID-19 pandemic in Taiwan. However, the absolute seasonal reduction in HbA1c was slightly less during the COVID-19 pandemic compared with the year without COVID-19. ## 1. Introduction The spread of coronavirus disease 2019 (COVID-19) was declared a global pandemic and became an international health crisis [1]. A number of lockdown measures were implemented to slow the spread of the virus worldwide. However, social distancing and other restrictions might lead to a reduction in clinical accessibility during lockdown measures [2]. The World Health Organization reported that diabetic treatment was partially or completely disrupted in $49\%$ of the 155 countries surveyed in May 2020 [3]. Moreover, among patients with type 2 diabetes mellitus (DM), an increase in carbohydrate intake and a decrease in physical activity have been reported following COVID-19 confinement [4,5]. Adverse lifestyle changes may promote weight gain and glycated hemoglobin (HbA1c) levels [6,7,8]. In particular, poor glucose control preceding COVID-19 infection increases the risk of adverse outcomes [9]. Therefore, it is necessary to evaluate the impact of lockdown measures during the COVID-19 pandemic. The impact of the COVID-19 lockdown on glucose control has been widely studied in type 2 DM. Unlike the study results in type 1 DM, which consistently reported an improvement in glycemic control [10], the findings in type 2 DM were heterogeneous [11,12,13]. Silverii et al. [ 11] showed that lockdown measures had no significant effect on HbA1c levels in a meta-analysis of observational studies in a population with type 2 DM. However, some other studies found that a COVID-19 lockdown was associated with a significant increase in HbA1c [13] and fasting glucose levels [13,14] in patients with type 2 DM. Another two more recent meta-analyses reported a reduction in mean glucose levels [15] and an insignificant change in HbA1c levels [14] after lockdown; nevertheless, the two studies pooled the results from both type 1 and type 2 DM, mostly from type 1 DM. As interpreting the observed changes in glycemic control during COVID-19 lockdown, seasonal variation should be taken into consideration [10]. Many studies have shown that glucose levels are higher in cold seasons than in warm seasons [16,17,18]. It has been reported that winter was significantly associated with increased admission rates of both diabetic ketoacidosis and hyperglycemic hyperosmolar state [19]. However, most previous studies simply compared the glucose levels before and after (or during) the lockdown in the same year [11,12,13,14]. The before-and-after comparison without referenced years restricts the feasibility to clarifying whether the observed changes in glucose levels were resulted from lockdown measures or seasonal variation. In addition, most previous studies of glycemic control following the implementation of COVID-19 lockdown measures had relatively small sample sizes and limited the statistical power to detect the changes in glucose markers [11,12,13,14]. In Taiwan, an extremely rigorous border control has been in force since January 2020 [20]. There were only sporadic cases and locally small-scale outbreaks of COVID-19 in 2019 and 2020, respectively. Due to a surge of confirmed COVID-19 cases in mid-May 2021, the nation-wide COVID-19 alert was raised to level 3 (Lv3) from level 2 (Lv2) from 19 May 2021, until 27 July 2021, according to the epidemic warning standards and guidelines announced by the Taiwan Centers for Disease Control. The measures implemented under the COVID-19 level 3 alert (Lv3 alert) included gathering restrictions, closing of businesses and public areas, social distancing, and avoiding non-essential travel from one’s home [21,22]. This Lv3 alert lasted for 69 days until 27 July 2021. After that, the alert level was downgraded to Lv2, which still recommended social distancing but allowed leisure activities to occur in public places. To explicitly investigate the impact of the COVID-19 lockdown on glycemic control in Taiwan with appropriate consideration of seasonal effect on glucose levels, we conducted a retrospective cohort study in adult patients with type 2 DM in Taiwan, which compared the seasonal changes in HbA1c levels before and after the Lv3 alert over three years, from the year without COVID-19 [2019], the year with COVID-19 but without Lv3 alert [2020], to the year with COVID-19 and Lv3 alert [2021]. ## 2.1. Study Design and Patients This retrospective cohort study was conducted at Taichung Veterans General Hospital (VGH) between 2019 and 2021. The Lv3 alert was issued on 19 May for the COVID-19 epidemic. Based on the different observation years, we enrolled patients into three study groups, which corresponded to three distinct scenarios of COVID-19 outbreaks: no COVID-19 cases (cohort-2019), only small-scale and local COVID-19 outbreaks with an Lv2 alert in Taiwan (cohort-2020), and with a COVID-19 epidemic and Lv3 alert in Taiwan (cohort-2021). The longest duration for refilling prescriptions was 12 weeks in Taichung VGH; therefore, the study period in each year was divided into season-before and season-after according to the start date of the Lv3 alert on 19 May 2021. The season-before was defined as the 12-week period before 19 May (i.e., between 14 February and 18 May), and the season-after was defined as the 12-week period following 19 May (i.e., between 19 May and 10 August). The study design is illustrated in Figure 1. The inclusion criteria were as follows: [1] outpatients with a diagnostic International Classification of Diseases (ICD) code record of 250 for the ICD 9th version or E11–E13 for the ICD 10th version before 14 February in the observation year and [2] having at least one HbA1c record in both the season-before and season-after, respectively, in the observation year. The exclusion criteria were as follows: [1] a history of hospitalization between 1 January and 10 August during the observation year; [2] age < 20 years; [3] type 1 DM; [4] other types of DM, including pancreatic, hepatic, and secondary diabetes due to endocrine diseases; [5] gestational diabetes; [6] pregnancy at the time of HbA1c examination; [7] a history of anemia, which was defined as ICD (9th version) of 280–285 or ICD (10th version) of D50-D64; [8] a history of steroid use between 1 January and 19 May in each observation year; and [9] a history of participating in Ramaḍān during the study season. Anonymous demographic characteristics and laboratory data were obtained from the Clinical Informatics Research and Development Center of Taichung VGH after delinking the identification information. The study protocol was approved by the Institutional Review Board of the Taichung VGH in Taiwan, with a waiver for obtaining informed consent. ## 2.2. Measurements We collected only the latest records of multiple HbA1c measurements during each study season in the observation year. Therefore, each patient had paired HbA1c values (HbA1c-before and HbA1c-after) in the observation year. The ΔHbA1c was defined as (HbA1c-after)−(HbA1c-before) in the same observation year. The other baseline characteristics were retrieved within the baseline period between 1 January and 19 May in each observation year, including age, sex, height, body weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), serum levels of glutamic pyruvic transaminase (GPT), creatinine, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG). Among multiple measurements during the baseline period, only the latest data were collected. The use of antidiabetic and antihypertensive drugs was defined as medication prescribed between 1 January and 19 May in each observation year. In the clinical practice of diabetes management, blood samples for biochemical analyses were collected the morning after an overnight fast. HbA1c levels were measured using cation-exchange high-performance liquid chromatography (National Glycohemoglobin Standardization Program, G8, TOSOH, Tokyo, Japan). Biochemical analyses were performed using a photometric enzymatic method with a chemical analyzer (Hitachi 7600, Tokyo, Japan). Body mass index (BMI) was calculated as the weight (kg)/(height (m))2. The estimated glomerular filtration rate (eGFR) was calculated using the modification of diet in renal disease equation, as follows: 186 × (serum creatinine)−1.154 × (age)−0.203 (×0.742 if female) [23]. Hypertension was defined as the use of any antihypertensive drugs (ICD 9th version of 401–409 or ICD 10th version of I10–I15). Chronic kidney disease was defined as an eGFR < 60 mL/min/1.73 m2. Hypercholesterolemia was defined as an LDL level ≥ 100 mg/dL, and hypertriglyceridemia was defined as a TG level ≥ 150 mg/dL according to the reference target goal [24,25]. ## 2.3. Statistical Analysis Distributions of the baseline characteristics in the study cohorts 2019, 2020, and 2021 are described. Continuous variables were summarized as the mean and standard deviation and compared using an analysis of variance. Linear contrast coefficients were used to test the linear trends of HbA1c-before and HbA1c-after across years. Categorical variables are expressed as counts and percentages and were compared using the chi-square test among groups. Bonferroni’s correction rule was applied for multiple comparisons. We adapted the general estimation equation (GEE) method in the linear regression model to compare the ΔHbA1c among different study years. An autoregressive working correlation structure of the ΔHbA1c was assumed in the GEE model, as the structure minimized the value of quasi-likelihood under the independence model criterion (QIC) statistic. The regression coefficient (β) corresponded to the changes in ΔHbA1c between years, for example, the ΔHbA1c in 2019 minus ΔHbA1c in 2021. In addition to univariable analyses, multivariable regression analyses were performed to adjust for potential confounding effects from patients’ characteristics and clinical features. To appropriately consider the effects of time-varying clinical features, we collected the first data of these clinical information in each year, so that three different values in three years were all included in regression analyses. In the multivariable GEE models, we managed these clinical data as time-dependent covariates and estimated the regression coefficients after adjustment for these covariate contributions on the ΔHbA1c. Missing values of covariates have been replaced by mean values of the study cohorts. Type I error was set at $5\%$ in all analyses. Data analyses were performed using SAS Enterprise Guide version 7.15 (SAS Institute Inc., Cary, NC, USA). ## 2.4. Subgroup Analyses To evaluate the potential bias that may result from incomplete data compared among different study cohorts, we additionally conducted subgroup analyses. The subgroup included the patients who fulfilled the inclusion criteria mentioned above and were simultaneously enrolled in cohort-2019, cohort-2020, and cohort-2021. Therefore, each patient had a total of three paired HbA1c records obtained before and after the season in all three observation years, and their baseline data were retrieved between 1 January and 19 May 2019. *In* general, the data analysis procedures in this subgroup analyses were the same as those used in the major analyses. Multiple HbA1c measurements in the same patient during different seasons or years were pairwise compared using a paired t-test in subgroup analyses. ## 3. Results A total of 9111, 9078, and 8663 patients were enrolled in cohort-2019, cohort-2020, and cohort-2021, respectively. The baseline characteristics are presented in Table 1. Compared with patients in cohort-2019, those in cohort-2021 had a larger body weight, larger BMI, higher SBP, higher DBP, faster HR, lower eGFR, lower LDL, lower TG, a smaller proportion of patients with hypertension, and a larger proportion of glucagon-like peptide-1 receptor agonist (GLP-1 RA) use. Compared with patients in the cohort-2020, patients in the cohort-2021 had a smaller proportion of females, larger body height, faster HR, lower eGFR, lower TG, lower GPT, a smaller proportion of patients with hypertension, and a larger proportion of GLP-1 RA use. There were no significant differences in age and proportions of antihypertensive drugs, insulin, and oral antidiabetic drug use among the three cohorts. Comparisons of HbA1c and ΔHbA1c levels across 2019–2021 are presented in Table 2. Compared with patients in cohort-2019, those in cohort-2021 had a lower HbA1c-before and lower HbA1c-after. Compared with patients in the cohort-2020, patients in the cohort-2021 had a lower HbA1c-before, lower HbA1c-after, and lower ΔHbA1c. The values of HbA1c-before and HbA1c-after significantly decreased across the three cohorts. Figure 2 depicts that HbA1c-after was lower than HbA1c-before in 2019 (7.27 ± $1.27\%$ vs 7.43 ± $1.38\%$, $p \leq 0.001$), 2020 (7.27 ± $1.28\%$ vs 7.37 ± $1.34\%$, $p \leq 0.001$), and 2021 (7.03 ± $1.22\%$ vs 7.17 ± $1.29\%$, $p \leq 0.001$). Table 3 shows results that examined the year effect on the ΔHbA1c. Compared with cohort-2021, the values of ΔHbA1c were lower in cohort-2019 and higher in cohort-2020 in the univariable regression analysis. However, with adjustment for potential confounding effect of baseline characteristics including demographic features, body mass index, lipid profile, blood pressure, renal function, liver function, antihypertensive and hypoglycemic agents, the difference in ΔHbA1c between cohort-2020 and cohort-2021 was largely minimized and became insignificant. The decrement in ΔHbA1c during cohort-2019 was more obvious than that during cohort-2021 (β [$95\%$ confidence interval (CI)]: −$0.047\%$ [−$0.073\%$ to −$0.021\%$], $p \leq 0.001$), but there was no significant difference between the ΔHbA1c in cohort-2020 and cohort-2021 (β [$95\%$ CI]: $0.009\%$ [−$0.017\%$ to $0.035\%$], $$p \leq 0.500$$) after adjustment for baseline characteristics. Moreover, several factors also affected their seasonal changes in HbA1c. Patients with TG ≥ 150 mg/dL, SBP ≥ 140 mmHg, eGFR < 60 mL/min/1.73 m2, high GPT, and use of antihypertensive drugs had a significantly high value of ΔHbA1c; however, patients receiving insulin and OHA treatment had a significantly low value of ΔHbA1c. Table 4 shows baseline characteristics of 3720 subjects included in subgroup analyses. Compared to the patients in the main analyses, the subgroup had similar distributions in age, sex, anthropometry, and blood pressure, and slightly lower TG and LDL levels. However, their eGFR values were similar to cohort-2019 and cohort-2020, but higher than cohort-2021; the proportions of receiving oral hypoglycemic agent (OHA) and GLP-1 RA treatments were higher than that in all three cohorts in the main analyses. The HbA1c-before, HbA1c-after, and ΔHbA1c values from different seasons in this subgroup were very close to that in the main analyses (Table 5). Compared to 2021, the HbA1c-before and HbA1c-after were higher in 2019 and 2020. There was a significant decreasing trend for HbA1c-before ($p \leq 0.001$) and HbA1c-after ($p \leq 0.001$) across the three years. The decrements in ΔHbA1c were more obvious in 2019 than in 2021 (β [$95\%$ CI]: −$0.037\%$ [−$0.068\%$ to −$0.006\%$], $$p \leq 0.019$$), while not different between 2020 and 2021 ($$p \leq 0.156$$). The linear regression analyses using the GEE method shows consistent results (Table 6). ## 4. Discussion The main finding of our study was that the ΔHbA1c values were not significantly different between 2020 (Lv2 alert) and 2021 (Lv3 alert), even though the HbA1c-after values were significantly lower than the HbA1c-before values in the same observation year. Another finding was a significantly lower ΔHbA1c in 2019 (without COVID-19) compared to 2021. The findings of the subgroup analyses were consistent with those of the main analyses. The present study indicated the absolute seasonal reduction in HbA1c was slightly lessen during the years with COVID-19 than the year without COVID-19. However, there was no deterioration in HbA1c level after the lockdown (raising the COVID-19 alert from Lv2 to Lv3) during the years with COVID-19. We found reductions in the HbA1c levels after the Lv3 alert in 2021, but there was a similar reduced HbA1c levels between the study seasons in the previous two years. Seasonal variations in glycemic control may explain this finding. Many previous studies have shown that HbA1c is higher in cold seasons than in warm seasons [16,17,18], and this variation might be associated with increased dietary intake and lower physical activity in colder seasons [26,27,28]. Cultural events may also influence seasonal variability in HbA1c levels. A prospective study in Taiwan reported a poor glycemic control during the Chinese New Year holiday [29], it was very likely due to the potentially increased calorie consumption. Traditionally, the Chinese population partake in elaborate dinners and consume large amounts of candies and snacks in family reunion or friends visits during the entire holiday period. In 2019 and 2021, the Chinese New Year holiday was in early February and the end of January, just around the beginning of the season-before defined in our study. HbA1c represents the integrated glucose concentration during the preceding 8–12 weeks [30]; therefore, higher HbA1c levels over the period before in the present study might be affected by lifestyle changes during the Chinese New Year holiday. A previous study that did not explore the impact of the lockdown revealed that the COVID-19 pandemic did not influence the pattern of seasonal variation in HbA1c levels [31]. This is in agreement with our finding of an unchanged pattern of seasonal variation of HbA1c during the COVID-19 pandemic. Despite the pattern of seasonal variation of HbA1c being unchanged, we found a slightly smaller reduction in the HbA1c values from the season-before to season-after during the years with COVID-19 than during the year without COVID-19. Many studies have explored the effects of COVID-19-associated lockdown measures on glycemic control, but the findings have been inconsistent. For instance, worsening glycemic control was reported in India [32], China [33], and Korea [34], respectively. In contrast, a study from Greece [35] and another study from India [36] showed improved glycemic control during the COVID-19 pandemic. Moreover, in studies conducted in Italy and Turkey, glycemic control did not change significantly [37,38]. Heterogeneous results have also been demonstrated in meta-analyses. Silverii et al. [ 11] found no significant change in the HbA1c levels, but Ojo et al. [ 13] revealed a significant increase in HbA1c and fasting glucose levels following a lockdown due to COVID-19. Different study designs and geographic variations in the countries where the studies were conducted might explain the heterogeneity in the findings. The strengths of restriction measures may also differ from country to country. For example, the restriction was particularly strict in Italy and Spain compared other countries [11]. *In* general, the restriction was less strict in some Asia countries, such as Japan, South Korea, and Taiwan, than in Europe. A subgroup analysis in Silverii’s study also revealed a reduced HbA1c levels in Asia but no significant changes in HbA1c in Europe [11]. Notably, the confounding effect of seasonal glycemic change has not been appropriately managed in most previous studies. However, in contrast to our findings, a study conducted in East Asia and South Korea showed a lack of seasonal variation in HbA1c levels and increased HbA1c levels following enhanced social distancing during the COVID-19 outbreak [34]. The worsening glycemic control has been explained by some studies, which demonstrated changes in lifestyle during the COVID-19 lockdown, including lack of physical activities, increased dietary intake, more screen time, and weight gain [6,7,8]. Stress and anxiety might mediate adverse lifestyle changes and poor glycemic control during the COVID-19 lockdown [8]. However, it is noteworthy that, in another study, increased levels of perceived stress and less exercise during the COVID-19 lockdown did not lead to a deterioration of glycemic control [39]. On the other hand, the messages alerting diabetes as a risk factor in developing critical situations of COVID-19 have been widely disseminated; therefore, patients with diabetes may pay more attention to self-manage their glucose levels and better adhere to medications during lockdown. The present study showed no significant difference in ΔHbA1c levels between the cohorts in 2020 and 2021. Briefly, lockdown measures (raising the COVID-19 alert from Lv2 to Lv3) did not lead to the deterioration of glycemic control. During the period of the Lv3 alert in Taiwan, hospital capacity was relatively adequate in central Taiwan. Many countries reported that COVID-19 had disrupted the care of people with diabetes [3]. In contrast, the national health insurance system, with coverage of more than $99\%$ of citizens in Taiwan [22] and medical access for diabetic management, was not disrupted. Furthermore, drive-through services to patients with chronic illness to refill prescriptions, which might increase the accessibility of prescription drugs and largely avoid the risk of contact transmission, were implemented. The impact of lockdown measures on glycemic control in patients with type 2 DM may not be significant. However, the extent to which lifestyle changes might affect glycemic control during the relatively short duration (69 days) of the Lv3 alert in Taiwan needs to be empirically examined. In addition to the effect of the lockdown, we found a downward trend in HbA1c levels across years in the present study. Different from our results, an elevated mean HbA1c level was observed in Japan in 2020, the year when the COVID-19 pandemic was most prevalent, compared with the previous two years [31]. However, in line with our findings, previous studies evaluating the quality of diabetic control in Taiwan have demonstrated a downward trend in HbA1c levels across more than a decade [40,41,42]. The annual HbA1c improvement might result from the pay-for-performance program for diabetes shared care in Taiwan [43]. The downward trend of HbA1c in our study was likely to be attributed to improved HbA1c control following the improved standard of diabetic care. Furthermore, it appears that the influence of the COVID-19 pandemic might be minimal in Taiwan. However, the impact of the COVID-19 pandemic on year-to-year variation in glycemic control needs to be explored in a longer-term study. Another finding in the present study was that weight and BMI increased compared to the year without the COVID-19 pandemic, even through the prevalence of insulin and OHA use did not change. Several previous studies revealed weight gains in patients with diabetes during the COVID-19 pandemic. Worsening weight control was found to be associated with adverse lifestyle changes including decreased physical activity [6,7,8,43], increased frequency of snack eating, and carbohydrate consumption [7,8]. On the other hand, some studies also found that increased fear and stress during the COVID-19 pandemic might be associated with adverse lifestyle change [8,39]. According to a previous study to investigate lifestyle changes during the COVID-19 Lv3 alert in the *Taiwan* general population, the online survey showed a significant decrease in physical activity but no significant changes in body weight during this period [44]. Notably, it has been reported that an increasing trend in obesity across more than a decade based on the data from Nutrition and Health survey in Taiwan [45]. However, further studies focusing on patients with diabetes to explore weight and lifestyle changes between the years with and without the COVID-19 pandemic in Taiwan are needed. This study had several strengths. The assessment of the impact of COVID-19 lockdown on glycemic control was not simply based on the before-and-after comparison, we took the seasonal variation of HbA1c levels into account, and compared the ΔHbA1c values between the year without COVID-19, the year with COVID-19 but not lockdown (Lv2 alert), and the year with COVID-19 lockdown (Lv3 alert). We also adjusted for other demographical and clinical baseline characteristics of patients using GEE model to appropriately consider the dependency of multiple measures of HbA1c. Lastly, we additionally conducted a subgroup analysis for patients with complete follow-up, demonstrating similar results with main analyses, and increasing the robustness of our conclusions. The present study also had several limitations. First, only HbA1c levels were analyzed to assess blood glucose control in patients with type 2 DM. Second, this was a single-center retrospective study in central Taiwan, and our results might not be representative of the entire patient population. Third, a definite causal relationship between the Lv3 alert and glycemic control could not be established based on an observational design. Fourth, glycemic control is significantly affected by patients’ lifestyle. However, we did not have the information of lifestyle change during the COVID-19 pandemic in this retrospective cohort study. Fifth, we did not collect the dosages and categories of antidiabetic drugs in the present study. Finally, there could be selection bias because some patients were lost to follow-up and lacked complete HbA1c data during the COVID-19 pandemic. The situations of patients remaining in the follow-up may tend to be more complicated or severe. However, in the subgroup analyses, we additionally included patients with complete follow-up and performed a subgroup analysis, the consistent results between subgroup analysis and main analysis suggested robust observations in our study. ## 5. Conclusions Compared with the HbA1c levels in season-before, HbA1c levels in season-after significantly decreased in all three years. However, there was no significant difference in seasonal reduction in HbA1c between the year with COVID-19 pandemic without lockdown [2020] and the year with COVID-19 pandemic with lockdown [2021]. The absolute value of seasonal HbA1c reduction was slightly lessen during the COVID-19 pandemic compared to the year without COVID-19 [2019] in the present study. The long-term studies for time-series analyses are warranted to clarify the impact of COVID-19 pandemic on the seasonal glycemic variation. ## References 1. **WHO Director-General’s Opening Remarks at the Media Briefing on COVID-19—11 March 2020** 2. 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--- title: Features of Obstructive Sleep Apnea in Children with and without Comorbidities authors: - Eusebi Chiner - Jose N. Sancho-Chust - Esther Pastor - Violeta Esteban - Ignacio Boira - Carmen Castelló - Carly Celis - Sandra Vañes - Anastasiya Torba journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054579 doi: 10.3390/jcm12062418 license: CC BY 4.0 --- # Features of Obstructive Sleep Apnea in Children with and without Comorbidities ## Abstract Background: To compare the clinical and polysomnographic features of obstructive sleep apnea (OSA) in children with adenotonsillar hypertrophy (Group A) and comorbidities (Group B). Methods: A five-year prospective study using nocturnal polysomnography before and after treatment. Results: We included 168 patients: 121 in Group A and 47 in Group B, with differences in age (6.5 ± 3 vs. 8.6 ± 4 years; $p \leq 0.001$), body mass index (BMI) (18 ± 4 vs. 20 ± 7 kg/m2; $p \leq 0.05$), neck circumference (28 ± 4 vs. 30 ± 5 cm; $p \leq 0.05$), and obesity ($17\%$ vs. $30\%$; $p \leq 0.05$). Group B patients were more likely to have facial anomalies ($p \leq 0.001$), macroglossia ($p \leq 0.01$), dolichocephaly ($p \leq 0.01$), micrognathia ($p \leq 0.001$), and prognathism ($p \leq 0.05$). Adenotonsillectomy was performed in 103 Group A patients ($85\%$) and 28 Group B patients ($60\%$) ($p \leq 0.001$). In B, 13 children ($28\%$) received treatment with continuous positive airway pressure (CPAP) and 2 ($4\%$) with bilevel positive airway pressure (BiPAP), compared with 7 in Group A ($6\%$) ($p \leq 0.001$). Maxillofacial surgery was more common in Group B ($p \leq 0.01$). Clinical and polysomnography parameters improved significantly in both groups after therapeutic intervention, though Group A showed better results. Conclusions: Obesity and facial anomalies are more frequent in childhood OSA patients with comorbidities, who often require combination therapy, such as ventilation and surgery. ## 1. Introduction Childhood obstructive sleep apnea (OSA) has a worldwide prevalence of 1–$5\%$, peaking in children aged 2 to 8 years and increasing to 7–$16\%$ when snoring in children aged 6 months to 13 years is also considered [1,2]. As in adult OSA, the main symptom of childhood OSA is snoring, frequently accompanied by apnea; however, children also show other manifestations, such as mouth breathing, failure to thrive, enuresis, and neuropsychic disorders [3,4]. Based on these varied symptoms, we can distinguish two phenotypes: (A) adenotonsillar hypertrophy and (B) concomitant diseases or comorbidities (with or without adenotonsillar hypertrophy), including facial anomalies, neuromuscular diseases, and complex syndromes (Down’s syndrome, Prader–Willi syndrome, etc.). Patients in both groups have reduced upper airway caliber and dynamic alterations, and although a clear relationship exists between adenotonsillar hypertrophy size and the apnea–hypopnea index (AHI), no study has revealed intervening factors or shown why adenotonsillectomy has different effects in OSA patients and controls [2]. In addition, obesity is a growing problem in European countries and is a known predisposing factor in adults [4,5,6]. Obesity alone can lead to OSA, and may be associated with adenotonsillar hypertrophy and a higher risk of residual disease after adenotonsillectomy in children. OSA is the sleep disorder most closely associated with cardiovascular consequences, primarily high blood pressure [7]. Management of childhood OSA can be complex, particularly in patients with comorbidities, as they require diagnostic tests at onset and during the course of the condition [6]. The current gold standard for OSA diagnosis is polysomnography [8,9]. First-line treatment consists of adenotonsillectomy, since adenotonsillar hypertrophy is found in most patients [10]. Nonetheless, OSA often persists after surgery and care providers must consider alternative and/or complementary treatments, such as intranasal corticosteroids or montelukast [11,12,13]. Residual OSA may require simple or combined treatment; the latter could include a hypocaloric diet, continuous positive airway pressure (CPAP), myofunctional therapy, or rapid maxillary expansion. Treatment should be tailored to individual patients, as no single strategy suits all [1,13]. Most published studies have analyzed single risk factors [13]; none has compared different predisposing conditions, treatment, and evolution in a pediatric population. We hypothesized that the clinical and polysomnographic features of childhood OSA may differ in children with adenotonsillar hypertrophy versus children with comorbidities, and that a more complex long-term strategy may be required to treat the condition. The aim of our study was to evaluate and compare the features of childhood OSA in the two populations. ## 2.1. Study Design and Population We performed a five-year prospective cohort study in people aged under 14 years who were seen in the Pulmonology Office of San Juan de Alicante University Hospital. We included individuals with suspected OSA, with or without neuropsychiatric or physical daytime symptoms. We excluded patients who refused diagnostic tests or with polysomnography results deemed technically invalid (recording time < 4 h). ## 2.2. Clinical Protocol We collected information from parents/guardians regarding snoring, apnea, nocturnal shortness of breath, restless sleep, nocturnal sweating, enuresis, nasal obstruction, rhinorrhea, mouth breathing, hearing problems, recurring infections, wheezing, heartburn, headaches, hyperactivity or attention deficit, apathy, shyness, drowsiness, poor academic performance, failure to thrive and other disorders, including poor appetite and polyphagia. These data were collected through a standardized data collection form. We examined the oral cavity of patients to determine Mallampati score, degree of adenotonsillar hypertrophy on the Brodsky scale, and palatal dimensions. We also recorded craniofacial morphological characteristics, height, weight, body mass index (BMI), and BMI percentile. Using the growth charts published by the Centers for Disease Control and Prevention and the American Academy of Pediatrics, we calculated BMI using the formula weight in kilograms divided by height in meters squared, and classified the values into age and sex-specific percentiles. Percentiles over 95 were considered to represent obesity [14]. ## 2.3. Diagnostic Procedure OSA diagnoses were established through polysomnography (Sleep Lab, Jaeger–Viasys®, Hoechberg, Germany), which monitored sleep variables—through electroencephalography (C3-A2), electrooculography, and chin electromyography—as well as the following respiratory variables: nasal airflow through cannula, respiratory impedance with uncalibrated thoracoabdominal bands, and oxygen saturation. We also monitored snoring, body position, and transcutaneous carbon dioxide, and performed electrocardiography and tibialis anterior electromyography. Apnea was defined as a reduction of more than $90\%$ in amplitude of the oronasal flow signal, with or without microarousal or desaturation, and hypopnea was defined as between $30\%$ and $90\%$ reduction with microarousal and/or $3\%$ desaturation. Respiratory effort associated with microarousal was defined as a period of limited flow lasting between 10 s and 2 min and ending with microarousal. The total number of events of apnea, hypopnea, and respiratory effort associated with microarousal was divided by the total sleep time to obtain the apnea–hypopnea index (AHI). The sleep stages were classified in accordance with international guidelines [15,16,17]. Patients underwent polysomnography in the sleep unit in an isolated single bed. They were supervised by a nurse and accompanied by a family member. OSA diagnosis required an AHI of at least 3/h 18 and severity was classified as follows: mild 3–5/h; moderate 5–10/h; and severe more than 10/h. ## 2.4. Patient Groups After assessing the whole sample, we compared the gender, anthropometric measurements, clinical and polysomnographic features, and evolution of the condition in two groups of patients. Group A included patients in whom the predominant alteration related to OSA was adenotonsillar hypertrophy. Group B included patients in whom other comorbidities were the main factors associated with OSA. These comorbidities could include a wide spectrum of severe facial anatomical defects or also marked obesity. ## 2.5. Therapeutic Protocol After diagnosis, some patients were referred to the otorhinolaryngology department for adenotonsillectomy, and others to maxillofacial surgery. Conservative treatment consisted of montelukast (4–5 mg/day for at least 6 months) combined with dietary, behavioral, and postural modifications. If continuous positive airway pressure (CPAP) was considered, an auto CPAP titration study was performed as part of an adherence program [18]. If bilevel positive airway pressure (BiPAP) was considered, a manual titration was performed to set optimal pressures. Between 6 and 12 months after surgery, patients underwent follow-up polysomnography. When this was not possible, symptoms were assessed through a clinical interview. We defined improvement as more than $50\%$ reduction in baseline AHI, and recovery as reduction to normal levels. ## 2.6. Sample Size Calculation Assuming a statistical power of $80\%$, an alpha error of $5\%$, and a loss to follow-up of $10\%$, in concordance with previous studies and owing to the distribution of patients (two-thirds in Group A and one-third in Group B), we estimated that at least 101 patients would be required in Group A and 30 in Group B to detect a statistically significant difference in proportions between the two [2,4]. Sample size calculation was adjusted for gender in each group. ## 2.7. Statistical Analysis An anonymized database was created using a measure of central tendency for the numerical variables, (mean ± standard deviation), and frequency distribution for categorical variables. We performed a descriptive analysis of clinical features, severity, concomitant disorders, obesity, and therapeutic approach. We used the Chi-square or Fisher’s exact test to compare categorical variables. After applying the Kolmogorov–Smirnov test and checking homogeneity of variance, we compared the numerical variables using the Student’s t-test or the Mann–Whitney test. We used the two-sided paired-samples t-test to compare clinical and polysomnography data before and after treatment in the same group, and the unpaired samples t-test to compare the data of Groups A and B. Values of $p \leq 0.05$ were considered significant. For all calculations, we used the statistical package IBM SPSS (version 15.0; SPSS; Chicago, IL, USA). ## 2.8. Ethical Aspects The study was conducted in accordance with the Declaration of Helsinki (updated in Edinburgh), the Council of Europe Convention on Human Rights and Biomedicine, the UNESCO Universal Declaration on the Human Genome and Human Rights, and the provisions governing biomedical research and data protection in Spain. The study was approved by the institutional review board of San Juan de Alicante University Hospital (HUSJ-20-003). ## 3.1. General Results Over the five-year study period, we included 168 patients (110 boys and 58 girls) with mean age 7 ± 4 years, BMI 18.7 ± 5.1 kg/m2, BMI percentile 67 ± 37, neck circumference 29 ± 4 cm, and weight percentile 72 ± 43. Forty-two children ($25\%$) were considered obese (BMI percentile ≥ 95). Patients were referred from otorhinolaryngology ($39\%$), pediatrics ($35\%$), pulmonology ($21\%$), neurology ($2.5\%$), and maxillofacial surgery ($2.5\%$). There were 121 children in Group A and 47 in Group B, which included 16 cases of asthma/rhinitis/polyposis; 4 cases each of cystic fibrosis and Down’s syndrome; 3 cases each of gastroesophageal reflux disease and Prader–Willi syndrome; 2 cases each of attention deficit hyperactivity disorder, neuromuscular disorders, epilepsy, morbid obesity, and cerebral palsy; and 1 case each of congenital hypothyroidism, ciliary dyskinesia, Pierre Robin syndrome, Rett syndrome, Rubinstein–Taybi syndrome, Apert syndrome, and congenital atrioventricular block with hearing loss. In Group A, there were 75 male and 46 female patients. In Group B, there were 35 male and 12 female patients. Gender differences between sexes were not statistically significant ($$p \leq 0.127$$). ## 3.2. Clinical Features The most common nocturnal clinical features in the whole series were snoring ($96\%$), apnea ($82\%$), shortness of breath ($70\%$), and restless sleep ($67\%$). The most common daytime clinical features were recurrent upper airway infections ($68\%$), chronic rhinorrhea ($63\%$), nasal obstruction ($58\%$), daytime mouth breathing ($57\%$), recurrent otitis ($29\%$), daytime sleepiness ($26\%$), failure to thrive ($23\%$), headache ($14\%$), and poor appetite ($14\%$). Neuropsychiatric manifestations were attention problems ($33\%$), poor academic performance ($21\%$), and shyness ($11\%$). Other undefined features reported by parents were weakness, irritability, low activity, polyphagia, poor sleep quality, and recurrent pneumonia. Figure 1A–C compares the nocturnal, daytime, and neuropsychiatric features of Groups A and B. The only significant differences were for snoring ($98\%$ vs. $89\%$, $p \leq 0.05$) and poor academic performance ($16\%$ vs. $36\%$, $p \leq 0.01$). Predisposing factors were tonsillar hypertrophy ($84\%$), adenoid hypertrophy ($47\%$), obesity ($20\%$), facial anomalies ($17\%$), high-arched palate ($13\%$), retrognathia ($12\%$), micrognathia ($8\%$), macroglossia ($4\%$), dolichocephaly ($4\%$), and prognathism ($1\%$). Eight patients had prior adenotonsillectomy. Table 1 compares the anthropometric measurements and predisposing factors of Groups A and B. We found a significantly higher proportion of obesity in Group B ($$n = 14$$, $30\%$) that in Group A ($$n = 21$$, $17\%$) ($p \leq 0.05$). ## 3.3. Polysomnographic Data Table 2 presents the polysomnography features of the two groups. Although there were no significant differences in sleep architecture or sleep efficiency, Group B had worse respiratory variables and more microarousals than Group A. OSA was considered mild in 13 patients ($8\%$), moderate in 40 ($24\%$), and severe in 115 ($69\%$). There were no significant differences in distribution of severity between the groups (Figure 2). ## 3.4. OSA Treatment Adenotonsillectomy was performed in 28 Group B patients ($60\%$) and 103 Group A patients ($85\%$) ($p \leq 0.001$). The proportion of children who underwent maxillary surgery or septoplasty was similar in both groups. Other therapeutic measures, such as orthodontic treatment, maxillary distraction, or behavioral therapy, were more common in Group B ($$n = 5$$, $11\%$ vs. $$n = 1$$, $1\%$; $p \leq 0.01$). Thirteen patients in Group B received CPAP ($28\%$), compared with 7 in Group A ($6\%$) ($p \leq 0.001$). In addition, the two patients treated with BiPAP ($4\%$) were in Group B ($p \leq 0.05$). Eight Group B patients received conservative treatment ($17\%$), compared with nine from Group A ($7.5\%$). This difference was borderline significant ($$p \leq 0.07$$). Post-treatment testing was performed in 88 patients ($52\%$)—polysomnography in 47, home respiratory polygraphy in 19, and clinical response follow-up in 22—and we found no differences between the groups in this regard. Both groups had similar nocturnal and daytime symptoms after treatment. All daytime, nocturnal, and neuropsychiatric symptoms had improved significantly in both groups after treatment ($p \leq 0.001$) (Figure 3). Table 3 shows the anthropometric and polysomnography values for both groups before and after treatment (polysomnography post-treatment values are for the 47 patients who underwent this procedure). Of the patients who underwent objective follow-up assessment after treatment, 49 ($29\%$) had a post-treatment AHI of 3 or more: 30 boys and 19 girls; 15 from Group B ($32\%$) and 34 from Group A ($28\%$) (p = NS). With an apnea–hypopnea index cutoff point of ≥10, 16 patients ($9.5\%$) were diagnosed with residual OSA: 8 boys and 8 girls; 5 from Group B ($11\%$) and 11 from Group A ($9\%$) (p = NS). ## 4. Discussion Childhood OSA is very common, with an estimated prevalence of 1–$5\%$ [1,19,20]. Adenotonsillar hypertrophy is a recognized predisposing factor, but others have been reported, such as craniofacial malformations, neuromuscular disorders, obesity, and Down’s syndrome [20]. Our series contained patients with these conditions. The predominant features in adults with OSA are obesity, drowsiness, and snoring, while childhood OSA is more frequently associated with failure to thrive, hyperactivity, and other manifestations. Drowsiness was recorded in only $26\%$ of our patients, who were more likely to show failure to thrive, hyperactivity, and attention deficit. OSA has characteristic nocturnal symptoms: $97\%$ of our patients snored, $82\%$ had apnea, and $70\%$ had shortness of breath. The predominant daytime symptoms include recurrent upper airway infection, nasal obstruction, and mouth breathing [4,21], which in our study affected $68\%$, $58\%$, and $57\%$ of patients, respectively. Compared with Group B, Group A patients were significantly more likely to snore and have poor academic performance, but no other differences were found regarding night-time or daytime symptoms. Some of the concomitant diseases in Group B patients may predispose them to OSA. These include asthma, cystic fibrosis, Down’s syndrome, and obesity. Several studies have shown that apnea and snoring are more frequent in people with asthma, and that these symptoms could lead to or aggravate OSA [22]. Other authors have noted that obesity is closely related to wheezing and asthma [23]. One-quarter of all our patients were obese, and this proportion was higher in those with concomitant disease. However, it is worth noting that several patients from both groups had adenotonsillar hypertrophy as well as obesity. Unlike in adult OSA, no clear correlation has been found between AHI and BMI in children under 12 years old [24,25], which leads us to believe that obesity was probably not the most determining factor of OSA in our study. Children diagnosed with Down’s syndrome are more likely to have OSA owing to a combination of anatomical factors such as macroglossia, midface hypoplasia, and micrognathia, together with obesity and adenotonsillar hypertrophy [26]. Children with Prader–Willi syndrome are also at greater risk of having OSA, associated with obesity, inactivity, drowsiness, and other behavioral disorders [27]. Our study confirms the differences in predisposing factors, as Group B had a significantly higher proportion of macroglossia, facial anomalies, micrognathism, retrognathism, prognathism, and dolichocephaly. In addition, our study demonstrated significantly greater severity in all respiratory variables and significantly more microarousals in children with concomitant disease. We found no differences in other neurological variables, meaning neurological monitoring contributed little to the diagnosis. In contrast, previous findings have highlighted the importance of identifying arousals, as many OSA symptoms may be secondary to sleep disruption, with frequent alterations in sleep architecture increasing the number of arousals and inhibiting deep sleep [23]. While international guidelines recommend polysomnography for the diagnosis of childhood OSA [8], home respiratory polygraphy is emerging as an alternative diagnostic technique in this population [24,28,29,30], although it can only be applied in the hospital setting under current Spanish legislation [1]. Adenotonsillectomy is the treatment of choice for OSA, as it resolves daytime and nocturnal symptoms with an efficacy of $78\%$ [31]. This technique was performed in $60\%$ of Group B compared with $85\%$ of Group A patients, which confirms the increased complexity of treating patients with concomitant disease. This group may require other treatments such as septoplasty, maxillomandibular surgery, maxillary distraction, behavioral therapy, and orthodontic treatment [1]. Indeed, our Group B patients were more likely to receive alternative treatments. The second most effective therapeutic option for OSA is CPAP, which is more commonly used in children with obesity, neuromuscular disorders, or craniofacial malformations, who may also have adenotonsillar hypertrophy [32]. In our study, there were marked differences between the groups, with a higher proportion of CPAP/BIPAP in Group B. When treatment is personalized in both groups of patients, it is expected that they will improve equally, although the group with concomitant disease required more frequently CPAP or BiPAP. This would require close monitoring during the growth of these patients, since the underlying disease is persistent and some patients may have to carry these treatments for life. Several studies have shown that symptoms and cognitive disorders clearly improve in OSA patients after treatment, particularly after adenotonsillectomy [33]. Similarly, in our study, daytime, nocturnal, and neuropsychiatric symptoms improved significantly with treatment. It is also worth noting the significant improvements in anthropometric characteristics, which demonstrates the negative and potentially reversible impact of OSA on child development. Our study highlights the need to distinguish between different phenotypes of childhood OSA and the importance of a multidisciplinary approach, as care providers may need to consider different treatment approaches in the initial clinical assessment [34]. 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--- title: Ultrasound Doppler Flow Parameters Are Independently Associated with Renal Cortex Contrast-Enhanced Multidetector Computed Tomography Perfusion and Kidney Function authors: - Arkadiusz Lubas - Arkadiusz Zegadło - Emilia Frankowska - Jakub Klimkiewicz - Ewelina Jędrych - Stanisław Niemczyk journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054581 doi: 10.3390/jcm12062111 license: CC BY 4.0 --- # Ultrasound Doppler Flow Parameters Are Independently Associated with Renal Cortex Contrast-Enhanced Multidetector Computed Tomography Perfusion and Kidney Function ## Abstract Background: The assessment of kidney perfusion has an emerging significance in many diagnostic applications. However, whether and which of the ultrasound Doppler parameters better express renal cortical perfusion (RCP) was not shown. The study aimed to prove the usefulness of Doppler ultrasound parameters in the assessment of RCP regarding low-dose contrast-enhanced multidetector computer tomography (CE-MDCT) blood flow. Methods: Thirty non-stenotic kidneys in twenty-five hypertensive patients (age 58.9 ± 19.0) with mild-to-severe renal dysfunction were included in the study. Resistive index (RI) and end-diastolic velocity (EDV) in segmental arteries, color Doppler dynamic RCP intensity (dRCP), RI (dRI), pulsatility index (dPI), and CE-MDCT blood flow (CBF) in the renal cortex were estimated. Results: CBF correlated significantly with age, estimated glomerular filtration rate (eGFR), RI, EDV, dRI, dPI, and dRCP. In separate multivariable backward regression analyses, RI (R2 = 0.290, $$p \leq 0.003$$) and dRCP (R2 = 0.320, $$p \leq 0.001$$) were independently associated with CBF. However, in the common ultrasound model, only dRCP was independently related to CBF (R2 = 0.317, $$p \leq 0.001$$). Only CBF and EDV were independently associated with eGFR (R2 = 0.510, $p \leq 0.001$). Conclusions: Renal cortical perfusion intensity is the best ultrasound marker expressing renal cortical perfusion. In patients with hypertension and kidney dysfunction, renal resistive index and end-diastolic velocity express renal cortical perfusion and kidney function, respectively. ## 1. Introduction The wide accessibility of radiologic imaging methods enabled the assessment of renal perfusion, which has an emerging significance in many diagnostic applications. As organ perfusion is considered a prerequisite of its function, alterations in renal perfusion can be detected, among others, in hypertension, cardiac and thyroid abnormalities, renal artery stenosis, and acute and chronic kidney diseases [1,2,3,4,5]. Most quantitative perfusion assessment methods, such as scintigraphy, computed tomography (CT), magnetic resonance imaging, and contrast-enhanced ultrasonography (CEUS), require a contrast agent for adequate measurement. However, in conventional (non-contrast) ultrasonography, some ultrasound Doppler parameters, e.g., flow velocities and resistive and pulsatility indexes (RI, PI) describing properties of intravascular blood flow, are often recognized as renal perfusion markers. It was not univocally shown which of these parameters, in a better manner, expresses the amount of organ perfusion. On the other hand, some studies challenge significant relations of considered Doppler parameters with perfusion attributes and arrange them as vascular and systemic hemodynamic properties markers [6,7,8,9]. Recently, Abe et al., in a group of 162 patients with chronic kidney disease, showed an independent association between interlobar end-diastolic velocity (EDV) and renal function, but there was no such association with regard to RI [10]. As tissue perfusion is defined as volume flow in time unit through tissue mass, e.g., mL/100 g/min, and can be estimated as blood flow in contrast-enhanced multidetector computer tomography (CE-MDCT), two-dimensional Doppler ultrasound can measure flow parameters through a plain vessel section. Probably, discrepancies resulted from the lack of third dimension between computer tomography and conventional ultrasound examination, and different methods and algorithms used in flow calculation influence measurement similarity. Lastly, a new experimental three-dimensional ultrasound perfusion assessment method was introduced, which could overcome the abovementioned inconsistencies in results [11]. Recently, many scientific publications have used the renal resistive index as an easily accessible marker of renal perfusion, especially in critically ill patients [9,12,13,14]. However, this should be confirmed in relation to an independent imaging method. Moreover, other ultrasound Doppler parameters, especially achieved in novel measurement methods, should be considered valuable in assessing renal perfusion. The study aimed to analyze the usefulness of selected Doppler ultrasound parameters in estimating renal cortex perfusion in comparison to low-dose CE-MDCT renal cortical blood flow. ## 2. Materials and Methods Data from non-stenotic kidneys in hypertensive patients with mild-to-severe renal dysfunction examined for renal artery stenosis were included in the study. Patients underwent ultrasound Doppler examination and then were diagnosed in low-dose CE-MDCT. Inclusion criteria encompass age over 18 years, suspicion of renal artery stenosis based on anamnesis or results of other examinations, and written informed consent. Regarding medical history and actual results, the exclusion criteria comprised acute kidney injury, chronic kidney disease (CKD) stage G5, inflammation, and iodide contrast intolerance. Informed consent was obtained from all patients who attended the study. ## 2.1. Renal Function Assessment A morning blood sample was taken before CE-MDCT to assess serum creatinine and calculate the estimated glomerular filtration rate (eGFR) according to the CKD-EPI equation [15]. ## 2.2. Contrast-Enhanced Multidetector Computer Tomography The perfusion assessment was performed in the dynamic measurement of blood flow with a contrast agent in the three-dimensional region of interest (ROI) appointed in the renal cortex. In the time of an iso-osmolar contrast agent (Visipaque 320), intravenous infusion ROI was repeatedly scanned (single-source DECT scanner with rapid kVp switching Discovery CT 750 HF; GE Healthcare, Waukesha, WI, USA). Flow readings acquired in ROI were normalized to those obtained in the aorta. Thus, results were not dependent on contrast agent concentration. At the time of examination, patients were asked for slow and shallow breathing to avoid artifacts. ## 2.2.1. CE-MDCT Protocol Radiographic examination comprised two phases. The first phase was performed for localizing kidneys and included a native, helical scan of the abdominal cavity, starting from diaphragm domes up to aortic bifurcation. In the second phase, the length of the scan area was set to 14 cm to complete both kidneys’ coverage. Every tested individual received 25 shuttle passes, providing 375 images. The total acquisition time of the second phase was 42.6 s. During the examination, a nonionic contrast medium (320 mg/mL Visipaque, GE Healthcare) was administered to each patient at a rate of 4.0 mL/s using a power injector. The scan delay was set AT 10 s. Technical data of the protocol are shown in Table 1. ## 2.2.2. Quantitative Analysis of Perfusion All scans were examined with Advantage Workstation server 4.7 (GE Healthcare, USA), with software CT perfusion 4D. Scans were evaluated by one attending physician with 20 years of experience with computer tomography. The software automatically calculated the blood flow (mL/100 g/min) corresponding to ROI perfusion. Three calculations were performed for each kidney in different regions: upper kidney pole, middle of kidney, and lower pole. To examine regional perfusion, we used manually set ROIs, not smaller than 7 mm2, which were located in the kidney cortex, where artifacts were smallest and the examined area was the most homogenous during the observation cycle. All set ROIs were automatically transformed into a perfusion map with the software (Figure 1, Figure 2 and Figure 3). ## 2.3. Kidney Ultrasound We performed a kidney ultrasound examination (Logiq P6, GE Healthcare, Seoul, Korea; equipped with a curved array probe of 2–5 MHz) to measure the kidney length and to estimate the parameters of kidney perfusion. Two or three segmental arteries localized in different regions of each kidney were evaluated in color Doppler and pulsed-waived Doppler technics to measure acceleration (ACC (cm/s2)), acceleration time (ACC (ms)), resistive index (RI (ratio)) and end-diastolic velocity (EDV (cm/s)) based on Doppler wave spectrum analysis (Figure 4) [2]. To assess the renal cortex perfusion (RCP) parameters, the dynamic tissue perfusion measurement (DTPM) method was used [16,17]. In this technique, we set the gain of the color Doppler on a constant level to record comparable results. After identification of the middle cortical segment of the kidney (localized between two medullar pyramids) in the longitudinal projection, a color Doppler frame was activated between the pyramids and renal capsule (Figure 5). Then, 3–5 s clips were recorded and transferred to PC software (PixelFlux, Chameleon Software, Leipzig, Germany). Semi-automatic color Doppler clips analysis resulted in perfusion parameters: dynamic renal cortex perfusion intensity (dRCP (cm/s)), dynamic resistive index (dRI (ratio)), and the dynamic pulsatility ndex (dPI (ratio)), which were considered for statistical analysis. ## 3. Results Thirty non-stenotic kidneys in twenty-five hypertensive patients (11M, 14F, age 58.9 ± 19.0) were included in the study. Twenty remaining kidneys met exclusion criteria because of nephrectomy (1 kidney) and >$30\%$ renal artery stenosis (19 kidneys). Demographic data and renal function of included patients are presented in Table 2. Three patients had CKD stage G1, seven had CKD G2, eleven had CKD G3, and four had CKD 4. Parameters of renal cortex perfusion estimated in CE-MDCT, conventional Doppler sonography, and DTPM are shown in Table 3. ## 3.1. Differences in CE-MDCT Measurements CE-MDCT results of renal cortical perfusion measured in different regions did not differ significantly (Figure 6). Moreover, we did not find any significant differences in perfusion parameters between the left and right kidneys (Table 4). In opposite to the other CE-MDCT measurements, due to having the lowest standard deviation and close to normal distribution, the result of the CBF measurement in the middle kidney pole was set as a reference for further analyses. Moreover, this localization of CBF measurement was close to the DTPM region of interest, which reduced discrepancies between these two methods. ## 3.2. Associations of Renal Cortex Perfusion Parameters CBF correlated significantly with age and eGFR. Moreover, RI, EDV, dRI, dPI, and dRCP were markedly related to CBF (Table 5). In the model of stepwise backward regression analysis, including age, BMI, creatinine, and eGFR, only age independently influenced CBF (R2 = 0.317, $$p \leq 0.001$$). Further regression analyses in conventional Doppler parameters and the DTPM method showed that RI and dRCP were independently associated with CBF (R2 = 0.290, $$p \leq 0.003$$, and R2 = 0.320, $$p \leq 0.001$$, respectively) (Table 6). Lastly, from considered ultrasound parameters, stepwise backward regression analysis showed dRCP as the only variable independently related to CBF (R2 = 0.317, $$p \leq 0.001$$). When the common ultrasound Doppler model was tested in stepwise forward regression analysis, only dRCP (as the first variable) and RI were independently related to CBF (R2 = 0.37, $$p \leq 0.003$$). ## 3.3. Relations of Perfusion Parameters with Kidney Function Ultrasound flow parameters correlated with CBF were also associated with kidney function. RI (r = −0.459; $$p \leq 0.012$$), EDV ($r = 0.672$; $p \leq 0.001$), dRI (r = −0.534; $$p \leq 0.002$$), and dRCP ($r = 0.707$; $p \leq 0.001$) were significantly associated with eGFR. In the model of stepwise backward regression analysis concerning CBF, RI, EDV, dRI, and dRCP only CBF and EDV were independently associated with eGFR (R2 = 0.510, $p \leq 0.001$). ## 4. Discussion In the presented study, we proved that renal cortex perfusion measured using the dynamic Color Doppler option and quantified in an external medical device (dRCP) is independently associated with renal cortical blood flow estimated in an objective CE-MDCT method (CBF). In recent years, the assessment of renal cortical perfusion has an increasing significance. Ma et al. investigated retrospectively 93 patients diagnosed for renal artery stenosis and found that RCP assessed in CEUS is correlated with renal function and the degree of stenosis [18]. In another work, renal cortex perfusion was the independent factor for renal function decline in 1 year of observation [19]. In the study conducted by Huo et al., semiquantitative estimation of renal blood flow was a good indicator of systemic and renal perfusion response to fluid resuscitation in patients with severe sepsis [20]. Although the DTPM method for renal cortex perfusion quantification was introduced over 15 years ago and is successfully used in many clinical applications, e.g., hypertension, glomerulonephritis, diabetic nephropathy, cardio-renal syndrome, vesicoureteral reflux, and renal neoplasm, it was not compared with a more objective and operator-independent method as CE-MDCT or magnetic resonance angiography [16,17,21,22,23,24,25]. In our work, considering all selected ultrasound flow parameters, dRCP estimated in the DTPM method had the strongest correlation with CBF. Nevertheless, from conventional ultrasound Doppler parameters, RI independently correlated with CBF. Thus, we confirmed that the renal resistive index measured in segmental renal arteries and the renal cortex perfusion estimated in the DTPM method are independently associated with the cortical blood flow in patients with hypertension and different stages of renal dysfunction. Recently, in the group of patients after thyroidectomy, we showed good repeatability of the DTPM method in estimating renal cortical perfusion [4]. Moreover, the diagnostic properties of RI were confirmed in earlier studies [1,14]. These data contribute to the use of the dynamic ultrasound assessment of renal cortex perfusion intensity (dRCP) or renal resistive index as perfusion markers in patients with hypertension and kidney disease. However, in hypotension, dehydration, sepsis, and shock, dRCP could be more accurate to CE-MDCT renal cortical blood flow than the RI [13,26]. Investigating acute kidney injury in a group of 50 patients with septic shock, Watchorn et al. showed that RCP measured in CEUS is independent of renal blood flow and RI [13]. However, this discrepancy can relate to $20\%$ lower renal cortex perfusion than renal blood flow in a healthy state and derangement between renal macro- and microcirculation in septic patients [26]. On the other hand, the superiority of dRCP over RI in expressing CBF can be related firstly to the exact cortical ROI localization and secondly to more accurate flow properties in bigger ROI than a single vessel flow assessment [27,28]. Our findings firstly entitled the use of renal resistive index as a marker of kidney perfusion and secondly show the DTPM as a better ultrasound non-contrast method to estimate this feature. Although performing DTPM is time-consuming and somewhat complicated, by the use of external software, the RI measurement is widely used. Renal resistive index is recognized as a marker of vascular alterations in cardiovascular diseases [1]. It could be used, among others, for hypertension monitoring and cardiovascular risk estimation, acute kidney injury recovery prediction, chronic kidney disease diagnosing and prognosis, renal autoregulation and microvascular diabetic complications assessment, and renovascular hypertension diagnosis and treatment prognosis [1,3]. Investigating 5950 patients with hypertension, Radermacher et al. found 138 participants with renal artery stenosis > $50\%$ [29]. They showed that a renal Resistive Index > 0.80 was associated with the lack of hypertension and renal function improvement after revascularization. Moreover, in another study, RI > 0.80 was connected with worse kidney outcomes and mortality despite the presence or absence of proteinuria [30]. Nevertheless, the elevated risk of unfavorable renal outcomes after revascularization probably starts with even lower RI values. Based on the case series, Cianci et al. suggested that RI > 0.75 at baseline and the absence of NGAL reduction after percutaneous renal artery angioplasty were associated with worsening renal function [31]. By showing an independent negative association of renal RI with kidney perfusion, we support a clear explanation for declining renal function in elevated RI circumstances. For an objective assessment of renal perfusion, we used the low-dose (40 mL) CE-MDCT method as a reference to the ultrasound flow parameters. Using low-dose contrast agents could be associated with worse image quality and misdiagnosis. On the other hand, low-dose contrast-enhanced CT for perfusion assessment is recommended for all patients if the method is sufficiently diagnostic [32]. Similarly to our study, Asayama et al. used a low-dose contrast agent (40 mL) CT and compared image noise, overall quality, and perfusion parameters in reconstructed data of renal tumors with conventional contrast-enhanced CT [33]. Although image noise was higher and overall image quality was lower in low-dose CT than in conventional procedures, arterial visualization was improved, and perfusion parameters and tumor detection were comparable between these two techniques. We investigated renal cortical blood flow in the CE-MDCT method in three different kidney localizations and found no significant differences in perfusion parameters. These data are consistent with the findings of Liu et al., who investigated renal perfusion in 43 patients with aortic dissection in 320-row CT using ROIs selected in four points at the axial or three points at the coronal plane (upper pole, hilum, and lower pole) of the kidney and found similarity of readings taken from these different positions [34]. Impaired renal perfusion can be the cause and the marker of kidney dysfunction. Although our results showed significant associations of Doppler parameters with cortical blood flow and kidney function, these relations were not obvious. The result of the dynamic assessment of renal cortex perfusion intensity was independently correlated with CE-MDCT cortical blood flow. Nevertheless, this association with kidney function was not as strong as CBF and EDV. Presented data are consistent with recent studies reporting a close relationship between EDV and kidney function, in contrast with other Doppler perfusion parameters that derive from the end-diastolic velocity [10,35,36]. Although our results are satisfactory, the presented study has some limitations. Firstly, the group is relatively small and encompasses patients with hypertension and mild-to-severe chronic renal impairment. 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--- title: A Molecular Docking Study Reveals That Short Peptides Induce Conformational Changes in the Structure of Human Tubulin Isotypes αβI, αβII, αβIII and αβIV authors: - Oluwakemi Ebenezer - Nkululeko Damoyi - Michael Shapi - Gane Ka-Shu Wong - Jack A. Tuszynski journal: Journal of Functional Biomaterials year: 2023 pmcid: PMC10054586 doi: 10.3390/jfb14030135 license: CC BY 4.0 --- # A Molecular Docking Study Reveals That Short Peptides Induce Conformational Changes in the Structure of Human Tubulin Isotypes αβI, αβII, αβIII and αβIV ## Abstract Microtubules are cylindrical protein polymers assembled in the cytoplasm of all eukaryotic cells by polymerization of aβ tubulin dimers, which are involved in cell division, migration, signaling, and intracellular traffic. These functions make them essential in the proliferation of cancerous cells and metastases. Tubulin has been the molecular target of many anticancer drugs because of its crucial role in the cell proliferation process. By developing drug resistance, tumor cells severely limit the successful outcomes of cancer chemotherapy. Hence, overcoming drug resistance motivates the design of new anticancer therapeutics. Here, we retrieve short peptides obtained from the data repository of antimicrobial peptides (DRAMP) and report on the computational screening of their predicted tertiary structures for the ability to inhibit tubulin polymerization using multiple combinatorial docking programs, namely PATCHDOCK, FIREDOCK, and ClusPro. The interaction visualizations show that all the best peptides from the docking analysis bind to the interface residues of the tubulin isoforms αβl, αβll, αβlll, and αβlV, respectively. The docking studies were further confirmed by a molecular dynamics simulation, in which the computed root-mean-square deviation (RMSD), and root-mean-square fluctuation (RMSF), verified the stable nature of the peptide–tubulin complexes. Physiochemical toxicity and allergenicity studies were also performed. This present study suggests that these identified anticancer peptide molecules might destabilize the tubulin polymerization process and hence can be suitable candidates for novel drug development. It is concluded that wet-lab experiments are needed to validate these findings. ## 1. Introduction Microtubules are cylindrical protein polymers assembled in the cytoplasm of all eukaryotic cells by polymerizing αß-tubulin heterodimers, which are involved in multiple biological functions such as cell division, migration, signaling, and intracellular traffic. These functions, especially the formation of mitotic spindles, make them important participants in the initiation and proliferation of cancerous cells and their subsequent metastases [1,2]. They exhibit an irregular temporal pattern of assembly and disassembly, which has been termed dynamic instability [3]. In addition, altered tubulin polymerization is detrimental to the formation of the tumor vascular system during the process of angiogenesis, which is a hallmark of cancer. Hence, unsurprisingly, the microtubular cytoskeleton and its building blocks, tubulin dimers, have become one of the key targets in cancer chemotherapy [4]. It is important to note that both α- and β-tubulin monomers are expressed by different genes and occur in the form of numerous isotypes, which differ in their amino acid sequence leading to slight structural changes, especially in the binding pockets of tubulin-targeting ligands [5]. Moreover, different β-tubulin isotypes exhibit a unique dynamic behavior manifested by different interactions with ligands, such as anti-tubulin drugs, both in vitro and in mammalian cells [6,7,8]. A promising tactic to disrupt tubulin polymerization and the development of microtubules is to interfere with the protein–protein interactions responsible for the self-assembly of microtubules. While the traditional approach to cancer chemotherapy has been based on small molecule development, short peptides have recently become the focus of new efforts to find more efficacious and less toxic drug candidates. Extensive research has been undertaken to investigate the use of peptides with a good safety profile to inhibit cancer and many other diseases [9,10]. Pieraccini et al. [ 11] reported modeling protein-protein interfaces and identified the amino acids responsible for peptide–tubulin binding. Thus, engineered peptides that produce anti-tubulin activity both in vitro and in cultured cells have been discovered [11]. This is of major significance since small molecules typically bind to pockets and grooves on target proteins but are seldom suitable for binding to flat protein-protein interfaces. Tubulin polymerization has been targeted by natural peptides or depsipeptides isolated from a wide range of organisms but with atypical amino acids. Among the peptides, dolastatin or cryptophycins, are regarded as promising anticancer drugs. At the same time, derivatives of these peptides such as dolastatin 10, crytophycin 1, phomopsin A, and hemiasterlin impede the binding of vinca alkaloids to tubulin in an uncompetitive way. Therefore, the subject of intensive pharmacological research is to identify similar pharmacophores. In addition, isotypes of tubulin βII, βIII, and βIV were also found to have a degree of difference in chemical affinities for various anticancer drugs such as taxol, colchicine, DAMA-colchicine, and nocodazole [12,13,14]. As a result, these drug-resistant tubulin isotypes have become attractive targets for developing novel anticancer agents. While treatments based on targeting microtubules have transformed cancer therapy, drug resistance and detrimental side effects that accompany the action of all known tubulin-binding agents remain significant drawbacks. It is therefore increasingly advisable to adopt new strategies by exploring the different profiles of tubulin isotypes in an effort to overcome the drawbacks plaguing the existing tubulin-binding drugs. Herein, we utilized peptide structure prediction, homology modeling, molecular docking, molecular dynamics simulations, and binding free-energy calculations to identify human tubulin isotypes-targeting peptides from a set of short antimicrobial peptides with potential for anticancer repurposing. We hope that the series of peptides identified in this study may offer benefits for the early discovery of a pharmacophore of interest because of their promising binding interactions with the family of tubulin protein isoforms predicted computationally in our work. ## 2.1. Peptide Screening and Preparation We explored the DRAMP (data repository of antimicrobial peptides) database in this work [15]. DRAMP is an open-access and manually curated database containing diverse annotations of AMP, including information on their sequences, structures, biological activities, physicochemical, patent, clinical, and references of the peptides. DRAMP currently contains 22,407 entries, 6032 of which are general AMPs (having both natural and synthetic AMPs), 16,110 patented AMPs, 77 AMPs in drug development (preclinical or clinical stage), and 188 stapled antimicrobial peptides belonging to specific AMPs. To expand the scope of AMPs’ design, DRAMP also holds 5909 candidate AMPs screened by some platforms whose antibacterial activities have not been assayed yet. In this study, we screened 826 peptides derived from plant sources. Anticancer peptides were extracted from the database. The peptides that did not have accurate information regarding their activity or function in the database were discarded. The peptides with more than 50 amino acids in length were also removed as being unlikely to hold promise for drug development. In addition, anticancer peptides with nonentity amino acids in their sequences were eliminated. The PEP-FOLD 2 webserver was used further to predict the information structure of 13 sequence peptides [16]. This web server visualizes the peptide structure using a hidden Markov model suboptimal sampling algorithm [17]. It uses a coarse-grained energy force field without including conformational entropy. ## 2.2. Homology Modeling and Protein Preparation The sequences of human α and β tubulin isotypes were downloaded from the universal protein resource (UniProt) [18] (Q71U36: α-tubulin, P02773, Q13885, Q13509 and, P04350: βl-βlV-tubulin proteins). The 3D structure of bovine tubulin (Q2HJ86 and Q6B856: αβ-tubulin chain (Bos taurus)) was downloaded from the Protein Data Bank (PDB ID: 1SA0) as the template structure. The complex includes two tubulin αβ heterodimers, while the native ligand, namely, colchicine, is bound to β subunits at the interface with the α subunit. The homology model of the human tubulin was built with SWISS-MODEL [19]. The native ligand in the template structure was deleted before homology modeling was performed. The stereochemical quality of the template (referred to as tubulin 1SA0 hereafter) and the various tubulin isotypes were evaluated using PROCHECK [18]. Subsequently, the Verify-3D [20] and ERRAT [21] algorithms were employed to check the reliability of the generated models. The Ramachandran plots for all the isotypes are shown in Figure S1. All the structures resulting from the modeling αβl, αβll, αβlll, and αβlV were further subjected to protein preprocessing, optimization, and minimization using the protein preparation in the Schrodinger suite [22]. ## 2.3. Molecular Docking After cleaning the proteins using the protein preparation tool in the Schrodinger software suite, the output was used for the protein-peptide molecular docking. PATCHDOCK [23] and ClusPro [24] web servers were used to analyze their interactions. FIREDOCK (Fast Interaction Refinement) webserver was used for further refinement [25]. The top 10 model solutions were determined and analyzed. The PATCHDOCK web server with default parameters was used to predict the best conformations. Since a rigid approach was utilized to obtain the docking solutions and because during protein−protein interactions, both side chains and backbones might change their conformation. The top 10 solutions were subjected to the FIREDOCK webserver to refine the interaction of protein–protein complexes resulting from molecular docking [25]. FIREDOCK performs side chain optimization and rigid body minimization to provide more extensive refinement. Subsequently, scoring and ranking identified the near-native advanced solutions. The final selection of the best-docked complexes was based on the global energy of the bound, predicted complexes after the refinement. ## 2.4. Molecular Dynamics The molecular dynamics (MD) simulations were evaluated using the Desmond simulation package embedded in the Schroedinger suite [26]. Before the MD simulations were performed, the molecular system, including the protein, water molecules, and ions, was built. The water molecules were described using the TIP3P (transferable intermolecular potential with 3 points) model in an orthorhombic cubic box. The boundary condition box volume was computed according to the complex type and counter ions, including Na+ and Cl−, to neutralize the system. The NPT ensemble with temperature and pressure of 300 K and 1 bar, respectively, was used in all the analyses for all the selected docked peptides in the αβl-αβlV tubulin receptor. The force field of OPLS_2005 was applied. Simulation progress was verified stepwise every 50 ps. The NPT assembly was launched following the simulation process, which covers the production of 100 ns. The frames were assembled and examined using the simulation interaction diagram that helped determine the fluctuations. ## 2.5. Post Molecular Dynamics MM-GBSA The Molecular Mechanics-Generalized Born and Surface Area Continuum Solvation (MM/GBSA) was calculated for each MD trajectory using the thermal MM/GBSA script [27]. This was run via the Python command line. The average binding energy was calculated for 20 snapshots from the overall trajectory of 100 ns. ## 2.6. Physicochemical, Allergenicity, and Toxicity Prediction Physicochemical, allergenicity, and toxicity assessments of the best peptides from the docked analysis were evaluated. The physiochemical properties of the best peptides were evaluated using ProtParam tools [28], which allow predicting the relevant properties, such as molecular weight, net charge at pH 7, peptide properties, stability, and charge. The AllerTop server was used to evaluate the nonallergenic nature of the peptides [29]. ## 3. Results and Discussion We retrieved plant peptides from the DRAMP database. The 13 peptides shown in Table 1 and Figure 1 were extracted from the set of plant-based peptides. Figure 2 displays the respective structures of the peptides. Our 3D predicted structures may not represent the native conformation in the plant, but they do represent at least one version of what might be created in the wet lab experiments. Which are linear cyclotides and they are aimed to be anticancer lead compounds. The Ramachandran plots obtained by PROCHECK found $85.1\%$ of residues in the most favored regions, $11.4\%$ in the additional allowed regions, and $2.3\%$ in generously allowed regions for αβI (see Table S1 and Figure S1). For αβII, $83.4\%$ of residues in most favored regions, $13.3\%$ in additional allowed regions, and $1.1\%$ in generously allowed regions were found. In the αβIII, $83.7\%$ of residues in the most favored regions, $12.9\%$ in additional allowed regions, and $2.4\%$ in generously allowed regions were observed. On the other hand, in αβIV tubulin, $84.1\%$ of residues are found in most favored regions, $12.7\%$ in additional allowed regions, and $2.3\%$ in generously allowed regions. The results from the overall quality factor obtained by the ERRAT agreed with the acceptable range (>50 for a high-quality model) [30]. The overall quality factor obtained by the ERRAT tool for the isotypes αβI-αβIV was found to be $91.32\%$, $80.86\%$, $82.68\%$, and $90.7\%$, respectively. Subsequently, VERIFY3D was used to confirm that at least $80\%$, $97.56\%$, $96.52\%$, and $97.79\%$ of the amino acids of all the analyzed isotypes achieved an average 3D/1D score higher than 0.2. In particular, most residues are found in the most favored regions; therefore, the built model was deemed reliable. The identification of the binding site is significant for elucidating the actual binding mechanisms as well as the interaction between a drug and a protein. To characterize this, we used molecular docking and MD simulations, which are standard, generally accepted theoretical prediction approaches for examining peptide binding sites in the various protein receptors. ClusPro was used to reexamine the peptides with the best-docked results from the FIREDOCK. The ClusPro score of docked peptides in αβIII and αβIV tubulin corroborates the result of the FIREDOCK. However, the results of αβI and αβII-tubulin obtained from CluPro and FIREDOCK do not corroborate it. Further, the peptides with the lowest global energy from the FIREDOCK (Table 2) were utilized for further analysis. The MD simulation analysis was carried out on the complexes in order to answer many relevant inquiries, such as the stability and accuracy of the binding mode and the ligand stability over the simulation period. Most of the interactions predicted in the docking analysis of the lead peptides were stable within the binding site. They interacted appropriately with different target regions by forming hydrogen bonds, as well as hydrophobic and electrostatic connections directly with protein side chains. ## 3.1. Peptide-αβI-Tubulin Complex The DRAMP00782 peptide (Figure 3a) had the best FIREDOCK global energy estimate of −65.44 kcal/mol. The binding energies for the DRAMP0776, DRAMP00783, and DRAM00789 peptides in FIREDOCK were estimated as −65.14, −56.63, and −54.12 kcal/mol, respectively, whereas the binding energies in ClusPro were −858.2, −738.0, −761.9, and −983.3 kcal/mol, respectively. The nonbonded interactions between the peptide molecules and the αβI-tubulin receptor are shown in Figure 3b. The DRAMP00776-αβ-tubulin complex was stabilized by five hydrogen bonds at αAsp224, αThr221, αArg359, βArg46, αGly223, and βASP355 and accompanied by one hydrophobic bond at αHis227. The DRAMP0782 peptide and αβ-tubulin receptor formed seven hydrogen bonds at βAsp355, αLys19, and αGly223, accompanied by four hydrophobic interactions at βPro243, βLeu42, αPro80, and αPhe81, and four electrostatic interactions at αLys19, βAsp355, βGlu45 and αGlu22 (Figure 2b, Table 3). DRAMP00783 peptide and αβ-tubulin receptor complex formed five hydrogen bonds at αSer78, βGly79, αGlu223, αTyr222, αAsp244, βAsp355, αGln15, αSer75, αThr221, αSer78, and αAsp224 and three hydrophobic interactions at αTyr222, βLeu42, and αAla18. The DRAM00789 peptide and αβ-tubulin receptor complex displayed ten hydrogen bonds at αGln279, βMet321, βMet323, αThr219, βAsp355, βGln245, αGly360, βSer322, and βASP355 and one hydrophobic bond at βArg320 (see Figure 2b, Table 3). Peptide binding to the receptor may cause the target molecule to inhibit its interactions. All these results confirmed that the four peptides could effectively repress tubulin interactions by occupying the interface of the αβI-tubulin dimer. The molecular dynamics simulations of the active peptides bound to the αβ tubulin heterodimer were carried out to confirm the structural rigidity and to validate the docking outcomes for the complexes. RMSD values of C-alpha atoms (Cα) have been studied to understand structural inflexibility. The results demonstrated that the DRAMP00776, DRAMP0782, DRAMP00783, and DRAM00789 complexes showed initial RMSD increases due to instability. The increase in RMSD was higher for the DRAM00789 peptide complex than for the other complexes. This result corroborates the molecular docking result. The trend in the RMSD was maintained between 40 and 65 ns, after which instability occurred. Meanwhile, DRAMP00776, DRAMP0782, and DRAMP00783 maintained stability from 70 ns to the end of the simulation period. Although the DRAMP00789 complex had a higher RMSD trend during the initial phase, the RMSD profile decreased with an increase in the simulation time (from 40 ns to 100 ns, see Figure 4). The average RMSD profile of the complexes formed with DRAMP00776, DRAMP00782, and DRAMP00783 was between 2.5 Å and 2.8 Å, respectively. The overall RMSD estimate for DRAMP00779 was 3.5 Å, and fluctuations were observed throughout the simulation time, indicating overall structural instability because higher RMSD profiles for Cα atoms are indicators of low stability (Figure 4A). DRAMP00776 formed hydrogen bonds with the residues, αLys19, αAsn226, αArg276, αGln15, αGly71, αSer75, αGly79, αPro80, αGly223, and αGlu22, respectively. Compared to the interacting residues before MD simulations, DRAMP00783 peptides shift from the initial binding position. DRAMP00783 interacts with αGln15, βAsp355, βGln245, αAsp74, and βAsp355 via hydrogen bonding, which is accompanied by three hydrophobic interactions via βMet323, βVal353, and αTyr222 (Table 2). It was also observed that the higher the hydrophobic interaction, the better the binding energy. RMSF plots provide information on the flexible regions of the MD simulated structures. Flexible regions display a higher RMSF value, while constrained regions display a low RMSF value. There were no significant fluctuations in amino acid residues in the β-monomer after binding the peptides. The calculated RMSF for DRAMP00776, DRAMP00782, and DRAMP00783 was analyzed, and the peptides exhibited lower flexibility, below the 4 Å range, as shown in Figure 4B. ## 3.2. Peptide-αβII-Tubulin Receptor Complex The binding region surrounding the peptides consists of residues within a 4 Å range from the peptide atoms (Figure 5a). Subsequently, two peptides were found to have potent binding energy, namely, DRAMP00779 and DRAMP00788, respectively, after docking the extracted peptides to the αβII-tubulin dimer. For the DRAMP00779 complex, the residues αArg221, αGlu279, αGlu77, αThr82, αArg229, αThr225, αThr82, αTyr83, αAla19, αGly365 were detailed in the α-tubulin and βGln245, βGlu45 in the β-tubulin subunit (Figure 5b). While residues αArg221, αThr225, and αTyr224 were detailed in the α-tubulin βLeu246, βAsp41, and βAsp41 in the β-tubulin subunit for the DRAMP00788 complex (Figure 5b, Table 4). The trajectories obtained from a set of MD simulations correspond to conformational changes of the complex of DRAMP00779 and DRAMP00788, and the corresponding data for individual biological systems were analyzed. The difference in the RMSD of the liganded and the unliganded tubulin heterodimer is not so dramatic (Figure 6A). The structural motions of the residues in each tubulin subunit achieve additional stability upon binding the peptides. The primary residues involved in the interaction of the DRAMP00779 complex after 100 ns of simulation time include αGly81, αArg221, βMet323, αGly81, αThr80, βAsp355, αArg221, αGly365, βMet321 (conventional and carbon–hydrogen bonds). Hydrophobic and electrostatic interactions also stabilized the complex. While DRAMP00788 interacted with residues, αAsp76, αGlu77, αArg221, αGly365, αAsp76, αGlu77, αArg221, αThr80, αGly81, βMet323, βLys324, βMet323, βAsp355, βLeu42, βMet321, and βLys324. Furthermore, the peptide formed distinct interactions such as electrostatic, hydrophobic, and hydrogen bonds with the intermediate domain residues of the αβ tubulin dimer (206–381). The domain opens with helices H6 and H7, a long loop, and helix H8 at the longitudinal interface sandwiched between the monomers. Many areas of the outer surface of tubulin are negatively charged and can attract hydrogen ions [31]. These regions play a role in tubulin–tubulin interactions and tubulin interactions with motor proteins such as kinesin. The MD results demonstrate that DRAMP00779 interacts electrostatically more strongly than DRAMP00788. To explore the atomic fluctuations at the binding sites in detail, we determined the RMSF value of each amino acid residue at the αβ tubulin binding site (Figure 6B). The residues fluctuated at the N-terminal domain (amino acids 1 to ~205). The atomic fluctuation profile shows a low fluctuation of the DRAMP00779 and DRAMP00788–tubulin complex in the α-tubulin compared to the β-tubulin monomer. ## 3.3. Peptides-αβIII-Tubulin Dimer Complex The DRAMP00776 and DRAMP00781 peptides bind to the αβlll-tubulin dimer with binding energies of −43.38 and −32.08 kcal/mol, respectively, which represents a strong binding affinity of the peptides to the αβlll-tubulin dimer (Table 2 and Figure 7a). The docking result gives an idea about the principal binding sites of DRAMP00776 and DRAMP00781 on the α-tubulin monomer surface, to a lesser extent on the β-tubulin monomer surface. Figure 7b and Table 5 indicate that DRAMP00776 expressly interacts with αGlu22, αThr82, αArg229, αAsn18, αGlu22, αThr82, and αTyr224 on α-tubulin, and it also interacts with residues, βGly244, βLeu246, βPro243, on β-tubulin. While DRAMP00781 binds to residues αThr225, αArg229, αGlu22, αGlu22, αThr225, αGln11, αPro364, and αTyr224 on the α-tubulin surface, and residues βGly244, and βLeu246 on the β-tubulin surface. The αβ-tubulin interface exhibits hydrogen bonding with DRAMP00776 and DRAMP00781, within a 4 Å range. The docking results suggest that the hydrogen bonds are vital for binding between DRAMP00776 and DRAMP00781 and the αβlll-tubulin dimer. In contrast, hydrophobic and electrostatic interactions also provide a minimal contribution to stabilizing the complexes. To investigate the conformational fluctuations, the aggregate RMSD deviations of tubulin atomic coordinates were considered during the interaction of DRAMP00776 and DRAMP00781 with the αβlll-tubulin dimer (Figure 8A). A specific ligand should interact with the H6-H7 loop to efficiently inhibit the switch of nucleotide in tubulin (T216-Y224) [32,33]. Meanwhile, the H6-H7 loop favors hydrophobic interactions; thus, DRAMP00776 formed a hydrophobic interaction with αTyr224, while DRAMP00781 formed hydrophobic interactions with the βPro243 residue in the H6-H7 loop. Both peptides interact with residues at the H7-H8 loop (βGln245 and βGly244) via hydrogen bonding. As mentioned above, both peptides have a similar binding landscape and exhibit similar RMSD values of ~3.2 Å. The calculation of RMSF is an exceptional tool to determine local protein mobility. However, the rate of hydrogen bond formation may be directly implicated in the flexibility of peptides in the binding site, as shown in the RMSF graph (Figure 8B). ## 3.4. Peptide-αβIV-Tubulin Receptor Complex The DRAMP00776 and DRAMP00784 bind to the αβlV-tubulin receptor (Table 2 and Figure 9a) with binding energies of −42.27 and −48.97 kcal/mol, respectively, which shows a strong binding affinity of the peptides with the αβlV-tubulin receptor compared to their counterpart. The visualization of the docking result details the binding sites of DRAMP00784 and DRAMP00776 on αβIV-tubulin. DRAMP00776 and DRAMP00784 display a similar extent for the α and β-tubulin monomers. Figure 9b and Table 6 show that DRAMP00776 specifically interacts with αGlu113, and αLys96, at α-tubulin, and it also interacts with residues, βGlu158, βAsp161, βPro160, and βGlu125, in β-tubulin. By comparison, DRAMP00784 forms attractive charge interactions with residues αGln31, αThr82, αAsn228, αArg229, βGly244, and αGlu22, respectively. This is accompanied by four hydrogen bonds with αThr82, αThr225, αGln15, βGly244, and βGln245 (Figure 9b, Table 6). The αβ-tubulin interface exhibits hydrogen bonding with DRAMP00784 and DRAMP00776 within a 4 Å range. The stability of the DRAMP00784 and DRAMP00776 peptides with the proteins was observed for the complete length of the simulation. The RMSD analysis shows that the protein complexes made with DRAMP00784 and DRAMP00776 were stabilized after 70 ns of the simulation time, and this was maintained for DRAMP00776 until the completion of the simulation (Figure 10A). Meanwhile, the RMSD of DRAMP00784 displayed a deviation between 80 ns and 90 ns and continued in a stable conformation until the completion of the simulation. The two peptides maintained contact with the proteins by hydrogen bond interactions with residues αThr109, βPhe159, βPro160, αThr94, αGly95, βAsp128, βCys127 αGly95, βGlu125, and βAsp128 for DRAMP00776 and αGlu77, αAsn228, αGln15, αThr73, αAsn18, and βAsp41 for DRAMP00784. The RMSF values for each amino acid residue in the protein backbone are depicted in Figure 10B. The peaks represent the fluctuation of every amino acid residue throughout the simulation. This means that higher RMSF values represent greater flexibility of residues, while lower RMSF values reflect lower flexibility of residues and better system stability. The RMSFs of the α and β-domains are depicted separately. A slight amount of fluctuation in residues present at the active site indicates minimal conformational change, implying that the reported lead compound was consistently bound to the target protein. ## 3.5. Post-MM-GBSA Analysis The post-MM-GBSA analysis of the free binding energy calculation was carried out by processing and analyzing the frame generated during molecular dynamics with a 10-step sampling size using the thermal MM-GBSA script in the Schrödinger suite. These are generally based on simulations of the molecular dynamics of the receptor–ligand complex. Consequently, they are intermediate in precision and computational effort between empirical scoring and strict alchemical disturbance methods [34]. These estimates have been applied to various systems with varying degrees of success. The free energies of binding have been enhanced after the post-MM-GBSA for all the analyzed compounds. The estimated values were negative for all the active docked complexes, of which DRAMP00776 showed the most negative MM/GBSA value (−109.02 kcal/mol), followed by DRAMP00783 (−87.04 kcal/mol) and DRAMP00789 (−64.01 kcal/mol) for the αβI-tubulin complex. DRAMP00789 peptides have low binding energy, which may have led to the instability of the peptides during the MD simulations, as represented in the RMSD and RMSF results. The results show that compound DRAMP00776 has a substantial binding energy based on the docked result and a significant post-MM-GBSA compared to the other compounds. These results indicate that the inhibition activity of DRAMP00776 against αβI-tubulin is likely to be more substantial compared to the other compounds. DRAMP00779 has a binding energy of −93.66 kcal/mol, whereas DRAMP00788 has a binding energy of −80.72 kcal/mol, which directly reveals the complex’s stability for αβII-tubulin. Notably, the high binding free energy was apparently due to strong electrostatic interactions, which demonstrate significant contributions of residues βLys324, αGlu77, αAsp76, βAsp355, and βAsp39, which were lacking in the binding of DRAMP00788. DRAMP00776 (−107.20 kcal/mol) exhibits superior predicted binding energy to the αβIII-tubulin dimer compared to the DRAMP00781 peptide (−106.12 kcal/mol). Moreover, both peptides show good stability results in this study, which corroborate with their ClusPro and the global energy value obtained in the docking analysis. Nevertheless, this provides initial evidence that these peptides represent potential candidates for the development of novel therapeutic applications to cancer cell inhibition, which renders them suitable for further examination. The binding energy calculation of the peptides-αβIV-tubulin complex shows that the average binding free energies of the DRAMP00776 and DRAMP00784 docked complexes are −102.97 and −104.90 kcal/mol, respectively. The resulting binding energy difference could be due to hydrophobic interactions between DRAMP00784 and the αTyr224 residue (H6-H7 loop), which are lacking in the DRAMP00776 docked complex. The MM-GBSA data suggest that the intermolecular electrostatic, hydrophobic, and hydrogen bonding interactions are vital in the binding of the peptides to the respective tubulin receptor sites. The more pronounced stabilization observed in the evaluated peptides appears to correlate with their binding energy. Importantly, the activity or inactivity of the peptides that inhibit tubulin polymerization corresponds to their tubulin-binding ability as assessed by the molecular dynamics simulation results [11]. ## 3.6. Physicochemical, Allergenicity, and Toxicity Prediction The physicochemical properties of the peptide sequences of interest were generated using the Expasy web server tool. The following properties were examined: length, aliphatic index, instability, and molecular weight (Table 7). Peptides DRAMP00782 and DRAMP00789 were determined to be unstable, with an instability index of 50.50 and 50.46, respectively. These peptides will most likely also be found unstable in vitro because a value of the instability index above 40 is considered unstable. Thus, preventive procedures are to be taken to stabilize the unstable therapeutic peptides through suitable biochemical processes. In comparison, the remaining peptides are predicted to be stable. Further, the sizes of the peptides range from 378 to 434 atoms, with molecular weights between 2902 and 3199 Dalton. The theoretical isoelectric point (pI) denotes the respective pH of the peptides. The predicted aliphatic indices of the peptides were found to be 84.84, 46.90, 74.67, and 50.35 for peptides DRAMP00776, DRAMP00782, DRAMP00783, and DRAMP00789, respectively. The aliphatic index often indicates the relative volume of the aliphatic lateral chains (alanine, valine, isoleucine, and leucine). This is a positive factor in increasing the thermostability of globular proteins. In terms of residue charge, DRAMP00776, DRAMP00779, and DRAMP00783 tended to be charged negatively. AllerTOP was used for the in silico prediction of allergens based on the primary physicochemical properties of proteins. Meanwhile, the application uses the amino acid z-descriptors, ACC protein transformation, and k nearest neighbors clustering parameters. Most of the peptides are non-allergic and non-toxic, apart from the DRAMP00779 and DRAMP00783 peptides, which are identified as possible allergens. The ToxinPred results for all the active peptides showed that they were non-toxic compared to the mutated peptides. Interestingly, all the peptides belong to the cyclotide family, with most of them classified as plant defensins. Cyclotides are macrocyclic peptides with a knotted arrangement of three disulfide bonds formed from their six conserved cysteine residues. They contribute to their exceptional stability and natural functions as plant defense peptides. Cyclotides have many pharmaceutically relevant activities, especially their significance in drug design. Several synthetic cyclotides have also been made for applications in drug design. The first cyclotides were generated during the rise of natural products through their discovery as active compounds in studies that screened plant extracts for medicinal properties [35,36,37,38]. They were initially discovered because of their uterotonic activity by identifying Kalata B1 as an active agent from Oldenlandia affinis, thus used in African traditional medicine as a utertonic tea to quicken childbirth [39]. Circulin A and circulin B isolated from *Chassalia parvifolia* extract have been reported to act as anti-HIV agents [40]. Hence, further explorations of the best plant-based peptides analyzed in this work, as tubulin polymerization agents are hoped to be of great benefit. After the MD analysis, all the peptides were found to lack interactions with residue β45. This may affect the microtubule dynamics in the class βII-VIII isotypes [3]. Our results also conclude that the different β tubulin isotype interactions with the peptides are unique. Among the docked peptides, DRAMP00776 was found to be involved in strong interactions with αβI, αβIII, and αbIV tubulin proteins. However, it shows superior binding energy with αβI (−109.02 kcal/mol) and αβIII (−107.20 kcal/mol), compared to αβIV (−102.97 kcal/mol). Numerous preclinical studies have demonstrated that elevated levels of βIII-tubulin expression are linked with drug resistance in human cancer cell lines such as lung, ovary, prostate, and cancer [41]. On the other hand, the βI-tubulin isotype is the most highly expressed tubulin isoform in humans and the most common isotype found in cancerous cells, hence its importance as a target for inhibition in cancer cells. Chemical synthesis can readily produce the promising peptide for the respective tubulin isotypes since specific differences will result in an improved therapy protocol. Moreover, recombinant technologies can be employed to satisfy the multiple prerequisites, which are in place in the pharmaceutical sector. Peptides can be efficiently designed, functionalized, and modified to optimize their bioavailability, stability, specificity, and effectiveness to enable the peptide to fulfill clinical drug requirements [42,43]. ## 4. Conclusions An in silico analysis of the protein–peptide interactions by docking using tubulin dimers as targets was carried out in sequence with molecular dynamics. In this study, the four most important isotypes of β-tubulin were explored (βI–βIV). Reported peptides with potential anticancer properties can serve as potential candidates for developing new therapeutic options for destabilizing microtubules. Consequently, they can provide candidate structures for anticancer applications. Interfering with mitotic spindle formation is a time-tested strategy for cancer chemotherapy design and development. The molecular dynamics simulation was further explored to rule out false interactions and investigate the stability of the proteins when interacting with the selected peptides. In addition, allergenicity profiling confirmed the non-allergic properties of the peptide molecules selected in this current study. The subsequent data analysis has led to the identification of the most promising peptide molecules that bind to the residues in the tubulin dimer and thus inhibit its polymerization dynamics. The presence of minor variations of peptide binding in the protein structure of β-tubulin isoforms can be an initial step for developing a new medicinal product with high levels of selectivity and specificity for a tubulin isotype of choice. 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--- title: Impact of Prenatal Health Conditions and Health Behaviors in Pregnant Women on Infant Birth Defects in the United States Using CDC-PRAMS 2018 Survey authors: - Girish Suresh Shelke - Rochisha Marwaha - Pankil Shah - Suman N. Challa journal: Pediatric Reports year: 2023 pmcid: PMC10054588 doi: 10.3390/pediatric15010015 license: CC BY 4.0 --- # Impact of Prenatal Health Conditions and Health Behaviors in Pregnant Women on Infant Birth Defects in the United States Using CDC-PRAMS 2018 Survey ## Abstract Objective: To assess both individual and interactive effects of prenatal medical conditions depression and diabetes, and health behaviors including smoking during pregnancy on infant birth defects. Methods: *The data* for this research study were collected by the Pregnancy Risk Assessment Monitoring System (PRAMS) in 2018. Birth certificate records were used in each participating jurisdiction to select a sample representative of all women who delivered a live-born infant. Complex sampling weights were used to analyze the data with a weighted sample size of 4,536,867. Descriptive statistics were performed to explore frequencies of the independent and dependent variables. Bivariate and multivariable analyses were conducted to examine associations among the independent and dependent variables. Results: The results indicate significant interaction between the variables smoking and depression and depression and diabetes (OR = 3.17; p-value < 0.001 and OR = 3.13; p-value < 0.001, respectively). Depression during pregnancy was found to be strongly associated with delivering an infant with a birth defect (OR = 1.31, p-value < 0.001). Conclusion: Depression during pregnancy and its interaction with smoking and diabetes are vital in determining birth defects in infants. The results indicate that birth defects in the United States can be reduced by lowering depression in pregnant women. ## 1. Introduction Birth defects are a primary cause of fetal death, infant mortality and morbidity, and long-term disability. Birth defects affect the quality of life of these infants and pose a burden for their families and society. According to the World Health Organization (WHO), about 300,000 newborns diagnosed with birth defects die within the first 28 days of life [1]. Approximately $3.3\%$ of live births in the United States constitute severe birth defects [1]. Birth defects result in an increased cost of care for children born with a birth defect compared to those with no birth defects [2]. The increased cost of care affects access to oral health care for children with birth defects [2]. Birth defects represent a significant public health issue due to their long-term individual and social consequences. Diabetes mellitus (DM) is a metabolic disease that results in hyperglycemia and is caused by either the low level of insulin in the body or resistance to insulin [3]. The overall prevalence ratio of offspring with any form of birth defects in women with pre-existing diabetes is $5.88\%$ compared to women without diabetes or gestational diabetes [4]. In pregnant mothers, Type 1 and Type 2 diabetes show a stronger association with craniofacial abnormalities in offspring, indicating a prevalence ratio of 8.9 compared to non-diabetic women [4]. Several studies indicate that birth defects are associated with maternal smoking [4,5]. In a systematic review of 38 studies, 13 studies indicated a significant association between smoking and orofacial clefts with a pooled odds ratio of 1.28, and 6 studies revealed a dose-response relationship [6,7]. Another meta-analysis using 29 case-control and cohort studies could not detect a dose-response relationship; however, it indicated a moderate risk of birth defects associated with smoking during pregnancy with an odds ratio of 1.29 [7]. Likewise, prenatal depression among pregnant women poses a comprehensive public health problem and is a potential risk factor for adverse birth outcomes [8]. A cross-sectional study conducted in Wuhan, China, between March 2013 and April 2014 suggested that prenatal depression was significantly associated with birth defects. The adjusted odds ratio for this variable was 1.67 compared with women reporting no prenatal depression; however, no temporal relationship could be established since it was a cross-sectional study [8,9]. This reflects an association between maternal depression and birth defects [8]. The study concluded that reducing the maternal depression can significantly reduce the risk of birth defects [8]. Although previous studies have addressed the impact of prenatal health conditions and health behaviors on birth defects, they did not assess the interactive effect of these variables on birth defects. This study aims to address the gaps in the literature by understanding both the individual and interactive effects of smoking during pregnancy, diabetes, and prenatal depression on birth defects. The study aims at finding the risk of delivering a child with birth defect in the women with depression, diabetes, and health behaviors such as smoking. The primary objective of this research was to assess both the individual and interactive effects of prenatal depression, diabetes, and smoking in pregnant women on infant birth defects. The study hypothesized that birth defects are associated with two-way or three-way interactions of prenatal depression, smoking, and diabetes during pregnancy. ## 2. Materials and Methods The research proposal was approved by Institutional Review Board at U.T. Health San Antonio on 2 March 2021. The IRB number is HSC20210029N. This secondary research planned to analyze the data collected through the Pregnancy Risk Assessment Monitoring System (PRAMS) survey datasets. PRAMS is a joint research project between the state, territorial, or local health departments and the Centers for Disease Control and Prevention, Division of Reproductive Health. The PRAMS survey dataset is a multistate analytic dataset created by the stratified sampling technique [10]. A sample of women across all PRAMS sites in the United States who had a recent live birth was collected from the state’s birth certificate file for the PRAMS survey [11]. The dataset contains demographic and clinical information collected through the state’s vital records system, birth certificate, and other variables such as operational, weighting, questionnaire, and analytic variables. Topics addressed in the PRAMS survey questionnaire included prenatal care, obstetric history, maternal habits, physical abuse, contraception, economic status, maternal stress, and early infant development. Each year, the data are collected through surveys and are available publicly after 14 months for a specific year. This study used the PRAMS data collected for the year 2018. The birth defect information is retrieved by the PRAMS through the birth certificate record and linked with the survey responder. The data received from PRAMS include information about birth defects which is classified as the binary variable of Yes or No. This birth defect binary variable includes all the birth defect-related anomalies [11]. The Pregnancy Risk Assessment Monitoring System (PRAMS) combined two modes of data collection, which were a survey conducted by mailed questionnaire with multiple follow-ups and a telephone survey [8]. Overall, 89,839 US women who had a recent live birth responded to the PRAMS mail questionnaire or participated in the PRAMS phone survey [12]. These 89,839 women were included as respondents in the present research [11]. Non-respondents to the questionnaires were excluded from the study reported in this paper. California, Idaho, and Ohio did not participate in the CDC-PRAMS 2018 survey. Hence, the data for these states were not available. The data obtained from CDC-PRAMS for 2018 were used to create a new data subset for analysis following initial data cleaning and merging. The independent or exposure variables included prenatal conditions and health behaviors such as depression, smoking, and diabetes. The birth defect variable, dependent or outcome variable, was dichotomous and classified as “Yes” for the presence of a birth defect and “No” for the absence of a birth defect. The “diabetes during pregnancy variable” classification is different. The PRAMS dataset combined all the types of diabetes together including Type 1, Type 2, and gestational diabetes. The diabetes during pregnancy variable in this dataset is binary showing “Yes” and “No”. The pregnant mother who responded yes reflects diabetes which includes Type 1, Type 2, and gestational diabetes. The data were analyzed using SPSS, Version 26 (SPSS, 2020). Univariate analyses were used to explore the frequencies for the dependent, independent, and demographic variables. Chi-square tests were conducted to test the associations between the birth defect variable with independent variables such as smoking, depression, and diabetes. Subsequently, the logistic regression model was used for diabetes during pregnancy and testing the interactive effects among two or more covariates. The effect modification was determined in the logistic regression model. A multiplicative model was the model of choice to determine the interactive effect of smoking, depression, and diabetes variables, and to assess various risk factors of birth defects, including depression, smoking during pregnancy. ## 3. Results The average survey response rate of the PRAMS survey for all states was $56.81\%$. The total sample of respondents is 89,839. This sample size is all the respondents of the study survey. After applying the complex sampling weight to the survey data, the total sample size is 4,536,867. The response rate varied from as high as $80.4\%$ for Puerto Rico to as low as $39.4\%$ for Nevada (Figure 1). After applying complex sampling, out of 4,536,867 live births in 2018, birth defects were reflected in $0.3\%$ of the total live births (Table 1). The initial data suggest that the study population varied by age, race, body mass index, and other health indicators. Women who were 25 to 34 years of age contributed to about $58.30\%$ of infants born with birth defects, with most pregnant women being White ($67\%$) and having an income of USD 57,000 to 85,000 ($38.6\%$). The data indicate that $7.2\%$ of pregnant women smoked during pregnancy, $14.2\%$ were diagnosed with depression, and $9.6\%$ were diagnosed with diabetes. The bivariate analysis revealed statistically significant Chi-square values for demographic variables, including age (p-value < 0.001), race (p-value < 0.001), body mass index (p-value < 0.001), maternal smoking habits during pregnancy (p-value < 0.001), depression during pregnancy (p-value < 0.006), diabetes during pregnancy (p-value < 0.023), abuse (p-value < 0.001), folic acid intake (p-value < 0.001), vitamin intake (p-value < 0.001), and hypertension (p-value < 0.001) (Table 1). The multivariate binary logistic regression model for the PRAMS data indicates that age, race, depression during pregnancy, maternal smoking, abuse during pregnancy, hypertension, and smoking e-cigarettes are significantly associated with birth defects (Table 2). The study result indicated that the birth defect did not vary much according to the income category when other variables are constant, and the change is the odds ratio is small to determine any association. ( Table 2). After adjusting the model for covariates, Asian women were at a higher risk of birth defects compared to White women (p-value <0.001, OR = 1.17). The women in the age group of 25–29 years show lower odds of delivering a child with birth defect compared to maternal age groups of 18–19, 20–24, and 40 years and above (OR = 1.67, p-value < 0.001; OR = 1.24, p-value < 0.001; and OR = 2.20; p-value < 0.001, respectively). The odds of delivering an infant with a birth defect in mothers who smoke during pregnancy are approximately two times the odds for mothers who do not smoke during pregnancy (OR = 2.29, p-value < 0.001). Depression during pregnancy was significantly associated with infants born with birth defects with odds of 1.31 compared to women with no depression during the prenatal period (OR = 1.31, p-value < 0.001). Diabetes during pregnancy was negatively associated with birth defects compared to non-diabetic women when the model was controlled for covariates. ( OR = 0.68; p-value < 0.001 and OR = 0.75; p-value < 0.001, respectively). The interaction of smoking, diabetes, and depression during pregnancy was insignificant in determining birth defects in children (p-value = 0.966). The interaction of smoking and depression resulted in higher odds of delivering the child with a birth defect compared to mothers who did not report smoking or depression when a multivariable model was controlled for covariates (OR = 3.17; p-value < 0.001) (Figure 2: Random Forests plot for the odds ratio and Figure 3). The interaction of depression and diabetes in pregnant women resulted in odds of 3.13 for delivering a baby with a birth defect compared to women with no depression and diabetes in the controlled multivariable model (OR = 3.13; p-value < 0.001). The interaction of smoking and diabetes was negatively associated with birth defects when other variables were constant (OR = 0.21; p-value < 0.001) (Figure 2 and Figure 3). ## 4. Discussion This research to analyze both individual and interactive effects of smoking, diabetes, and depression during pregnancy on birth defects using recent data from all PRAMS active sites in the United States for 2018 [11]. The complex sampling methods used for analysis provided a representative sample for all pregnant women in the United States in 2018 [11]. The interaction of all three variables, smoking, diabetes, and depression, during pregnancy, was insignificant (p-value = 0.966) in predicting birth defects in children. The findings are inconsistent with the study hypothesis that these variables show an interactive effect in determining birth defects, thus rejecting this hypothesis. Insignificant results could be due to different reasons, such as study design and selection bias. The sample of women who answered yes to smoking, diabetes, and depression during pregnancy was very small to identify the effect of exposure in the population (Table 1 and Table 2). There may be response bias for this question as pregnant women most likely misreported smoking behavior and depression during pregnancy. The strength of this study was its large sample size and reasonable survey response rate. This study was based on recent data collected for CDC-PRAMS, which provided the latest results for variables of interest. The average survey response rate for CDC-PRAMS was $56.81\%$ [1] (Figure 1). The large sample size and adequate response rate supports the external validity of this study. The analysis weights used in the study were calculated from sampling, non-response, and non-coverage weights, which represented other women similar to respondents in the sample [1]. The study results need to be tested with other equivalent populations such as Europe or Asia to test the study’s external validity further. The sample used for this study effectively analyzed the strata with fewer participants, reflecting good internal validity. The stratified systematic sampling technique and weighting reduced sampling and selection bias, respectively which improved the study’s internal validity. Although the study design was cross-sectional, minimizing the selection bias and sampling techniques enhanced the study’s internal validity. This study provided more evidence supporting the interaction of depression and diabetes as well as smoking and depression on birth defects compared to the other variables. The interaction presented in the study might be due to the confounding effect of the depression variable, and this variable should be adjusted to analyze the interaction of smoking and diabetes with depression during pregnancy. Previous studies have depicted the effect of the single variable of interest, i.e., smoking, diabetes, and depression during pregnancy alone, on the outcome variable [4,13,14,15,16]. This study of the interaction was unique as it analyzed nationwide data to understand the interactive effect of smoking, diabetes, and depression during pregnancy on a rare event such as a birth defect. The results of this study indicated that depression in pregnant women is related to birth defects in infants, which is consistent with previous studies suggesting that depression during pregnancy may be due to domestic violence and abuse. Yu and colleagues reported a significant impact of domestic violence, i.e., abuse (OR = 1.67) and depression (OR = 1.72) in pregnant mothers, on delivering children with birth defects [8]. The result of our study confirms the association of maternal depression with the birth defect and is consistent with the prior studies. Previous studies did not analyze the interaction of smoking and depression, but the present study provided significant evidence of the interactive effects of smoking and depression during pregnancy on children with birth defects (OR = 3.17; p-value < 0.001). This study used a cross-sectional study design and larger sample, which provided the necessary number of subjects to analyze the effect of smoking and depression on birth defects. Another prospective cohort study proposed that diabetes, including gestational diabetes and its interaction with obesity, was significantly related to birth defects and increased birth defects by $65\%$ [9]. Our study used classification criteria for diabetes similar to those used by Moore et al. ( 2000b), but reached contradicting results [3]. These contradicting results might be due to lower cases of pregnant women diagnosed with Type 1 and Type 2 diabetes. Gestational diabetes cases might have contributed more to the sample of diabetes, which resulted in contradicting results as gestational diabetes does not have a stronger association with birth defects [9]. This study used the already collected survey data by CDC-PRAMS, so it was not possible to separate the diabetes cases in gestational or non-gestational diabetes. For future studies, this variable should be reclassified to understand the impact of different types of diabetes on birth defects. The study shows that income distribution is not a strong factor in determining the birth defect. The income status predicts health care utilization in rural areas. The recent research completed by Shelke et al. suggests that preventive treatment utilization is improved in rural areas and more in the income category of USD 25,000 to 45,000 compared to other income groups [17]. The income-related differences did not show a strong odds ratio in the current study which depicts that healthcare access is improving and pregnant women in all age groups are getting access to healthcare. This study proposed a new direction of analyzing different variables and interactions to evaluate the effect on the birth defects. The study confirmed the impact of depression in pregnant women on birth defects. Further research can assess the effects of depression and conditions leading to depression during pregnancy on delivering a child with birth defects. Positive mental health and reducing abuse that leads to depression can help reduce birth defects in most US populations. A limitation of this study is the use of the cross-sectional study design, which restricted the establishment of temporality between the independent variables of smoking, diabetes, and depression during pregnancy on the birth defect. The data were self-reported, which might lead to information bias, which was reflected in a smaller sample size of subjects reporting health behaviors such as smoking. Another limitation included no participation from a few states in the CDC-PRAMS 2018 survey (Figure 1). The income variable was classified using more than one classification system that imposed overlapping categories and challenges in reclassifying this variable in rational categories. The few subcategories of race variables such as Chinese, Japanese, Filipino, Hawaiian, American Indian, and Alaskan Native showed minimal participation, resulting in a higher standard error in regression analysis. This variable was then reclassified into “Other Asian” and “Other American Including Tribes”. The diabetes variable should have been classified as Type 1, Type 2, and gestational diabetes to understand the impact on birth defects. This is one of the limitations of this paper, and we did not succeed in determining the impact of the different types of diabetes on the birth defect. The CDC-PRAMS data did not classify birth defects into different categories. Individual PRAMS sites collected the birth defect variables, but data collection from birth records varies from state to state. All PRAMS data collection sites were contacted to retrieve this information to gather data on types of the birth defect but did not receive information on different types of birth defects. States restrict the sharing of birth defect information because it is an extremely rare anomaly with very few reported cases annually and may violate PHI (Protected Health information) or HIPAA (Health Insurance Portability and Accountability Act) possibility due to linkage of birth defect data individually with birth records. If given a chance to repeat this study, more emphasis should be placed on understanding the individual and interactive impact of different types of birth defects. ## 5. Conclusions This study provided strong evidence that depression during pregnancy is associated with birth defects and variables leading to depression, including abuse or other mental health issues that can be related to childbirth defects [3,9]. 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--- title: Hypoglycemic Potential of Carica papaya in Liver Is Mediated through IRS-2/PI3K/SREBP-1c/GLUT2 Signaling in High-Fat-Diet-Induced Type-2 Diabetic Male Rats authors: - Jeane Rebecca Roy - Coimbatore Sadagopan Janaki - Selvaraj Jayaraman - Vishnu Priya Veeraraghavan - Vijayalakshmi Periyasamy - Thotakura Balaji - Madhavan Vijayamalathi - Ponnusamy Bhuvaneswari - Panneerselvam Swetha journal: Toxics year: 2023 pmcid: PMC10054599 doi: 10.3390/toxics11030240 license: CC BY 4.0 --- # Hypoglycemic Potential of Carica papaya in Liver Is Mediated through IRS-2/PI3K/SREBP-1c/GLUT2 Signaling in High-Fat-Diet-Induced Type-2 Diabetic Male Rats ## Abstract Regardless of socioeconomic or demographic background, the prevalence of type 2 diabetes mellitus, which affects more than half a billion people worldwide, has been steadily increasing over time. The health, emotional, sociological, and economic well-being of people would suffer if this number is not successfully handled. The liver is one of the key organs accountable for sustaining metabolic balance. Elevated levels of reactive oxygen species inhibit the recruitment and activation of IRS-1, IRS-2, and PI3K-Akt downstream signaling cascade. These signaling mechanisms reduce hepatic glucose absorption and glycogenesis while increasing hepatic glucose output and glycogenolysis. In our work, an analysis of the molecular mechanism of *Carica papaya* in mitigating hepatic insulin resistance in vivo and in silico was carried out. The gluconeogenic enzymes, glycolytic enzymes, hepatic glycogen tissue concentration, oxidative stress markers, enzymatic antioxidants, protein expression of IRS-2, PI3K, SREBP-1C, and GLUT-2 were evaluated in the liver tissues of high-fat-diet streptozotocin-induced type 2 diabetic rats using q-RT-PCR as well as immunohistochemistry and histopathology. Upon treatment, C. papaya restored the protein and gene expression in the liver. In the docking analysis, quercetin, kaempferol, caffeic acid, and p-coumaric acid present in the extract were found to have high binding affinities against IRS-2, PI3K, SREBP-1c, and GLUT-2, which may have contributed much to the antidiabetic property of C. papaya. Thus, C. papaya was capable of restoring the altered levels in the hepatic tissues of T2DM rats, reversing hepatic insulin resistance. ## 1. Introduction The chronic metabolic condition, diabetes mellitus, is a major threat to society’s health and quality of life. Type 2 diabetes mellitus (T2DM), which affects more than half a billion people today, has been rapidly rising year after year, irrespective of socioeconomic or demographic status. If this number is not effectively managed, it will increase and have detrimental repercussions on people’s health, emotional, sociological, and financial status [1,2]. The liver is one of the primary organs in charge of maintaining metabolic homeostasis. Glucose homeostasis is maintained by coordinating the production of glucose in the liver through the pathways of glycogenolysis and gluconeogenesis in times of fasting, with the disposal of glucose into skeletal muscles through glycogen synthesis and glucose metabolism, and to a much lesser extent adipose tissue during feeding [3]. The functional duality of the liver in glucose production (glycogenolysis) and glucose storage (glycogenesis) helps in maintaining a fasting and fed state. This dynamic organ plays critical roles in many physiological processes, including the regulation of systemic glucose and lipid metabolism. Dysfunctional hepatic lipid metabolism is a cause of nonalcoholic fatty liver disease (NAFLD), the most common chronic liver disorder worldwide, and is closely associated with dyslipidemia, insulin resistance, and T2DM [4,5]. Hepatic insulin resistance occurs by means of excessive postprandial hyperglycemia due to inadequate inhibition of hepatic gluconeogenesis, decreased glycogen synthesis, and increased lipid accumulation [6,7,8]. Adipose tissue serves as the body’s energy reserve in times of nutritional excess by vigorously absorbing excessive blood glucose to store additional energy such as triglycerides. Moreover, insulin is essential for controlling the activity of lipolysis in adipose tissue, which is dysregulated in insulin resistance and results in the release of significantly elevated amounts of FFAs, pro-inflammatory cytokines (IL-1, IL-6, and TNF-), and glycerol into the bloodstream [8,9]. Kupffer cells, the localized macrophages of the liver, are involved in the production of cytokines and chemokines. They draw in new macrophages or other immune cells in response to foreign and local pro-inflammatory molecular triggers such as excess FFA and proinflammatory cytokines. Augmented levels of reactive oxygen species (ROS) reduce insulin receptor substrate -1 (IRS-1) and insulin receptor substrate -2 (IRS-2) recruitment and also the subsequent activation of the PI3K-AKT cascade downstream. Although they reduce hepatic glucose intake and glycogenesis, these signaling mechanisms also enhance hepatic glucose output, glycogenolysis, and triglyceride (TG) synthesis [10,11]. The pro-inflammatory cytokines produce acute-phase proteins in the liver, and may cause insulin resistance and apoptosis of pancreatic β cells [12,13]. Kupffer cells go from being anti-inflammatory to be pro-inflammatory, and it is assumed that this interaction with hepatocytes leads to insulin resistance [14]. This can also pave the way to the development of hepatic inflammation during non-alcoholic steatohepatitis (NASH) [15]. NAFLD is linked to more severe hyperinsulinemia, dyslipidemia, and insulin resistance in hepatic and adipose tissue in obese T2DM individuals than in those without NAFLD [16]. Modern medicine has grown in relation to efforts towards the development of antidiabetic medicine such as glycoside inhibitors as a way to reduce the absorption of carbohydrates so as to lower postprandial glucose and insulin levels [17,18]. In order to surpass the adverse effects of conventional diabetic treatments, seeking natural remedies is a definitive target. Our research focuses on finding therapeutic and preventive approaches that could slow the processes that lead to T2DM and enhance the treatment of issues related to diabetes. Thus, we intended to identify a natural plant-based product as a therapeutic approach to the effective management of diabetes mellitus. Several pieces of scientific literature have recorded the antidiabetic, immunomodulatory, and hepatoprotective outcomes of *Carica papaya* (C. papaya) [19,20,21,22]. In our previous work, we displayed the molecular action of the antihyperglycemic property of C. papaya in the skeletal muscle of T2DM animal models that reinstated glucose homeostasis via in vivo and in silico analysis. Our current study concentrates on the molecular mechanism of C. papaya in mitigating insulin resistance in the liver. ## 2.1. Chemicals Eurofins Genomics India Pvt Ltd., Bangalore, India, and Sisco Research Laboratories, Mumbai, India, as well as other suppliers, provided all the chemicals, primers, reagents, and ELISA kits used in this work. The other suppliers were MP Biomedicals (Santa Ana, CA, USA); Sigma Aldrich (St.Louis, MO, USA); Spin React, Spain; Ray Biotech (Peachtree Corners, GA, USA); and Abbkine Scientific Co, Ltd. (Wuhan, China). ## 2.2. Collection of C. papaya Leaves The leaves of C. papaya were gathered in Kerala and were desiccated in the shade, then pulverized. The National Institute of Siddha, Chennai, validated the content: -Certificate No: NISMB4392020. ## 2.3. Animals At the Central Animal House of Saveetha Dental College and Hospital in Chennai, Tamil Nadu, male Wistar albino rats of 8–10 weeks old, weighing 150–180 g, were housed under standard environmental conditions of ambient temperature (21–2 °C), humidity (65–$5\%$), and a stable 12-hour light–12-hour dark cycle. They were given regular rat pellets and unfettered use of water. ( IAEC No: BRULAC/SDCH/SIMATS/IAEC/08-$\frac{2021}{071}$ dated 21 August 2021). ## 2.4. T2DM Induction The rats were fed with high-fat diet (HFD) for 4 weeks, which included $66\%$ conventional rat feed, $30\%$ coconut oil, $3\%$ cholesterol, and $1\%$ cholic acid. Streptozotocin (STZ) (35 mg/kg) (Sigma Aldrich, St. Louis, MO, USA) was injected intraperitoneally to the rodents after 28 days of high-fat diet (HFD) feeding [23]. Two days after STZ administration, those animals with a fasting blood glucose of >120 mg/dl were taken into consideration for the study. Therefore, T2DM rats were allowed post induction. ## 2.5. Experimental Design Random selection was used to choose five groups of eight rats each. In this study, we wanted to compare the efficacy of C. papaya with the commercially available oral hypoglycemic agent, metformin (50 mg/kg.b.wt). On the last day of the experiment, the animals were sedated with sodium thiopentone (40 mg/kg body weight) and blood was drawn through cardiac puncture. The blood was removed from the organs by injecting 20 mL of isotonic sodium chloride solution via the left ventricle. The liver from control and treated animals were immediately dissected and stored at −80 °C for further analysis. ## 2.6. Liver and Renal Function Markers Urea and creatinine (kidney function markers), as well as liver function markers such as aspartate transaminase (AST) and alanine transaminase (ALT) were assessed using commercial kits. ## 2.7.1. Assay for Glucose-6-Phosphatase To assess glucose-6-phosphatase (G6P), Koide and Oda’s working protocol was used [24]. An hour was spent incubating 0.1 mL of the homogenized tissue with 0.3 mL of citrate buffer and 0.5 mL of substrate, and at 37 °C. 10 percent TCA was added to halt the reaction, and then Fiske and Subbarow’s method was used to calculate inorganic phosphate [25]. At 640 nm, the absorbance measurement was made. ## 2.7.2. Assay for Fructose-1,6 Bisphosphatase The Gancedo & Gancedo protocol was applied [26]. About 2.3 mL of a mixture with Tris-HCl buffer, potassium chloride, tissue homogenate, magnesium chloride, EDTA, and substrate was incubated for 15 min at 37 °C. The reaction was stopped using 10 percent TCA, and Fiske and Subbarow’s approach was used to estimate the endpoint [25]. ## 2.8. Determination of Glycolytic Enzymes The method described by Brandstrup et al. [ 27] was used to measure the activity of hexokinase (HK). HK converted ATP and D-glucose into glucose 6-phosphate and ADP, respectively. The residual glucose reacts with the o-toluidine reagent and emits a green color that can be observed at 640 nm spectomorphometrically. In terms of the mol of glucose phosphorylated per hour and mg of protein, the enzyme’s activity was calculated. Pyruvate kinase (PK) tissue activity was assessed by means of Valentine and Tanaka’s method [28]. *Pyruvate* generation from phosphoenolpyruvate was employed as a starting point. In order to determine how much pyruvate was released, dinitrophenyl hydrazine was supplemented, and the color formed was measured at 520 nm. The mol of pyruvate formed/min/mg protein was used to represent the values. ## 2.9. Glycogen Level The Hassid and Abraham method [29] was used to estimate the amount of glycogen in the livers for all five study groups. ## 2.10. Oxidative Stress Markers Rat liver tissues were examined using an ELISA kit for the detection of lipid hydrogen peroxide (H2O2) and peroxidation (LPO). ## 2.11. Enzymatic Antioxidants Investigation of the expression of enzymatic antioxidants markers such as reduced glutathione (GSH), catalase (CAT), glutathione peroxidase (GPx), and superoxide dismutase (SOD) in the liver tissue of the rats were assessed with ELISA kit. ## 2.12. Total RNA, cDNA Synthesis, and Real-Time PCR Total RNA was extracted from the liver of the rats in each of the five groups using the TRIR kit. The reverse transcriptase kit was provided by Eurogentec (Seraing, Belgium). The cDNA was created using 2 µg of total RNA. The list of primer sequences is mentioned in Table 1 as well as the house-keeping gene. *The* genes were amplified using a real-time PCR system (Stratagene MX 3000P, Poway, CA, USA) under the following reaction conditions: 40 cycles of 95 °C for 30 s, 59–60 °C for 30 s, and 72 °C for 30 s. Using the melt and amplification curves as a guide, relative quantification was created. ## 2.13. Histopathology Hematoxylin and eosin were used to stain the liver tissue’s histopathology after it had been cut into sections and fixed in $10\%$ neutral buffered formalin [34]. Sections were taken by means of microtome, and photographs at a 100-fold magnification were captured. ## 2.14. Immunohistochemical Analysis Deparaffinized liver tissues from the experimental rats measuring 4 µm were then rehydrated using xylene and ethanol, sequentially, at steadily decreasing concentrations. The tissues were combined with sodium citrate buffer (1M, pH 6.0–6.2) and warmed for 5 min in three cycles. Thereafter, the slides were treated for 5 min with 1M PBS. Prior to processing the sections, the primary antibodies Akt and GLUT-2 were diluted 1:100 and peroxidase activity was performed. ## 2.15. Statistical Analysis By means of Graph pad prism version 5 (computer-based software), the data were examined using one-way analysis of variance (ANOVA) and Duncan’s multiple range test to determine the importance of individual variance within the control and treated groups. The data were represented as mean ± S.E.M animals ($$n = 8$$) in a group and the significance was calculated at the levels of $p \leq 0.05.$ ## 2.16.1. Ligand Molecule Preparation The literature on the bioactive substances found in C. papaya was compiled, and the PubChem database was used to download their chemical structures. Table 2 shows the list of ligands used in the study. In Pyrx, open Babel’s conjugate gradient technique was used to add hydrogens to the molecules while minimizing energy using the UFF force field. For pyrx 0.8 input, all structures were saved as pdb files. The Pdbqt file format was then used to save all of the ligand structures for later input into the AutoDock version. Later, the Auto Dock Pdbqt format was applied to all lead molecules. ## 2.16.2. Protein Macromolecule Preparation From the protein data bank, the three-dimensional crystal structures of IRS-2 (PDB ID: 3FQW) and P13K (PDB ID: 5XGJ) were downloaded. We eliminated all extra docking chains after downloading. The next step involved was the elimination of ligands and crystallized water molecules. Later, using a program developed at the Molecular Graphics Laboratory called the Mgl Tool (also known as Auto Dock tools), polar hydrogens and Kollmann charges were supplemented (MGL). They were added to the protein as a last step, along with any missing amino acids, and the protein as a whole was reduced using the Swiss PDB Viewer Software. The protein was subsequently set aside in the pdb format and was prepared for docking using Autodock Vina, with an estimation made using a soft virtual screening library by the name of Pyrx. ## 2.16.3. Ligand–Protein Docking Molecular docking experiments were conducted in order to comprehend the molecular interaction between the chosen drugs and the target proteins utilizing a computer technique. The binding mechanisms of the naturally occurring inhibitors from C. papaya were ascertained using the AutoDock (PyRx) suite of tools. The PyRx was used to assess the binding sites and the docking run of the target protein with the ligand. By selecting the Lamarckian GA docking technique and turning on the “Run AutoGrid” and “Run AutoDock” options in the control panel, an exhaustive search was carried out. This method involves the ligand randomly moving around the stationary protein. The grid point was given the energy of this one atom’s interaction with the protein. An equation based on free energy was used to determine interaction energies and include terms for dispersion/repulsion energy and directional hydrogen bonding. ## 3.1. Efficacy of C. papaya on Liver and Renal Function Markers The liver (ALT and AST) and kidney function markers (urea and creatinine) were significantly high ($p \leq 0.05$) in the T2DM Group 2 when matched with control rats and this is depicted in Figure 1 and Figure 2. The medicament with C. papaya reduced these high marker levels. The levels were brought down close to the control group with the administration of metformin. The control + C. papaya group showed nil changes. ## 3.2. Impact of C. papaya on Gluconeogenic Enzymes and Glycolytic Enzymes Figure 3a,b demonstrates that in diabetic Group 2 rats, there is high fructose-1,6 bisphosphatase (FBPase) and glucose-6-phosphatase (G6P) activity. Treatment with C. papaya showed a reduction of these enzymes which was almost similar to the metformin group. Control + C. papaya did not exhibit any appreciable differences. The levels of hepatic hexokinase (HK) and pyruvate kinase (PK) in the rats of all five groups are showcased in Figure 4a,b. The levels were lowered in diabetic Group 2 when compared to Group 1. Furthermore, when C. papaya was administered orally, hepatic hexokinase and pyruvate kinase significantly increased ($p \leq 0.05$), in a similar way to the metformin medicament. ## 3.3. Outcome of C. papaya on Hepatic Glycogen Level Figure 5 shows the levels of glycogen. Rats with T2DM in Group 2 have significantly lower ($p \leq 0.05$) levels of glycogen in their livers than rats without the disease in Group 1. This was largely restored by C. papaya therapy in Group 3, which is close to Group 4 with metformin therapy. Group 5 showed no alterations. ## 3.4. Efficacy of C. papaya on Oxidative Stress Markers Figure 6a,b illustrates the amounts of LPO and H2O2 in control and test rats. The levels of LPO and H2O2 in the liver of the T2DM group remained significantly greater ($p \leq 0.05$) when analyzed with Group 1. Indicators of stress effectively decreased values in the C. papaya-treated hepatic tissue when compared to Group 2. The levels were noticeably reduced by the drug metformin as well. In Group 5 rats, there were no changes in the levels of these markers of oxidative stress. ## 3.5. Impact of C. papaya on Enzymatic Antioxidants Figure 7a–d indicates the amounts of catalase, glutathione peroxidase, and superoxide dismutase in control and test rats. The enzymatic levels of GPx, CAT, GSH, and SOD were all significantly reduced ($p \leq 0.05$) in the liver of T2DM Group 2 when compared to Group 1. When compared to Group 2, the antioxidant enzyme values in the liver with the C. papaya treatment group were considerably improved. Additionally, their levels significantly improved when using the drug metformin. In Group 5 rats, these enzymatic antioxidant levels were constant. ## 3.6. Impact of C. papaya on mRNA Expression of IRS-2, PI3K, SREBP-1c and GLUT-2 in Liver Figure 8a–d shows the impact of C. papaya on the mRNA expression of IRS-2, SREBP-1c, PI3K, and GLUT-2 in the liver of each of the five test groups. The mRNA gene levels of IRS-2 and PI3K remained significantly lowered ($p \leq 0.05$) in T2DM rats when compared with Group 1 rats. The administration of C. papaya enhanced these levels in the hepatic tissues in a similar way to metformin administration. Meanwhile, in diabetic rats, the levels of the mRNA genes for GLUT2 and SREBP-1c were dramatically elevated. Similar to the standard medication metformin, C. papaya therapy in diabetic rats decreased the levels of mRNA for GLUT2 and SREBP-1c in the liver. C. papaya-treated control rats did not display any discernible modifications. ## 3.7. Role of C. papaya on the Liver Tissue’s Histopathological Changes To determine histological alterations in the diabetic condition and its restoration upon treatment with C. papaya, H&E staining was done (Figure 9a–e). The histology of the liver in the normal group revealed a single layer of hepatocytes encircling the central vein and a normal, distinct, and typical liver lobular architecture. However, the liver of Group 2 T2DM rats exhibited significantly extensive lipid vacuoles and a high number of fat depositions. The histological abnormalities and the micro-vesicular fatty alterations were seen to be significantly reduced by the C. papaya intervention in Group 3 in a similar way to that of the Group 4 metformin medicament, indicating that C. papaya could almost entirely restore the liver tissues to normalcy. No considerable changes were observed in group 5. ## 3.8. Efficacy of C. papaya on the Immunohistochemistry Alterations in Liver Tissue Figure 10a–e depicts the immunohistochemical changes in Akt in the study group. Akt expression in the liver was lower in Group 2 animals. As seen in Group 3, C. papaya therapy boosted the levels of Akt. The rats in Group 4 with metformin administration also displayed a considerable rise in Akt expression in the hepatic tissue of T2DM. Rats in Group 5 showed no discernible alterations. Figure 11a–e displays that the lessened expression of GLUT-2 in the liver of Group 2 T2DM rats were noticed when collated with Group 1 rats. The administration of C. papaya bettered the expression of GLUT-2 in Group 3 in a similar way to that of metformin therapy. No alterations were viewed in group 5. ## 3.9. Molecular Docking Protein–ligand interaction is a result of molecular docking. The result of the protein–ligand interaction has been summarized in tabular form as the number of H-bonding and amino acid interactions, as well as the binding affinity score. The ligand’s negative binding energies signify a stable connection between the ligand and receptor. The binding energy and interaction of C. papaya compounds with the protein targets were made known in Table 3 and Figure 12, Figure 13, Figure 14 and Figure 15. ## 4. Discussion The prevalence of NAFLD in obese people has increased exponentially, and it is considered the hepatic component of metabolic syndrome [35,36]. NAFLD usually appears before T2DM, and NAFLD individuals almost invariably have hepatic insulin resistance, which may play a key role in the pathophysiology from NAFLD to T2DM [37]. The liver serves as a significant site for the uptake and storage of glucose and can be responsible for up to one-third of oral glucose load disposal [38]. Increased hepatic glucose production is intertwined with fasting hyperglycemia in T2DM patients, suggesting that insulin resistance in the liver may play a role in hyperglycemia progression later on [39]. In the case of hepatic insulin signaling, insulin binds to and activates the insulin receptor tyrosine kinase (IRTK), which then facilitates the tyrosine kinase phosphorylation of insulin receptor substrates (IRS), most significantly IRS2 in the liver [40,41]. Proteins with Src homology 2 domains, such as phosphatidylinositol-3-OH kinase (PI3K), can bind to IRS2 by being phosphorylated [42,43]. Phosphatidylinositol-3,4,5-trisphosphate (PIP3) is recruited by PI3K binding to IRS2 in order to recruit Akt [43,44]. Akt activation serves four primary functions in the liver: [1] Increasing glycogen synthase (GS) activity to stimulate the synthesis of glycogen by inhibiting GS kinase (GSK); [2] Reduction of the expression of important gluconeogenic genes in part through forkhead box O1 (FoxO1) inactivation; [3] Sterol regulatory element-binding protein 1 (SREBP1) is controlled to stimulate endogenous fatty acid synthesis; and [4] Glucose transporter 2 (GLUT2) is directed to transport glucose into cells for aerobic metabolism or anaerobic breakdown [45,46,47,48,49]. Obesity causes ectopic fat accumulation in the liver and under the skin, which marks insulin resistance because adipocytes’ capacity to store and retain triglycerides is reduced [50]. Insulin-mediated inhibition of lipolysis in adipose tissue is weakened by insulin resistance, which leads to a significantly increased release of FFAs and glycerol into the bloodstream. Patients with NAFLD have higher amounts of circulating FFAs, which are the main source of escalating oxidative stress and inflammatory signals leading to systemic inflammation [50]. In hyperglycemic conditions, hepatic glucose production and glycogen synthesis is diminished while an increase in hepatic lipogenesis takes place [51,52]. Thus, hyperinsulinemia, hyperglycemia, and hypertriglyceridemia are common in T2DM patients [53]. Recent research has made significant efforts to completely understand the nature that bestows many medicinal benefits, and as a result, the quest for innovative approaches is conducted to effectively treat and defeat the growing epidemic of obesity and T2DM. As one of them, C. papaya is on the list of medicinal plants for the treatment of diabetes. C. papaya possess a rich source of phytochemicals with abundant anti-inflammatory and antioxidant properties, as well as favorable effects on glucoregulatory function [54]. In our earlier research, we found that C. papaya can restore glycemic control by exhibiting insulinemic action in T2DM skeletal muscle by increasing the levels of IR, IRS-1, Akt, and GLUT-4. The potential influence of C. papaya on insulin-signaling molecules in skeletal muscle was shown in a HFD-STZ-induced T2DM model [55,56]. In light of this, we centered on oxidative stress, gluconeogenic-glycolytic enzymes, and the expression of genes in the hepatic tissues of diabetic rats, and assessed the effect of C. papaya on hepatic insulin resistance using in vivo and in silico models. Individuals with NAFLD and NASH generally have elevated circulating concentrations of markers of liver injury, such as AST, and ALT. Both AST and ALT serve as endoenzymes in hepatocytes for both amino acid production and catabolism and the alterations in the expression of ALT and AST in the serum serve as a biomarker for liver function [57]. In this work, the levels of liver function markers were increased in T2DM rats. The treatment with C. papaya leaf extract brought down the levels of ALT and AST in a comparable way to the result of metformin-treated rats, suggesting the hepatoprotective role of C. papaya. A parallel work by Abdel-Halim et al. [ 58] showed that the deleterious effect of carbon tetra chloride (CCl4) was eliminated upon the administration of C. papaya, which restored liver function markers. Albrahim and her co-worker displayed a considerable decline in ALT and AST levels in aged rats with the treatment of blueberry extract, thus proving its ability to enhance liver function [59]. NAFLD and type 2 diabetes may progress due to interactions between liver enzymes and insulin resistance. To establish the extent of renal impairment brought on by T2DM, serum urea and creatinine levels were also examined. According to earlier research, T2DM causes the kidney to expand due to hyperplasia and disrupts glomerular filtration [60]. Parallel to the study of Lathifi et al. [ 61], the renal function markers in our work were also lessened by enhancing the filtration function of the kidney upon the treatment of C. papaya in insulin resistance. Due to hepatic insulin resistance in T2DM, the functionality of hepatocytes is dysregulated [62]. Thus, the levels of important enzymes involved in glycolysis and gluconeogenesis were quantified to investigate the molecular mechanism underlying the anti-hyperglycemia impact of C. papaya leaves. In the current study, enhanced hepatic glucose production and subsequent hyperglycemia in the HFD-streptozotocin-induced T2DM model were caused by the enhanced activity of FBPase and G6Pase, the major enzymes involved in gluconeogenesis in the liver. Further to this, the medicament of C. papaya downregulated the levels of these gluconeogenic enzymes close to those in the metformin-treated group. Similarly, the administration of Scutellariae radix and Coptidis rhizome reduced the levels of FBPase and G6Pase in a study carried out by Cui et al. [ 62]. Pari et al. [ 63] reported that when diabetic rats were given naringin in a dose-dependent manner, the altered FBPase and G6Pase activity were considerably restored to close to normal levels. Glycolysis typically has an impact on insulin output and various cell metabolisms. Deficiency of the key glycolysis enzymes, HK and PK, can result in decreased glycolysis, as well as decreased glucose absorption and utilization for energy output, which contributes to insulin resistance [64]. In the current work, poor insulin signaling resulted in a decrease in HK and PK in T2DM rats. In comparison to the metformin group, the medicament of C. papaya increased the range of HK and PK in the liver tissues of diabetic rats. According to Sureka et al. [ 65], another similar characteristic of *Sesbania grandiflora* augmented the levels of glycolytic enzymes in T2DM rats when matched with the control group. The total glycosides of *Cistanche tubulosa* were also used by Zhu et al. [ 66] to demonstrate higher levels of glycolytic enzymes in diabetic hepatic tissue. The results of our investigation suggested that the anti-hyperglycemic activities of C. papaya could be related to its phytochemical constituents which maintain glucose homeostasis [67]. Glycogen, which is mostly found in muscles and the liver, is crucial for preserving glucose homeostasis [68]. In a study by Luo et al., the amount of muscle and liver glycogen increased noticeably, showing that sweet potato leaf polyphenols may help diabetic mice produce more glycogen [68]. In a related, encouraging investigation, berry extract from *Aronia melanocarpa* increased the amount of hepatic glycogen in rats with type 2 diabetes [69]. Our treatment with C. papaya in T2DM rodents boosted the levels of hepatic glycogen in a similar way to that of the metformin administered group. The enhanced levels of hepatic tissue glycogen alleviated oxidative-stress-incited FFA and reactive oxygen species (ROS), thus improving the antioxidant defense status. Increased ROS production from T2DM induced dyslipidemia and oxidative stress, which lead to lipid peroxidation and membrane damage [70]. In our investigation, the T2DM group was seen to have raised levels of LPO and H2O2, which increased the generation of ROS. In a related study, *Phyllanthus amarus* extract was shown to reduce oxidative stress biomarkers in HFD-induced T2DM rats [71]. However, C. papaya dramatically reduced LPO and H2O2 levels, owing to its antioxidant properties which come from its phytochemical backbone, which promotes the scavenging of overproduced ROS. Free radicals diminish enzymatic antioxidants such as CAT, SOD, GSH, and GPx in T2DM, thereby contributing to oxidative stress [72]. The treatment of C. papaya markedly boosted enzymatic antioxidant levels, which significantly decreased ROS and prevented lipid peroxidation in diabetic rodents’ liver tissue, and displayed a similar efficacy to the metformin-treated group. These results were pretty closely in accordance with Nain et al. study [73]. Earlier studies have recorded that the deterioration of glucose homeostasis due to IRS-2 and PI3K deficiencies led to insulin resistance in the liver [74,75]. This can result in the dysfunction of IRS-2 and PI3K which can contribute to the pathophysiology of T2DM [74]. In our current work, a decline in the levels of IRS-2 and PI3K was observed in T2DM rats. Zhang et al. [ 76] researched the antidiabetic effects of *Bifidobacterium animalis* 01 and its beneficial improvement on IRS-1 and PI3K gene expression. Liu and his co-workers demonstrated that the derivatives of Mogroside delivered hypoglycemic results on HepG2 cells and lessened insulin resistance in T2DM rats by improving the gene expression related to insulin signaling [77]. In the same way, in our study, the therapy of C. papaya considerably improved the levels of IRS-2 and PI3K, in a way comparable to that of the metformin medicament. It is well known that in T2DM, liver GLUT2 gene transcription is elevated. This transcription factor plays a crucial role in the maintenance of glucose homeostasis [78]. The expression of the GLUT 2 gene is mainly dependent on sterol response element-binding protein (SREBP)-1c. SREBP-1c activates the GLUT2 promoter reporter, whereas a dominant-negative version of SREBP-1c inhibits the activation [79]. In the T2DM state, elevated ranges of SREBP-1c and GLUT-2 are observed. In our study, high levels of SREBP-1c and GLUT-2 were shown in the HFD-streptozotocin-induced T2DM rats. Similar works were reported in the earlier literature that reduced these levels to influence insulin signaling in the liver [80,81]. The medicament of C. papaya in our present research displayed the restoration of these upregulated genes in the insulin-signaling cascade, aiding in the maintenance of glucose homeostasis. Insulin insufficiency and the dysregulation of fatty acid β-oxidation in mitochondria are the two main factors in the fatty degeneration of hepatocytes. This causes the conversion of fatty acids to numerous triglyceride droplets in the hepatocytes [82]. Kupffer cells get activated in inflammatory states such as obesity and T2DM, to release a good deal of inflammatory cytokines and chemokines [83]. As a result, hepatocyte injuries, cellular inflammation, fatty deposits, and vascular congestion were observed in the histopathological liver section of T2DM rats in our work, which was similar to Brancaccio et al. [ 84]. A comparable work was done by Motshakeri et al. [ 85]. The C. papaya treatment gradually reinstated the architecture of hepatocytes and consequently diminished cellular inflammation. These highlight the hepatoprotective potential of C. papaya and its role in hepatic insulin signaling. Hepatic insulin resistance can be alleviated by activating the PI3K/Akt pathway. In order to assess this, immunohistochemistry of Akt in hepatic tissues was done. The T2DM group displayed less expression of Akt in the liver tissues of the experimental rats. A similar study was done by Zhu et al. [ 86], in which the expression of Akt in T2DM-induced rodents was improved by the treatment of Liubao brick tea. In our work, the administration of C. papaya increased the levels of Akt in a comparable way to metformin treatment (Figure 16) The administration of C. papaya lowered the high levels in diabetic rats. A supportive work by Mathur and his team [87] found that *Psidium guajava* Linn. leaf extract reduced the levels of hepatic GLUT2. The excess availability of GLUT2 protein was decreased with the therapy of C. papaya to curb the glucose influx into hepatocytes. Thus, C. papaya improved downstream signaling by reducing gluconeogenic enzymes and oxidative stress markers, thus increasing glycolytic enzymes, hepatic glycogen content, and enzymatic antioxidants [88]. In the in silico analysis, non-covalent intermolecular interactions including hydrogen bonds between molecules, Van der Waal interactions, electrostatic interactions, and hydrophobic interactions all have an impact on binding affinity. The presence of several additional molecules may also affect the binding affinity of a ligand to the active site of a receptor. The outcomes showed that each of the ligands under investigation has a similar orientation and location within the putative binding site of the aforementioned proteins, which acts as a conduit intended for the substrate to reach the active site [89]. The strength of the relationship between the ligand’s affinity for the protein and the binding free energy can help interpret and comprehend the activity of the ligand through a variety of potential pathways. Additionally, the shape of the ligand–receptor complex plays a critical role in the development of pharmacological activity. With regard to binding energy, hydrogen bond interaction, and hydrophobic interaction, quercetin, kaempferol, caffeic acid and p-coumaric acid demonstrated robust binding with every receptor in the current study. The researchers hunting for new drugs with anti-diabetic effects will benefit greatly from this in silico study. The possibility that the abovementioned proteins are intimately involved with C. papaya’s bioactive compounds needs to be confirmed in order to forward research. ## 5. Conclusions The current study clearly demonstrates that C. papaya improves glycemic control in liver of HFD–STZ-induced T2DM rats through the regulation of IRS-2, PI3K, SREBP-1c, and GLUT-2 signaling molecules by facilitating glycolysis and inhibiting gluconeogenesis. This eventually encouraged the synthesis of hepatic glycogen by normalizing oxidative stress and antioxidant enzymes. 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--- title: Delirium Risk Score in Elderly Patients with Cervical Spinal Cord Injury and/or Cervical Fracture authors: - Koji Tamai - Hidetomi Terai - Hiroaki Nakamura - Noriaki Yokogawa - Takeshi Sasagawa - Hiroaki Nakashima - Naoki Segi - Sadayuki Ito - Toru Funayama - Fumihiko Eto - Akihiro Yamaji - Kota Watanabe - Junichi Yamane - Kazuki Takeda - Takeo Furuya - Atsushi Yunde - Hideaki Nakajima - Tomohiro Yamada - Tomohiko Hasegawa - Yoshinori Terashima - Ryosuke Hirota - Hidenori Suzuki - Yasuaki Imajo - Shota Ikegami - Masashi Uehara - Hitoshi Tonomura - Munehiro Sakata - Ko Hashimoto - Yoshito Onoda - Kenichi Kawaguchi - Yohei Haruta - Nobuyuki Suzuki - Kenji Kato - Hiroshi Uei - Hirokatsu Sawada - Kazuo Nakanishi - Kosuke Misaki - Akiyoshi Kuroda - Gen Inoue - Kenichiro Kakutani - Yuji Kakiuchi - Katsuhito Kiyasu - Hiroyuki Tominaga - Hiroto Tokumoto - Yoichi Iizuka - Eiji Takasawa - Koji Akeda - Norihiko Takegami - Haruki Funao - Yasushi Oshima - Takashi Kaito - Daisuke Sakai - Toshitaka Yoshii - Tetsuro Ohba - Bungo Otsuki - Shoji Seki - Masashi Miyazaki - Masayuki Ishihara - Seiji Okada - Shiro Imagama - Satoshi Kato journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054626 doi: 10.3390/jcm12062387 license: CC BY 4.0 --- # Delirium Risk Score in Elderly Patients with Cervical Spinal Cord Injury and/or Cervical Fracture ## Abstract The number of elderly patients with cervical trauma is increasing. Such patients are considered to be at high risk for delirium, which is an acute neuropsychological disorder that reduces the patient’s capacity to interact with their environment due to impairments in cognition. This study aimed to establish a risk score that predicts delirium in elderly patients with cervical SCI and/or cervical fracture regardless of treatment type. This retrospective cohort study included 1512 patients aged ≥65 years with cervical SCI and/or cervical fracture. The risk factors for delirium according to treatment type (surgical or conservative) were calculated using multivariate logistic regression. A delirium risk score was established as the simple arithmetic sum of points assigned to variables that were significant in the multivariate analyses. Based on the statistical results, the delirium risk score was defined using six factors: old age (≥80 years), hypoalbuminemia, cervical fracture, major organ injury, dependence on pre-injury mobility, and comorbid diabetes. The score’s area under the curve for the prediction of delirium was 0.66 ($p \leq 0.001$). Although the current scoring system must be validated with an independent dataset, the system remains beneficial because it can be used after screening examinations upon hospitalization and before deciding the treatment strategy. ## 1. Introduction Delirium is an acute neuropsychological disorder that reduces the capacity of a patient to interact with their environment due to impairments in cognition [1]. Although the symptoms of delirium are normally reversible, potentially negative effects may persist for both the patient and the healthcare system [2]. These effects include delayed discharge and rehabilitation, an increased risk of adverse events and mortality, and failure to comply with care instructions [3,4]. Although there are treatment options for delirium, including non-pharmacological approaches, the effects of treatment are still limited [2]. Hence, the prevention of delirium is still critical. The pace of population aging has been accelerating dramatically worldwide. Expectedly, from 2015 to 2050, the proportion of the world’s population aged over 60 years will increase nearly two-fold (from $12\%$ to $22\%$) [5]. The elderly population experiences high rates of osteoporosis and falls due to declining functional ability [6,7]. Hence, the proportion of individuals aged >60 years with a traumatic spinal cord injury (SCI) has risen from $4.6\%$ in 1970 to $13.2\%$ in 2008 [8]. Moreover, the elderly population is more likely to be diagnosed with a cervical spine injury due to minor trauma, than a thoracic and lumbar spine injury, compared to the younger population [8]. Hence, the number of elderly patients with cervical SCI and/or a cervical fracture has been increasing dramatically [9,10,11]. Old age and life-threatening conditions such as cervical SCI are major risk factors for delirium [12,13]. Consequently, elderly patients with cervical SCI and/or a cervical fracture are considered to be at high risk for delirium. However, due to limitations in healthcare systems, physicians and medical staff cannot always provide intensive preventive measures to all such patients. Therefore, screening tools for delirium in elderly patients with cervical SCI and/or cervical fracture should be established to select patients who are at especially high risk for delirium. Although there are several screening tools for delirium, standard indicators for delirium screening have not been uniformly recognized [14]. Previously proposed screening tools, such as the Abbreviated Mental Test, the 4 A’s Test, the Brief Confusion Assessment Method, reciting the months of the year backward, and the Single Question in Delirium, are reported to be effective predictors of delirium in geriatric inpatients [15]. However, the use of these tools on admission may not be ideal for patients with cervical SCI and/or cervical fracture, as many of them require interviews that might not be immediately feasible for patients with cervical trauma. Additionally, it is important to take preventive measures for delirium immediately upon admission of the patient. Therefore, the current study aimed to create a screening tool that can predict delirium during treatment (regardless of whether surgical or conservative) in elderly patients with cervical SCI and/or cervical fracture. The current screening tool was designed to predict delirium without any data obtained from lengthy interviews with the patient. ## 2.1. Patient Population This study analyzed multi-center registry data retrospectively collected by the Japan Association of Spine Surgeons with Ambition (JASA) [16]. Registrars reviewed the medical records and retrospectively registered cases into the JASA database based on the following inclusion and exclusion criteria:Inclusion criteria: patients aged ≥65 years with traumatic cervical SCI and/or traumatic cervical fracture; patients treated conservatively or surgically between 2010 and 2020 at an institution registered in the JASA and those who were followed for at least three months after the injury;Exclusion criteria: patients with cervical metastasis; and those with any missing data;Registrars did not exclude patients on the basis of specific medications, surgical procedures, surgical instruments, and/or reasons other than the inclusion/exclusion criteria indicated above. In total, 1512 patients from 78 institutions were registered in the JASA database (average age: 75.8 ± 6.9 years; 1007 males and 505 females; 1310 patients were transferred to a hospital within 24 h of injury; 202 patients were hospitalized at an average of 10.0 ± 16.9 days after the injury). All registered patients were included in the current analysis. The patients were divided into two cohorts according to treatment type: the conservative cohort (including patients who underwent conservative therapy for traumatic cervical SCI and/or traumatic cervical fracture) and the surgical cohort (including patients who underwent surgery for the injury, whether expected or unexpected) (Figure 1). ## 2.2. Collected Data All data regarding patient background, delirium status, neurological impairment scale, therapy, and radiography were extracted from our registry database. ## 2.2.1. Patient Background Data Data regarding the age at injury, sex, height, weight, body mass index, pre-injury mobility (independent, able to walk with assistance, or wheelchair/bedridden), blood examinations at the first visit, and comorbidities (dementia, diabetes, and hypertension) were collected. Blood tests included the levels of hemoglobin (Hb; g/dL), total protein (g/dL), and albumin (Alb; g/dL). All assessments were performed immediately after patient transfers and hospital visits. ## 2.2.2. Delirium Data The existence or absence of delirium during the in-hospital stay was collected from medical records retrospectively. Standard tools such as the Diagnostic and Statistical Manual of Mental Disorders, 4th or 5th Edition, and the Confusion Assessment Method were used to diagnose delirium [2]. ## 2.2.3. Radiographic Data Collected radiographic data included the presence of a cervical fracture and cervical ossification of the posterior longitudinal ligament (OPLL), as detected by plain radiography and/or computed tomography (CT). Additionally, data regarding signal changes in the spinal cord on T2-weighted magnetic resonance imaging was collected, and comorbid major organ injuries were evaluated using whole-body CT when necessary. All assessments were performed immediately after patient transfers and hospital visits. Major organ injuries were defined as head, chest, abdominal organ, and pelvic injuries. ## 2.2.4. Neurological Impairment Scale The American Spinal Cord Injury Association (ASIA) Impairment Scale was used as a parameter of neurological impairment [17]. All assessments were performed immediately after patient transfers and hospital visits. ## 2.2.5. Therapeutic Data For the conservative cohort, information was collected regarding the existence of acute steroid use and neck fixation (neck brace or halo-traction). For the surgical cohort, the existence of early surgical intervention within 24 h of injury and surgical type (posterior decompression, posterior fusion ± decompression, anterior fusion ± decompression, or combined fusion ± decompression) were recorded. ## 2.3. Statistical Analysis All analyses were performed using SPSS software (version 23; SPSS, Chicago, IL, USA). A p-value of <0.05 was considered statistically significant. ## 2.3.1. Risk Factors for Delirium The incidence of delirium was compared between the conservative and surgical cohorts using the chi-square test. Data on patient background factors, radiographic images, neurological impairment scale grade, and therapeutic options were compared between patients with and without delirium in each cohort using the Mann–Whitney U test or chi-square test, as appropriate. A residual analysis was performed to confirm the chi-square test results for specific cervical alignment parameters. The results of the residual analysis were described as $p \leq 0.05$ when the variable showed |r| >1.96, in accordance with the Haberman method [18]. For each cohort, significant variables with $p \leq 0.05$ on univariate analysis were included in a multivariate analysis as explanatory variables; the presence of delirium was set as the objective variable. In the multivariate analysis, continuous or non-binary data were translated into binary values before calculation using previously reported thresholds [19,20,21,22]. The adjusted odds ratio (aOR) and $95\%$ confidence interval (CI) of the dependent variables were calculated. ## 2.3.2. Delirium Risk Score A delirium risk score was established as the simple arithmetic sum of points assigned to variables that were significant in the multivariate analyses of the two cohorts. The points assigned to each variable were decided based on the adjusted risk relationship: 1 point for an aOR of 1.0−10 and 2 points for an aOR > 10 [23]. When specific factors were calculated as risk factors of delirium in both cohorts, the factor was treated as a single factor in the final scoring system. The predictive value of the delirium risk score was evaluated by a receiver operating characteristic (ROC) curve analysis using data from the total cohort. The area under the ROC curve (AUC), $95\%$ CI, sensitivity, and specificity were calculated for various score thresholds. ## 3.1. Patient Characteristics The conservative cohort included 609 patients (average age: 77.1 ± 7.6 years; 226 patients were aged ≥80 years; 376 males and 233 females; in-hospital stay: 82.8 ± 26.7 days; follow-up period: 17.9 ± 22.1 months). The surgical cohort included 903 patients (average age: 75.0 ± 6.3 years; 233 patients were aged ≥80 years; 631 males and 272 females; in-hospital stay: 74.9 ± 30.5 days; follow-up period: 20.0 ± 20.1 months). Delirium was diagnosed in 56 patients ($9.2\%$) in the conservative cohort and 66 patients ($7.3\%$) in the surgical cohort during the in-hospital stay. There were no significant differences in the incidence of delirium between the conservative and surgical cohorts ($$p \leq 0.211$$). ## 3.2. Risk Factors of Delirium in the Conservative Cohort On univariate analysis in the conservative cohort, there were significant differences in age ($p \leq 0.001$), pre-injury mobility ($$p \leq 0.028$$), Hb ($$p \leq 0.038$$), and Alb levels ($$p \leq 0.011$$), ASIA Impairment Scale grade ($$p \leq 0.022$$), number of patients with cervical fracture ($$p \leq 0.025$$), and comorbid major organ injury ($$p \leq 0.006$$) between patients with and without delirium (Table 1). After binarizing age, mobility, and Alb and Hb levels using previously published thresholds (age: 80 years, mobility: independent or non-independent, Alb: 3.5 g/dL, Hb: 12 g/dL) [19,20,21], the multivariate analysis revealed old age (≥80 years; aOR: 2.26, $$p \leq 0.024$$), hypoalbuminemia (<3.5 g/dL; aOR: 2.15, $$p \leq 0.043$$), cervical fracture (aOR: 2.33, $$p \leq 0.020$$), and comorbid major organ injury (aOR: 2.01, $$p \leq 0.045$$) as independent variables related to the occurrence of delirium in the conservative cohort (Table 2). ## 3.3. Risk Factors of Delirium in the Surgical Cohort On univariate analysis in the surgical cohort, there were significant differences in age ($$p \leq 0.003$$), sex ($p \leq 0.001$), pre-injury mobility ($$p \leq 0.024$$), ASIA Impairment Scale grade ($$p \leq 0.008$$), number of patients with dementia ($p \leq 0.001$), diabetes ($$p \leq 0.045$$), cervical fracture ($$p \leq 0.019$$), cervical OPLL ($$p \leq 0.015$$), and a signal change in the spinal cord ($p \leq 0.001$) between patients with and without delirium (Table 3). After binarizing age, mobility, and ASIA Impairment Scale grade using previous thresholds (age: 80 years, mobility: independent or non-independent, ASIA Impairment Scale: A, B, or C, D, E) [19,22], the multivariate analysis revealed old age (≥80 years; aOR: 2.75, $p \leq 0.001$), dependence in pre-injury mobility (aOR: 2.28, $$p \leq 0.023$$), comorbid diabetes (aOR: 1.91, $$p \leq 0.030$$), and presence of a cervical fracture (aOR: 2.33, $$p \leq 0.020$$) as independent variables related to the occurrence of delirium in the surgical cohort (Table 4). ## 3.4. Establishment of a Delirium Risk Score Based on the results of the multivariate analyses of the two cohorts, old age (>80 years), hypoalbuminemia (<3.5 g/dL), dependence in pre-injury mobility, the presence of a cervical spine fracture, comorbid major organ injury, and comorbid diabetes were included in the delirium risk score calculation (Figure 2). Each variable was scored at 1 point based on the calculated aORs and indicated definitions. The delirium risk score was calculated as the sum of the six variables, with a total score varying from 0 to 6. The ROC analysis using data from the total cohort revealed that the AUC of the score for predicting delirium was 0.66 ($95\%$ CI: 0.61–0.71, $p \leq 0.001$, Figure 3). For a risk score threshold of 2 points, the sensitivity was 0.784 and the specificity was 0.455 (Table 5). For a risk score threshold of 3 points, the sensitivity was 0.480 and the specificity was 0.740. ## 4. Discussion In our dataset, approximately $10\%$ of elderly patients with cervical cord injury and/or cervical fracture who were treated conservatively or surgically developed delirium during the in-hospital stay. We established a screening system for delirium using six risk factors, including older age, hypoalbuminemia, cervical spine fracture, major organ injury, dependence on pre-injury mobility, and diabetes. Patients with at least two of these six risk factors could be predicted to develop delirium during treatment with $78\%$ sensitivity and $46\%$ specificity, regardless of the type of therapy. There is no consensus on how to establish a scoring system. For example, the Spine Instability Neoplastic Score, which is a standard scoring system for patients with spinal metastasis, was recently created using expert opinions [24]. In contrast, the Katagiri scoring system, which predicts the prognosis of patients with skeletal metastasis, was recently created using the results of statistical tests [25]. In the current study, we created a delirium scoring system by combining risk factors (as determined by regression analysis) from two cohorts. This approach was used because we aimed to create a scoring system that could be applied to elderly patients with traumatic SCI and/or cervical fractures regardless of the selected therapeutic method. Additionally, the current scoring system was developed using cases with cervical SCI as well as cases with cervical fractures, enabling physicians to apply this scoring to patients with cervical fractures who are at risk of neurological deterioration after admission. Delirium is known to negatively impact both the healthcare system and the patient. Leslie et al. [ 4] analyzed hospitalized elderly patients in the non-intensive care general medical unit and concluded that patients who experienced delirium during hospitalization had a $62\%$ increased risk of mortality, with an average loss of $13\%$ in life years, compared to that for patients without delirium. Additionally, in a study on the effect of delirium in patients with traumatic SCI by Cheung et al. [ 13], patients with delirium had a significantly longer hospital stay than the control group. These results indicate the importance of the prevention of delirium as a component of the quality of treatment. Cheung et al. [ 13] evaluated the risk factors for delirium in 192 patients with traumatic SCI and concluded that old age at the time of injury and a low initial motor score were risk factors for delirium. Similarly, we found that old age was a risk factor for delirium in both the surgical and conservative treatment cohorts. In addition to old age, we included hypoalbuminemia, dependence on pre-injury mobility, the presence of a cervical fracture, comorbid major organ injury, and comorbid diabetes in our delirium risk scoring system, based on the present statistical results. Dependence on pre-injury mobility might reflect aspects of physical aging that cannot be determined by the number of years of life. Hypoalbuminemia and diabetes are well-known to be associated with delirium [26,27]. The presence of a cervical fracture and a comorbid major organ injury could be considered indicators of an extremely severe trauma, which is reported to be a major risk factor for delirium [28]. Contrarily, the motor score was not identified as a risk factor in either cohort in the current study. The postulated reason for this result is that the cohorts in the current study included patients who suffered a cervical fracture without neurological deficits. Furthermore, sex was not a significant variable in either cohort. To prevent delirium during in-hospital treatment, the most important non-pharmacological multi-component approaches include (a) attempting to keep patients well-oriented to their surroundings and making them more familiar, (b) providing stimulation to maintain memory and thinking skills, and (c) attempting to improve sleep [29]. Such approaches can reduce the occurrence of delirium by $43\%$ compared to usual hospital care practices [29,30]. Although such treatments show effectiveness in preventing delirium, not all patients are capable of receiving them because of increased medical costs and limitations in medical staffing. Hence, screening tools for the development of delirium can aid physicians and the medical staff by identifying patients potentially at high risk for delirium; the limited medical resources can then be preferentially applied to such patients. We recommend using 2 points as the cut-off value for physicians who apply the current scoring system as a screening tool for delirium to real-world patients evaluated during treatment because of the high sensitivity of the test value. Additionally, we recommend using 3 points as the cut-off value when attempting to identify high-risk patients for delirium because of the high specificity of the test value. There are several limitations to the present study that need to be addressed. First, the diagnosis of delirium was dependent on the criteria of each institution. Additionally, the timing of the onset of delirium and its severity were not considered. Second, the database used in the current study was already established, and all data were collected retrospectively. This database was imbalanced in terms of sex; there were 1007 males and 505 females. Further, some conditions, such as dementia, might have been under-evaluated, which might have influenced the results of the current study. The data were collected from high-volume trauma centers; patients with severe frailty, dementia, or other degenerative conditions might not have been brought to such institutions. All such differences might bias the current results. Third, this retrospective study analyzed relatively recent data from patients who could be treated with standard delirium measures. Additionally, the retrospective chart review might miss several cases of delirium, especially in those with mild ones. Indeed, the overall incidence of delirium in the current study ($8.1\%$) was low compared to that previously reported [2]. Fourth, our scoring system does not take into account the patient’s psychological perspective. Finally, the AUC of our delirium risk score system was relatively low. Further, the system was not validated in an independent dataset; this constitutes the most considerable limitation of the current study. Accordingly, the current scoring system must be validated in independent samples before clinical application. The benefit of the current screening tool is that it can be used in patients before treatment decision-making, making it possible to evaluate the delirium risk at an early stage, such as upon admission. Furthermore, the current screening tool can be scored using only data from medical records, without subjective data obtained from interviews by trained experts. Finally, identifying patients at high risk for delirium before deciding on treatment strategies can positively affect the patient’s outcomes. ## 5. 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--- title: An Attentional Bias Modification Task, through Virtual Reality and Eye-Tracking Technologies, to Enhance the Treatment of Anorexia Nervosa authors: - Franck-Alexandre Meschberger-Annweiler - Mariarca Ascione - Bruno Porras-Garcia - Marta Ferrer-Garcia - Manuel Moreno-Sanchez - Helena Miquel-Nabau - Eduardo Serrano-Troncoso - Marta Carulla-Roig - José Gutiérrez-Maldonado journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054656 doi: 10.3390/jcm12062185 license: CC BY 4.0 --- # An Attentional Bias Modification Task, through Virtual Reality and Eye-Tracking Technologies, to Enhance the Treatment of Anorexia Nervosa ## Abstract Mirror exposure therapies (METs) have been shown to be effective in reducing body image disturbances through the habituation process. Virtual reality (VR) combined with eye-tracking techniques can provide innovative solutions to some of METs’ limitations reported with patients with anorexia nervosa (AN), especially the negative influence of body-related attentional bias (AB). This pilot study aimed to assess the preliminary efficacy of a new VR-based AB modification task (ABMT) among healthy women and the procedure’s user experience. AB levels towards weight- and non-weight-related body parts, using complete fixation time (CFT) and number of fixations (NF), were assessed throughout the ABMT procedure (300 trials). The user experience was evaluated at the end of the procedure. The results showed that VR-based ABMT was effective in reducing AB significantly after 150 trials for both CFT- and NF-based measures, although 225 trials were necessary to get the same result for women with an NF initially more oriented towards weight-related body parts. Overall, the software received a “C-rating” on a scale from “A” (most usable) to “F” (least usable). These results provide evidence of the opportunity to use a VR-based ABMT procedure to reduce AB and improve existing treatments for AN. ## 1. Introduction Eating disorders (ED) are severe conditions defined by dysfunctional eating behaviors that negatively affect physical and mental health [1]. Anorexia nervosa (AN), characterized by low weight (less than $85\%$ of what is expected considering age and height), alterations in the perception of body image, and an extreme fear of gaining weight, is considered one of the most serious EDs. Indeed, AN has a multitude of medical complications derived from the state of malnutrition and high comorbidity with other disorders, especially anxiety, depressive, and personality disorders [2]. Fear of gaining weight, defined as an extreme fear of the possibility of gaining weight in the entire body or in some specific body parts even at a significantly low weight [3], and body anxiety toward specific body areas (i.e., the body parts that the individuals may relate to weight) are considered one of the strongest risk and maintenance factors of AN symptomatology and have been related to more severe ED symptoms [4,5]. Furthermore, body image disturbances (BIDs) (i.e., the dysfunctional way individuals experience their body weight and shape), both in their perceptual components (body image distortions) and affective components (body image dissatisfaction) (e.g., [6]), cause a series of avoidance behaviors and negative checking strategies towards one’s own body [7,8]. To reduce the effects of these factors, mirror exposure therapies (METs) have been used to enhance AN cognitive-behavioral therapy (CBT) through the habituation process [9,10]. METs, which involve the patients systematically observing their bodies or specific body parts over a certain amount of time and describing them [11], showed promising results in ED patients [12,13] and individuals with high body dissatisfaction [14]. However, the habituation process used in MET protocols might be limited due to cognitive processes leading to selective attention to body information, a phenomenon known as body-related attentional bias (AB). AB is a propensity to pay more attention to certain types of stimuli or information (e.g., disorder-relevant information) than to other sorts of information [8]. Previous studies showed this AB in adult women with high body dissatisfaction (e.g., [15]) and patients with ED (e.g., [16,17]) as a tendency to focus more on self-reported unattractive body parts than other body parts. Indeed, cognitive theories about body dissatisfaction suggest that the processing of information about body image might be influenced by schemas related to appearance, shape, and weight, which lead to increased negative emotions regarding body image (such as fear of gaining weight and body anxiety) and unhealthy behaviors aimed at changing shape and weight for individuals with ED [8]. Furthermore, these theories suggest that body-related AB may be an important risk factor for maintaining BIDs and associated mental health concerns in patients with EDs and healthy individuals (see the full review in [18]). Indeed, many previous studies showed an association between AB and BIDs [18]. For example, when AB was induced toward one’s self-reported unattractive body parts, it led to greater body dissatisfaction in healthy women [19], healthy adolescents, and adolescents with AN and bulimia nervosa (BN) [17]. In contrast, inducing AB toward self-reported attractive body parts of body-dissatisfied women elicits higher levels of body satisfaction (e.g., [14,17]). In addition, an AB predominantly focused on weight-related body parts (such as legs, thighs, buttocks, hips, stomach, or waist) has been shown to be a mediator of the relationship between body mass index and body dissatisfaction [20]. To reduce the negative effects of AB on the mechanisms underlying psychological disorders, AB modification tasks (ABMT) have been proposed to modify early, automatic, and usually unconscious AB [21]. To achieve this, repeated practice of a skill over a period of time was proposed to produce neuroplasticity changes in the brain, in order to strengthen the neural correlates of attention and improve attentional control [22]. Although ABMT procedures have been widely proposed for individuals with anxiety disorders to reduce the attentional avoidance of a threatening stimulus and improve habituation processes (see the overview in [23]), only a few studies have focused on the ABMT procedure in individuals with ED or high body dissatisfaction [22]. Among the studies that proposed ABMT for ED patients or women with high body dissatisfaction, most were focused on food-related AB (e.g., [24,25]). Some of them centered on body-related ABMT but used an attentional probe task to draw attention to negative shape/weight-related words or neutral ones (e.g., [26]). To our knowledge, only two studies have proposed a body-related ABMT procedure using body image stimuli, although with non-clinical participants so far. One study trained attention toward self-reported attractive and unattractive body parts through the eye-tracking (ET) technique [19]. The other was based on the presentation of pictures of the self-defined positive and negative parts of one’s own body using a dot-probe task [27]. Due to a lack of studies so far with ED patients, existing body exposure therapies for the treatment of ED, such as METs, usually aim to extinguish negative cognitive, emotional, and behavioral responses to one’s own body [28], rather than directly modify body-related AB in ED patients [22]. In addition, apart from its limitations due to the influence of body-related AB during the habituation process, METs have other specific limitations with AN patients. First, the risk of eliciting habituation toward extremely low weight and very skinny body shapes may make it difficult to use METs in severe cases of AN [29,30]. METs may increase the probability of rejection and dropout from treatment [9], due to the highly negative reaction of some AN patients while initially observing their bodies [11]. Finally, METs are usually conducted in controlled settings (e.g., therapists’ offices, research laboratories, or ED treatment centers), so it can be difficult to generalize the positive changes learned by applying body exposure protocols [31]. The procedure proposed in the current study, based on new technologies such as virtual reality (VR) and ET, may provide innovative solutions to METs’ limitations mentioned above (the influence of body-related ABs, a high dropout rate, and difficulties in generalizing positive results). In the last two decades, VR-related hardware and software have made impressive headway, allowing this transformative technology to be used in various fields of psychology, both in research and therapeutics. For example, VR has been extensively and successfully used to investigate and improve exposure-based therapies for the treatment of ED: to propose a food-cue exposure protocol for the treatment of BN and binge-eating disorder (BED) (e.g., [32]), to assess body image distortion and body dissatisfaction [33], to elicit and reduce fear of gaining weight and body anxiety in patients with AN through VR-based body exposure [34], and to modify and improve BIDs in healthy individuals (e.g., [35,36]) and in patients with EDs (e.g., [37,38]). For exhaustive reviews about VR-based therapeutic applications, see [39,40]. VR technology enables researchers and therapists to create highly realistic simulations of real-life settings and situations that individuals have associated with their body and weight concerns (e.g., a dressing room, a bathroom, or a locker room). It also allows the design of three-dimensional (3D) avatars that reproduce the patients’ silhouettes based on their own body size, height, skin tone, and clothes [41]. In addition, VR is capable of moving the same way as individuals due to full-body motion tracking. This encourages participants to perceive and feel their respective virtual bodies as if they were their real bodies by activating the feeling of ownership over a virtual avatar [42,43], a paradigm known as the full-body ownership illusion [44]. As a result, some studies have shown that VR technology could improve treatment adherence and acceptance rates compared to in vivo exposure therapies [45] and have higher ecological validity, allowing generalization of the positive results acquired during VR-based therapies [31,41]. VR technology provides new opportunities for research on AB in patients with ED, due to the integrated ET feature in the Head-Mounted Display (HMD). ET allows a direct, continuous measure of AB that records participants’ saccades toward visual stimuli in real time [46]. By tracking attention over time, ET provides a detailed, direct, and objective picture of attentional patterns, bringing out avoidance and engagement with stimuli over time (e.g., with food cues or the specific body parts of participants). This allows attentional processing to be detected at both automatic and strategic stages. Furthermore, ET-based methods are ecologically valid, as they can be used to study AB on a more naturalistic visual array [47]. Several studies have already used VR technology in combination with ET techniques to investigate AB toward body parts to enhance body exposure techniques for the treatment of ED (full reviews are available in [48,49]). For example, body parts have been classified in weight- and non-weight-related areas based on the delineation established in the physical appearance anxiety scale of the Physical Appearance State and Trait Anxiety Scale (PASTAS) questionnaire [50] to assess AB in both areas of interest and its relationship with ED symptoms (such as fear of gaining weight, body anxiety, or BIDs) (e.g., [51]). The use of these VR and ET techniques revealed differences in the attentional patterns between genders [52,53]. Consequently, the simultaneous use of VR technology and ET techniques offers considerable advantages for developing develop new ABMT procedures, such as greater motivation of the participants to carry out the training, the continuous measurement of attentional patterns during and after the task, or the control of participants’ fixations in real time to ensure that individuals effectively follow the procedure without attentional avoidance. The current pilot study aimed to evaluate a new body-related ABMT by using VR and ET technologies, among healthy women as a first stage. The proposed procedure was adapted from that of Smeets et al. [ 2011] [19], in which participants were instructed to detect and identify the nature of geometrical shapes that appeared on their body parts, previously self-reported as “attractive” or “unattractive”. As a result, the attention of the participants was directed to some specific body parts, and AB was temporally modified. The objective of the present study was to assess the preliminary efficacy and usability of this VR-based intervention and figure out the most suitable task duration until a significant reduction in AB was achieved. In addition, the user experience was evaluated at the end of the procedure. The proposed VR-based ABMT intervention was expected to: (i) reduce AB significantly at some point in the procedure compared to the baseline; and (ii) obtain an acceptable user experience rating (i.e., easy-to-use), which would allow a higher level of engagement and a lower dropout rate. Positive results of the present study would enable us, in a second stage, to optimize the procedure and study the efficacy of the ABMT intervention in patients with AN, to reduce AB as a risk and maintenance factor of AN symptomatology, and to enhance possible future therapeutic adaptations to improve currently existing treatments for AN, such as METs or VR-based body exposure. ## 2.1. Participants Of the seventy women who were initially candidates to participate in the study, six were excluded as they reported that they met at least one exclusion criteria, and four candidates did not complete the full study procedure as they reported dizziness once immersed in the VR environment. Finally, sixty college women (Mage = 24.83 years, SDage = 6.64 years; MBMI = 22.23 kg/m2, SDBMI = 3.25 kg/m2) from the University of Barcelona’s Faculty of Psychology, recruited using social networks and flyers, voluntarily participated in this study and went through the entire procedure. The exclusion criteria were self-reported diagnoses of mental disorders with psychotic or manic symptoms (e.g., psychotic disorders or bipolar disorders), self-reported diagnoses of ED (AN, BN, BED), pregnancy (which could temporarily distort the body image), epilepsy, and visual conditions that could prevent exposure to a VR environment or distort eye-tracking measures. ## 2.2. Instruments The participants were immersed in a VR-environment using a HMD HTC VIVE Pro Eye™, including dual-OLED displays with a combined resolution of 2880 × 1600 pixels and 615 PPI. The full body tracking feature (i.e., the process of tracing the movements of the participants and applying them to their avatars in real-time within an immersive environment) was ensured using five body trackers: one in the HMD itself, two in the VR controllers the participants hold in their hands, and two feet-trackers (VIVE trackers V3.0), which communicated wirelessly with four SteamVR Base Station 2.0™. This created a sufficient play area (up to 10 m × 10 m) with high stability and pinpoint accuracy. Furthermore, the eye-tracking feature (ET), provided with the HMD HTC VIVE Pro-Eye and powered by Tobii™, was used to detect eye-movement while the participants were looking at their avatars’ bodies in a VR-environment with very high precision (binocular gaze data output frequency: 120 Hz, spatial accuracy between 0.5 and 1.1 degrees, 5-point calibration process). Each participant was immersed in a VR environment consisting of a room, developed using Unity 3D 5.6.1. software, without any furniture except for a large mirror located 1.54 m in front of the participant and two boxes placed on the floor beside her (see Figure 1). The participant could thus see her whole image in the mirror, even while she was moving, due to full-body tracking. This image consisted of an avatar (see Figure 1), which was initially generated from a generic Caucasian female avatar designed using the software Blender v. 2.78 and then finely adjusted to each participant’s height and silhouette through an initial photography procedure. The avatar wore standard clothes (including a t-shirt, trousers, and shoes, as shown in Figure 1), whose colors could be adapted to fit the actual participant’s clothing. The avatar’s skin color could also be adjusted to fit the participant’s. Finally, to reproduce the actual participant’s condition during the task and to reduce the influence of individual hairstyles, the avatar wore a HMD, and its head was covered by a grey cap. ## 2.3.1. Body-Related AB Assessment To assess the body-related AB, participants were asked to stand with their arms slightly raised and legs separated on fixed reference marks (green spheres for the arms, footprints for the feet), and gaze freely at their avatar in the mirror for 30 s (as done in previous studies, e.g., [51]), while the fixation patterns were recorded by the ET feature of the HMD (RAW ET data). During the process, as a cover story to avoid reactivity, the participant was asked to remain still while the virtual avatar position was recalibrated. In addition, during the process, participants were asked to gaze at four fixed reference marks located around the avatar for 4 s. This information was then used by software developed specifically for this purpose to eventually correct the raw ET fixation data vertically and horizontally (drift-corrected ET data), to validate the ET calibration, and ensure the best precision of the AB assessment (see Figure 2). The drift-corrected ET data were then imported into the Open Gaze and Mouse Analyzer (OGAMA) software (Freie Universität, Berlin, Germany) to calculate the number of fixations (visual act of maintaining one’s gaze at a single location for a minimum duration, usually 100–200 ms; [54]) and the visual fixation duration in each specific body-related area of interest (AOI). Such specific gaze-behavioral measures have been shown to be a reliable and continuous measure of attention allocation towards specific body areas in previous studies using ET techniques (see full reviews in [47,48]). AOIs were divided into two groups based on the Weight Scale of body items in the PASTAS questionnaire [50]: the weight-related AOI group, including legs, thighs, buttocks, hips, stomach, and waist; and the non-weight-related AOI group, including the remaining body parts (see Figure 3). The participant’s head was not taken into consideration since the head of the avatar wore an HMD, like the participant, so the fixation of the gaze on this part of the body has more to do with the attention that this device captures than that really dedicated to the head of the participant. The Weight Scale of body items of the PASTAS questionnaire has good internal consistency (with a Cronbach’s alpha of 0.88), a test-retest correlation coefficient (0.89) and convergent validity with other scales of eating disturbances (EDI-DT, EDI-B), body dissatisfaction (EDI-BD), physical appearance evaluation (BSRQ-PAE), and anxiety (STAI) [50]. Finally, like in previous studies (e.g., [55]), AB was assessed through the AB_CFT variable, which is the difference between the complete fixation time (CFT) in the weight-related AOI group and the non-weight-related AOI group, and through the AB_NF variable, which is the difference between the number of fixations (NF) in the weight-related AOI group and the non-weight-related AOI group. Both AB_CFT and AB_NF could thus have positive or negative values, depending on whether the participants’ visual attention was predominantly focused on weight-related AOIs (positive values) or non-weight-related AOIs (negative values). Only a few studies focused of the reliability and internal consistency of AB measures (such as fixation duration or number of fixations) using the eye-tracking paradigm while participants were freely looking at body parts (mainly emotional faces) (e.g., [56]). Cronbach’s alpha estimates for the total fixation time and number of fixations were high (between 0.94 and 0.96) when participants’ viewing time was greater than 2 s. This indicates the excellent reliability of these measures [56]. However, reliability estimates were very low when the viewing duration was shorter (less than 1 s) but increased afterwards [57]. These results suggest that AB measures using eye-tracking techniques have excellent reliability overall when the measures are averaged over time, but their reliability varies substantially over the presentation time of the display [58]. In the present study, AB was assessed through a 30-s free-viewing task on the avatar in the mirror. In addition, the test-retest reliability of AB measures through ET techniques was estimated to be 0.68 (“good” range) for a one-week test-retest [56] and between 0.39 and 0.65 (“fair” range) for a 6-month test-retest [58]. In the present study, AB assessment’s reliability will be calculated and reported in the “results” paragraph below, using the intraclass correlation coefficient (ICC) that has been shown to be more appropriate than Cronbach’s alpha for ET measurements [59]. ## 2.3.2. User Experience User experience was assessed through the System Usability Scale (SUS) [60]. The SUS is a 10-item questionnaire with 5 response options. It yields a single number between 0 and 100, which represents a composite measure of the overall usability of the system that is being studied (0 stands for the least usable system and 100 for the most usable one). It is currently the most used questionnaire for measuring perceptions of usability and has been tested on hardware, consumer software, websites, cell phones, interactive voice responses (IVRs), and even the yellow pages. It has become an industry standard, with references in over 600 publications [61]. The scale has good reliability (with a Cronbach’s alpha of 0.91) and concurrent validity (a significant correlation of 0.806 between the SUS and a single 7-point adjective rating question for an overall rating of “user friendliness”) [62]. ## 2.4. Procedure This study was approved by the Bioethics Commission of the University of Barcelona (CBUB). At the beginning of the study, participants freely signed a consent form, which informed them about data confidentiality and the possibility of withdrawing from the study at any point without consequences. Additionally, confidentiality was ensured by assigning a different identification code to each of the participants. Participants were told that the study aimed to study body image disturbances through the virtual reality procedure. Weight and height were measured to calculate the BMI. A virtual avatar was then created from two photos taken using frontal and lateral perspectives, matching the avatar’s profile to the participant’s real-size body silhouette (e.g., arms, legs, hips, waist, chest, stomach, breast, and shoulders). The participant was then equipped with HTC VIVE Pro Eye™ and body trackers and immersed in the VR room. Once in the room, five-minute visuo-motor and visuo-tactile stimulation procedures adapted from previous studies (e.g., [34]) were applied to elicit a full body ownership illusion (i.e., to perceive and regard a virtual body as one’s own real body). At that point, body-related AB was measured for the first time as the baseline assessment. Furthermore, the ABMT intervention was applied, following the procedure adapted from Smeets et al. [ 2011] [19], in which AB was induced toward attractive or unattractive body parts to modify body dissatisfaction among non-clinical female participants. Since the purpose of our study was to reduce AB, the ABMT procedure was aimed at drawing the participant’s attention more equally to all the body parts (i.e., weight- and non-weight-related areas of interest defined based on the Weight Scale of body items of the PASTAS questionnaire [50]). Participants were instructed to detect and indicate the shapes (triangles, squares, and circles) or colors (red, green, and yellow) of different geometric figures. The software selected the shape and the color of each figure at random. In each trial, while they were staring at the figures, nearby body areas were lit up progressively. After 4 s holding the gaze, a new figure was projected. If the participant looked away due to a lack of attention before those 4 s, the software waited for them to look at the current projected figure again (the illumination of the nearby body was automatically paused by the software). Real-time fixation data were available due to the HMD’s eye-tracking function. During the intervention, the figures appeared on weight-related body parts in $45\%$ of trials, on non-weight-related body parts in another $45\%$ of trials, and on two neutral stimuli (boxes) located in the ground next to the avatar’s feet for the remaining $10\%$ of the trials (see Figure 4). The ABMT procedure consisted of projecting a total of 300 figures, divided into 4 series of 75 trials that lasted about 5 to 6 min each. The balanced distribution of figures between weight- and non-weight-related body parts was respected within each series. In addition, figures were equally distributed between right and left sides of the body (in the case of lateralized body parts such as shoulders, arms, legs, and feet). In the first and third series, the participants had to indicate the shape of the projected figure, while in the second and fourth series, they had to indicate the color of the figure. The task for the participants was varied (shapes and colors) to reduce boredom [19]. The required time to complete the task for each series was approximately 6 min. Immediately after each series, AB was assessed again to provide a total of five AB assessments throughout the intervention (baseline, after series 1, 2, 3 and 4). The participant was allowed a 2-min rest time, sitting in a chair after each AB assessment and before beginning the next ABMT series. After the last AB assessment, the HMD and body trackers were removed. User experience was assessed using the System Usability Scale Questionnaire. Furthermore, the participant was able to rest for the necessary time while the researcher explained the real objective of the study and answered any possible doubts. ## 2.5. Statistical Analysis After drift-correction of RAW ET data, the data were imported into the OGAMA software to process both AB variables: AB_CFT (based on the complete fixation time) and AB_NF (based on the number of fixations) for five assessments over time (baseline and after ABMT series 1, 2, 3, and 4). Further details about this procedure can be found in Porras-Garcia et al. [ 2020] [34]. All the subsequent statistical analyses were performed with SPSS version 27. Two outliers were detected in the AB baseline assessments by inspection of a boxplot. These were excluded from the analysis. Thus, only 58 participants were included ($$n = 58$$). For the purpose of analysis and for each AB variable (AB_CFT and AB_NF), the participants were divided into two AB groups: one group with a positive baseline AB outcome, in which the AB was predominantly oriented towards weight-related body parts, and another group with a negative baseline AB outcome, in which the AB was predominantly oriented towards non-weight-related body parts. The repartition of participants into weight-oriented and non-weight-oriented AB groups was performed independently for each AB variable (AB_CFT and AB_NF), and the statistical analysis was carried out separately. First, independent-sample t-tests were conducted to assess whether there were any significant group differences in age and BMI. Furthermore, mixed between the AB group within AB assessment times, analyses of variance (ANOVA) were conducted for each AB variable (AB_CFT and AB_NF). Regarding the assumptions of ANOVA analyses, homogeneity of variance and sphericity were met for all AB variables (as demonstrated respectively by Levene’s and Mauchly’s tests with $p \leq 0.05$). Although some of the AB variables were not normally distributed (as shown by the Shapiro–Wilk tests: $p \leq 0.05$), it was decided to run the tests anyway since ANOVA is considered a reasonably robust test for deviations from normality [63]. Bonferroni adjustment for multiple comparisons was used in the post-hoc analysis. As for the user experience, Pearson correlations were run to assess the relationship between the System Usability Scale outcome, BMI, and age in the overall sample. ## 3. Results First, AB assessment reliability was calculated with SPSS using the intraclass correlation coefficient (ICC) [59]. Both AB_CFT (ICC = 0.619) and AB_NF (ICC = 0.678) showed “good” reliability (between 0.60 and 0.74, following the guidelines for interpretation proposed by Cicchetti, 1994 [64]). The descriptive results revealed that, overall, participants spent more time looking at non-weight-related body parts than weight-related body parts, as indicated by the negative outcome of AB_CFT (M = −236 ms < 0, SD = 6018 ms). They also showed a higher number of fixations on non-weight-related body parts than weight-related body parts, as indicated by a negative outcome of AB_NF (M = −2.31 < 0, SD = 12.40) (see Table 1). Independent sample t-tests confirmed no significant mean differences ($p \leq 0.05$) in age and BMI between comparison groups formed from baseline AB assessments. As expected, there were significant mean differences ($p \leq 0.001$) in baseline AB assessment between comparison groups (i.e., between weight- and non-weight-oriented AB groups), regardless of whether these groups’ formation was done using the complete fixation time or the number of fixations. Figure 5 shows the evolution of the AB measures (using complete fixation time on Figure 5a and using number of fixations on Figure 5b) over time (during the AB assessment times: at baseline and after each of the 4 ABMT series). A two-way mixed between AB group and within AB assessment times ANOVA was conducted for both attentional bias measures (i.e., using AB_CFT and using AB_NF). The results indicated a statistically significant interaction between the group and assessment time for the AB_CFT (F [4, 53] = 14.707, $p \leq 0.001$, partial η2 = 0.526) and the AB_NF (F [4, 53] = 7.284, $p \leq 0.001$, partial η2 = 0.355). Post-hoc analyses assessed the change in AB_CFT values from baseline to each ABMT series separately in both groups. The results revealed that, both in women with a non-weight-oriented AB and in women with a weight-oriented AB, only two ABMT series were necessary to produce a significant ($p \leq 0.001$) reduction in their AB (see Table 2). Regarding AB_NF, the results revealed that only two ABMT series were necessary to produce a significant ($$p \leq 0.006$$) reduction in the AB in women with a non-weight-oriented AB at baseline, while three ABMT series were necessary to produce a significant ($$p \leq 0.007$$) reduction in the AB in women with a weight-oriented AB at baseline (see Table 3). Finally, a significant increase in the number of fixations towards weight-related body parts could be noted among weight-oriented AB women after the ABMT fourth series ($$p \leq 0.030$$ for AB_NF mean differences between AB assessment after the 3rd ABMT series and after the 4th ABMT series) (see Table 3). Regarding the user experience, the results with the entire sample ($$n = 58$$) of the SUS showed a mean of 67.46 (SD = 10.90) (see Table 1). Pearson correlation analysis showed a significant negative relationship between user experience and age (r[56] = −0.30, $$p \leq 0.023$$): the younger the participant, the more usable our software was perceived to be. In contrast, no significant Pearson correlation was found between user experience and BMI ($p \leq 0.05$). ## 4. Discussion The results of the pilot study provide initial evidence of the efficacy of the proposed ABMT procedure, through VR and ET technologies, in significantly reducing AB (i.e., obtaining a more balanced attentional pattern between weight- and non-weight-related AOIs), considering the AB_CFT and the AB_NF in healthy women. Furthermore, post-hoc analyses showed that 150 trials (2 series of 75 trials) of the figures’ projection onto the avatar were sufficient to produce a significant reduction in AB_CFT and AB_NF measures, except for the AB processed from the number of fixations among women with initial AB predominantly focused on weight-related body parts. In this last group, 225 trials (3 series of 75 trials) were necessary to obtain the same results. These results are important since body-related AB has been shown to be an important factor in maintaining BIDs in patients with ED [16] and healthy individuals [18] and a mediator of the relationship between BMI and body dissatisfaction [20]. These preliminary results obtained with healthy female participants in this pilot study would have to be confirmed in a future clinical study. They indicate that the proposed ABMT procedure could probably be used as an adjunctive technique to enhance body and mirror exposure therapies for ED patients, whose current objective is to extinguish negative cognitive, emotional, and behavioral responses to their own body [28], considering the modification of the body-related AB underlying the psychological mechanisms involved in these responses [22]. Our study shows the results of AB reduction assessed through two indices (AB_CFT and AB_NF). However, both measures should be interpreted separately, since CFT and NF have been shown to be related to different psychological constructs that reflect and influence cognitive, emotional, and behavioral responses [65]. For example, one study revealed that the nature of the AB can vary over time while emotional pictures are processed. A shorter CFT measured after the first seconds of exposure could indicate avoidance of some detected negative stimuli, even if the NF remains high [66]. Another study with children indicated that increased snack intake was influenced by longer CFT for food cues but not by the NF towards these cues [67]. Possible explanations of these results are that gaze duration activates greater neurological responses (especially in “reward” regions) to food cues than the number of fixations [68]. When fixation time is longer, there is longer activation of brain regions associated with future weight gain and weight maintenance in response to food cues (e.g., middle frontal gyrus, middle temporal gyrus, and insula) [69], or longer activation of brain areas related to food intake regardless of the number of fixations [67]. Thereby, it seems that CFT has a greater influence on emotional, and behavioral responses than NF. However, another study with individuals with depression showed that a greater number of fixations, responsible for repeated turning of attention towards the dysphoric stimuli, rather than longer fixation duration on these stimuli, likely reflects sustained or elaborative processing of the stimuli. Repeated fixations within a stimulus may be necessary to process the image comprehensively [70]. Hence, the choice of 2 series of 75 ABMT trials (required to significantly reduce the AB_CFT for all comparison groups) or 3 series of 75 trials (required to significantly reduce the AB_NF among women with an initial focus predominantly on weight-related body parts) should be carefully considered in future studies, depending on their specific objectives. This pilot study aimed to obtain preliminary results with non-clinical participants to evaluate the procedure’s efficacy and usability and the ABMT duration that is strictly necessary to ensure this efficacy without producing unnecessary fatigue among participants. Indeed, these results provide researchers with objective data, which allows them to adapt and optimize the procedure in future studies with clinical participants with AN. In fact, standing in front of a mirror and looking at geometric figures for more than 20 min might lead to lower patient engagement and a higher dropout rate. This point is even more important because it is often difficult to keep AN patients committed to treatment, with a high proportion failing to complete the full course of treatment [71]. A significant level of dropout among AN patients, reported in the range of 20–$40\%$ for CBT, has serious implications for recovery, research, and the development of new treatments [72]. Several studies have shown that AN patients who leave treatment prematurely are unlikely to recover independently [73] and are more likely to have a poor long-term outcome. In turn, this may lead to greater chronicity of ED symptomatology [74]. For these reasons, it was especially important for us to consider the participants’ user experience throughout the study procedure. Indeed, paying attention to the participants’ own perspective has been highlighted by the increased focus on assessing client satisfaction in ED health services [75,76], since dissatisfaction with treatment can lead to treatment delay, failure to engage, and, ultimately, treatment withdrawal [77,78]. Regarding the procedure’s usability, our results indicated that the user experience was very close to the average SUS score of 68 calculated from 500 studies, granting our software a “C-grade” on a scale ranging from “A” (most usable) to “F” (least usable) [61], with a more satisfying user experience reported by younger participants. These results are acceptable as a starting point, but special attention will have to be paid to improving the user experience, especially considering the age and BMI of the participants in future clinical studies with AN patients. Indeed, our sample had a mean age of 24.93 years (with SD = 6.73 years) and a mean BMI of 22.28 kg/m2 (with SD = 3.27 kg/m2). In contrast, $40\%$ of individuals with AN are diagnosed during early adolescence or adolescence [79,80], and their BMI should be less than $85\%$ of what would be expected considering age and height [1]. A previous study showed that age influences body representations and thus the user experience, as older participants (more than 26 years old) were more resistant to changes induced by the bodily illusion than younger participants [81]. A better user experience reported by younger individuals in our study may thus positively influence the efficacy of the proposed VR-based ABMT procedure among younger participants (which is often the case for AN patients). For these reasons, it might be recommended that future research assess the efficacy of the proposed intervention separately for adults and adolescents with AN. Regarding the ABMT’s duration, the results of the AB assessment after the fourth ABMT series revealed that extending the task to more than 225 trials might be counterproductive. Indeed, the results showed that the mean differences in AB measures increased between the evaluation times after the third and fourth series in both comparison groups and in both AB indices (AB_CFT and AB_NF). However, this increase was only statistically significant for the group of women with an initial AB_NF orientation toward weight-related body parts. It is difficult to interpret this outcome with the available data, but this may be due to a certain relaxation in the participants’ attention during the last AB assessment task since they knew at that moment that the procedure was about to end. Another possible explanation of these results would be that, after 3 ABMT series (225 trials lasting around 18 min), the participants felt a greater level of stress and/or fatigue, which negatively affected their attention during the fourth series and the last AB assessment task. Indeed, the proposed VR-based ABMT procedure required both selective attention, which involves processing parts of the sensory input to the exclusion of others (i.e., in this study, locating and indicating each of the 300 geometric figures projected on the avatar), and sustained attention, which involves maintaining sensitivity to incoming stimuli over a long period of time (i.e., in this study, maintaining attention during a fairly long exposure procedure, as it took approximately 24 min to complete all four ABMT series). A previous study revealed that attentional performance (especially in its visual modality, not so much in its auditory one) could be negatively affected due to the increase in the level of stress over time [82]. The qualitative verbal feedback given by the participants during the debriefing at the end of the procedure may confirm such a hypothesis, since they often mentioned that the task was “long”, “repetitive” and “boring”. Hence, taking into account the above considerations and in order to ensure a proper balance between efficacy (i.e., a significant reduction in AB) and usability (getting participants committed to a “user-friendly” and “easy-to-use” procedure), we would recommend not extending the ABMT procedure to more than 225 trials: ideally 150 trials (considering AB_CFT assessment) or 225 trials (considering AB_NF assessment). Such a reduction in body-related ABMT, if confirmed in a further clinical study, could then be used in clinical practice to improve the efficacy of the usual AN treatment (e.g., mirror exposure therapy) carried out immediately after this AB modification. In the current study, the body-related AOIs used during AB assessment and ABMT intervention were defined based on the weight-related scale of the PASTAS questionnaire [50] and were the same for all participants without considering individual differences. Such a methodology differs from other studies, using a similar free-viewing and single-body paradigm but measuring the AB toward self-reported attractive vs. unattractive body areas (e.g., [14,17]). Since there may be weight- or non-weight-related body areas in both self-reported attractive and unattractive body parts for a specific participant, such differences may influence the results of the present study compared to other studies using other body-related AOI classification methodologies. Even so, the use of the weight-related scale of the PASTAS questionnaire, statistically representing higher body dissatisfaction (significant positive correlation between the weight-related scale of the PASTAS and body dissatisfaction assessed through the EDI-BD questionnaire [50]), has the advantage of simplifying the process in comparison with self-reported attractive vs. unattractive body areas. In addition, it is important to take into account that this study only included healthy participants, whose attentional patterns may be different than those of clinical patients with AN. Indeed, a previous study showed that AN patients have a longer fixation time and more fixations on weight-related body parts than non-clinical individuals [55]. Hence, the efficacy of the proposed ABMT procedure cannot be generalized and will have to be investigated in further clinical studies. However, some limitations in VR software should be considered in order to be addressed in future studies. First, the VR software allowed adaptation of the color of the avatar’s clothing and skin tone to match the actual appearance of each participant as closely as possible. However, although the general silhouette of the virtual body respected that of the participant (thanks to the initial photographic procedure), some specific parts of the avatar were not exactly that of each individual, such as the hairstyle (covered by a grey cap in the VR environment), the facial lines (most of the face was hidden by black glasses that simulated the HMD), or the specific outfit of each participant at the time of the intervention (the type of the avatars’ t-shirt, trousers, and shoes were the same for all participants). Hence, the full body ownership illusion (i.e., the identification with the virtual body) could be limited [83], which in turn could decrease the efficacy of the intervention. The use of 3D body scanning, allowing the simulation of an exact 3D biometric avatar with all the individual’s features, would notably enhance the realism of VR embodiment-based techniques and, consequently, improve VR studies on body-related issues for ED treatments. Some recent studies have already benefited from this 3D scanning technology to create more realistic avatars (e.g., see [84]). However, such technology is not usually available in eating disorder treatment centers (mainly due to its high cost), so our protocol of creating avatars of participants based on a photography procedure may be more adapted to clinical practice. In addition, the VR immersive environment generated by our software was quite neutral (only furnished with a mirror, a door, and two boxes; see Figure 1) and did not correspond to other settings that are more relevant in everyday life situations (e.g., a dressing room or bathroom). Consequently, the improvement in the VR environment in future research would be an opportunity to enhance the ecological validity of the studies, taking full advantage of all the possibilities offered by VR technology. 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--- title: Neuroprotective Effects of the Neural-Induced Adipose-Derived Stem Cell Secretome against Rotenone-Induced Mitochondrial and Endoplasmic Reticulum Dysfunction authors: - Mahesh Ramalingam - Sujeong Jang - Jinsu Hwang - Boeun Kim - Hyong-Ho Cho - Eungpil Kim - Han-Seong Jeong journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054666 doi: 10.3390/ijms24065622 license: CC BY 4.0 --- # Neuroprotective Effects of the Neural-Induced Adipose-Derived Stem Cell Secretome against Rotenone-Induced Mitochondrial and Endoplasmic Reticulum Dysfunction ## Abstract Mesenchymal stem cells (MSCs) have therapeutic effects on neurodegenerative diseases (NDDs) known by their secreted molecules, referred to as the “secretome”. The mitochondrial complex I inhibitor, rotenone (ROT), reproduces α-synuclein (α-syn) aggregation seen in Parkinson’s disease (PD). In this present study, we examined the neuroprotective effects of the secretome from neural-induced human adipose tissue-derived stem cells (NI-ADSC-SM) during ROT toxicity in SH-SY5Y cells. Exposure to ROT significantly impaired the mitophagy by increased LRRK2, mitochondrial fission, and endoplasmic reticulum (ER) stress (ERS). ROT also increased the levels of calcium (Ca2+), VDAC, and GRP75, and decreased phosphorylated (p)-IP3R Ser1756/total (t)-IP3R1. However, NI-ADSC-SM treatment decreased Ca2+ levels along with LRRK2, insoluble ubiquitin, mitochondrial fission by halting p-DRP1 Ser616, ERS by reducing p-PERK Thr981, p-/t-IRE1α, p-SAPK, ATF4, and CHOP. In addition, NI-ADSC-SM restored the mitophagy, mitochondrial fusion, and tethering to the ER. These data suggest that NI-ADSC-SM decreases ROT-induced dysfunction in mitochondria and the ER, which subsequently stabilized tethering in mitochondria-associated membranes in SH-SY5Y cells. ## 1. Introduction Parkinson’s disease (PD) is complex, and the second most common age-related multifactorial neurodegenerative disorder (NDD) characterized by motor and non-motor symptoms that reduce the quality of life. PD can affect all movement, including walking, physical balance, and speech, and is associated with a reduction of a neurotransmitter in the brain called dopamine (DA). Moreover, inhibition of the mitochondrial electron transport chain (ETC) complex I, leading to the production of reactive oxygen species (ROS), mitochondrial dysfunction, α-synuclein (α-syn) aggregation, and oxidative stress, is associated with the occurrence of PD [1,2]. Leucine-rich repeat kinase 2 (LRRK2; PARK8) can be modified by the overexpression of α-syn and might impair mitophagy [3,4] via the phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK1) and the E3-ubiquitin ligase Parkin (PARK2) [5]. Ubiquitin (Ub) is essential for the recognition of desired cargoes for degradation. PINK1 accumulates on the outer mitochondrial membrane (OMM) of damaged mitochondria by interacting with import receptor subunit translocase of the OMM (TOM complex) and activates parkin-mediated ubiquitination of OMM proteins to degrade the mitochondria [6]. The expression of PINK1 and parkin are functionally linked to mitochondrial fission [7] controlled by the dynamin-related protein 1 (DRP1), which translocates from the cytosol to the OMM. However, mitochondrial fusion is controlled by mitofusin 1 and 2 (MFN$\frac{1}{2}$) localized to the OMM and optic atrophy 1 (OPA1) located in the inner mitochondrial membrane (IMM) [8]. Abnormally increased mitochondrial fission may induce endoplasmic reticulum (ER) stress (ERS) [2]. α-syn aggregates accumulate inside the ER activating key sensing proteins, protein kinase R-like endoplasmic reticulum kinase (PERK) and inositol-requiring enzyme 1 α (IRE1α) [2], via the dissociation of ER chaperone glucose-regulated protein 78 (GRP78)/binding protein (BiP) [9]. PERK-dependent protein translational modifications on the alpha (α) subunit of eukaryotic initiation factor 2 (eIF2α) lead to the paradoxical increase of pro-apoptotic transcription factors, such as activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP) [10]. IRE1α activation leads to apoptosis through stress-activated protein kinase (SAPK; c-Jun N-terminal kinase; JNK) signaling [11]. ER membrane proteins interact with the OMM complex to exchange materials and transmit signals between them to maintain and balance cellular activities [12]. The exchange of calcium (Ca2+) between these two organelles [13] is regulated by a molecular tripartite tethering complex containing the inositol 1,4,5-triphosphate receptor (IP3R), glucose-regulated protein 75 (GRP75), and the voltage-dependent anion channel (VDAC) [14]. The interface between the ER and mitochondria for Ca2+ fluxes, among other cellular functions, encompasses the microdomain and mitochondria-associated membranes (MAM), and is tightly controlled by additional tethering proteins, such as MFNs. Mitochondrial MFN1 and 2 tethering complexes with MFN2 present in the ER membrane also physically connect ER and mitochondria [8]. Rotenone (ROT), a lipophilic piscicidal compound isolated from the roots of the subtropical plant species of Lonchocarpus and Derris suppresses the flow of electrons from the iron–sulfur centers in mitochondrial electron transport chain complex I. ROT reproduces PD-like impairments, such as decreased tyrosine hydroxylase, increased phosphorylation and aggregation of α-syn, and imbalanced autophagy degradation, which induces apoptotic death in SH-SY5Y neuroblastoma cells [15,16]. Treatments for PD mainly focus on restoring mitochondrial function and subsequently relieving motor symptoms, such as tremors, bradykinesia, and rigidity. Mesenchymal stem cells (MSCs) have the potential therapeutic capacity to replace dopamine and stimulate brain repair [17]. Bioactive molecules secreted from MSCs, referred to as “the secretome”, include growth factors, cytokines, chemokines, microvesicles, and exosomes known for their improved therapeutic effects [18]. Moreover, adipose tissue-derived stem cells (ADSC) have been reported to be easily harvested and can differentiate into neural cells in the presence of basic fibroblast growth factor (bFGF) and forskolin [19,20,21]. In this present study, we evaluated the neuroprotective effects of the neural-induced ADSC secretome (NI-ADSC-SM) on ROT-induced dysfunction of mitochondria, the endoplasmic reticulum, and their tethering proteins in human SH-SY5Y cells. ## 2.1. Effects of the NI-ADSC-SM on Intracellular Ca2+ Levels after ROT Exposure In this study, ROT-induced toxicity (48 h) induced higher Ca2+ production (Figure 1; $216.6\%$; $p \leq 0.001$) compared with control SH-SY5Y cells ($100\%$). The experimental study plan is described in Supplementary Figure S1b. However, treatment with a $50\%$ dilution of the NI-ADSC-SM against ROT toxicity for the last 24 h successively reduced the Ca2+ production ($101.8\%$; $p \leq 0.001$). The ADSC-SM did not reduce the ROT-induced Ca2+ levels; however, it showed increased Ca2+ levels in control cells. In our previous studies, ADSC-SM treatment significantly decreased the cell survival with increased ROS levels in control cells [15,16]. These results suggest that the NI-ADSC-SM has more protective effects than the ADSC-SM against ROT-induced toxicity in SH-SY5Y cells. ## 2.2. Effects of the NI-ADSC-SM on LRRK2 Protein Expression after ROT Exposure LRRK2 as one of the most common causes of PD provided much hope for the field of PD therapeutics. As shown in Figure 2, the LRRK2 protein level was significantly increased in SH-SY5Y cells after exposure to ROT for 24 and 48 h in Triton X-100-soluble (a) and -insoluble (c) fractions. At 48 h, ROT significantly increased LRRK2 expression ($p \leq 0.001$; Figure 2b); however, the levels were decreased by NI-ADSC-SM treatment in the Triton X-100-soluble ($p \leq 0.01$) and -insoluble fractions (Figure 2b and Figure 2d, respectively). These results suggest that the NI-ADSC-SM prevents LRRK2 expression changes during ROT exposure. ## 2.3. Effects of the NI-ADSC-SM on PINK1 and Parkin Protein Expression after ROT Exposure PINK1 and parkin promote mitochondrial health. In this study, the ROT exposure decreased PINK1 (Figure 3a; Figure 3b: $p \leq 0.05$) and parkin (Figure 3a; Figure 3c: $p \leq 0.01$) expression at 48 h in SH-SY5Y cells. Treatment with the NI-ADSC-SM or ADSC-SM increased parkin ($p \leq 0.05$) levels after ROT exposure (Figure 3c), though they had no effect on PINK1 (Figure 3b). Moreover, neither the ADSC-SM nor NI-ADSC-SM altered PINK1 or parkin expression in the control groups. These results suggest that the NI-ADSC-SM can rescue parkin expression after ROT exposure and may impede dysfunctional mitophagy and the parkin-mediated signaling pathway. ## 2.4. Effects of the NI-ADSC-SM on Ub Protein Expression after ROT Exposure Ub is a substrate for PINK1. Damaged mitochondria are known to be cleared by mitophagy mechanisms by mediating ubiquitination. In our time-course study, ROT decreased the levels of monomer (9 kDa) and polyubiquitinated (9~300 kDa) Ub in the Triton X-100-soluble fraction (Figure 4a), but increased them in the Triton X-100-insoluble fraction (Figure 4e). The levels of monomer (9 kDa; Figure 4b,c) and polyubiquitinated (9~300 kDa; Figure 4b,d) Ub in the Triton X-100-soluble fraction was upregulated by the NI-ADSC-SM ($p \leq 0.001$) or ADSC-SM ($p \leq 0.05$ for monomer; $p \leq 0.01$ for ubiquitinated) treatment after ROT exposure. As shown in Figure 4f, we observed that NI-ADSC-SM decreased the levels of Ub in the Triton X-100-insoluble fraction. The ADSC-SM was not used in Western blot to detect the Triton X-100-insoluble fraction and was shown to be less protective than the NI-ADSC-SM. ## 2.5. Effects of the NI-ADSC-SM on DJ-1 and TOM20 Protein Expression after ROT Exposure Along with PINK1 and parkin, DJ-1 has various cellular functions. DJ-1 colocalizes with Lewy bodies (LBs) and can downregulate α-syn. Moreover, oligomeric α-syn binds to TOM20, a transit peptide receptor from the OMM, to impair mitochondrial protein import. Using a time-course study, the levels of DJ-1 and TOM20 were significantly decreased by ROT toxicity at 24 and 48 h (Figure 5a). DJ-1 ($p \leq 0.001$; Figure 5b) and TOM20 ($p \leq 0.01$; Figure 5c) were significantly decreased after ROT exposure for 48 h. By contrast, the NI-ADSC-SM upregulated both DJ-1 and TOM20 in the ROT-exposed cells ($p \leq 0.001$). The ADSC-SM also increased DJ-1 ($p \leq 0.01$) and TOM20 ($p \leq 0.05$) after ROT exposure. ## 2.6. Effects of the NI-ADSC-SM on Mitochondrial Fission and Fusion Protein Expression after ROT Exposure Mitochondrial fission is the division of single mitochondria into two and is mainly controlled by DRP1 phosphorylated at Ser616 and Ser637. We found that ROT-induced neurotoxicity significantly increased the phosphorylated DRP1 Ser616 (Figure 6a,b) and decreased the phosphorylated DRP1 Ser637 (Figure 6a,c), although ROT did not modify total DRP1 (t-DRP1) levels (Figure 6). The ratios of p-DRP1 Ser616/t-DRP1 ($p \leq 0.001$; Figure 6b), p-DRP1 Ser616/β-actin ($p \leq 0.05$; Supplementary Figure S2a), p-DRP1 Ser637/t-DRP1 ($p \leq 0.001$; Figure 6c), and p-DRP1 Ser637/GAPDH ($p \leq 0.001$; Supplementary Figure S2c) were all significant. These results suggest that ROT induced the translocation of DRP1 Ser616 from the cytosol to mitochondria, possibly leading to a malfunction in mitochondrial dynamics. However, the ratio of p-DRP1 Ser616/t-DRP1 was decreased ($p \leq 0.001$; Figure 6b), and p-DRP1 Ser637/t-DRP1 was increased ($p \leq 0.01$; Figure 6c) by NI-ADSC-SM treatment. The t-DRP1 was also not changed ($p \leq 0.05$; Supplementary Figure S2b,d) by the NI-ADSC-SM in SH-SY5Y cells after exposure to ROT. Mitochondrial fusion is the union of two mitochondria into one elongated mitochondrion, which is controlled by MFN1, MFN2, and OPA1. In the time-course study, ROT decreased the levels of MFN1, MFN2, and OPA1 at different timepoints (Figure 7a). We observed a decrease in MFN1 ($p \leq 0.001$; Figure 7b), MFN2 ($p \leq 0.01$; Figure 7c), and OPA1 ($p \leq 0.001$; Figure 7d) after exposure to ROT for 48 h in SH-SY5Y cells. Treatment with the NI-ADSC-SM ($p \leq 0.001$ for all) or ADSC-SM ($p \leq 0.001$ for MFN1 and OPA1; $p \leq 0.01$ for MFN2) at the final 24 h significantly increased the levels of MFN1, MFN2, and OPA1 in the ROT-exposed cells. Treatment with the ADSC-SM also increased the OPA1 level in control SH-SY5Y cells ($p \leq 0.01$; Figure 7d). ## 2.7. Effects of the NI-ADSC-SM on Endoplasmic Reticulum Stress Protein Expression after ROT Exposure The ER is a crucial organelle involved in protein production. In this present study, ROT-induced toxicity increased the ratios of BiP/GAPDH ($p \leq 0.01$; Figure 8b), p-PERK Thr981/GAPDH ($p \leq 0.05$; Figure 8e and Supplementary Figure S3c), t-PERK/GAPDH ($p \leq 0.05$; Figure 8e and Supplementary Figure S3d), t-PERK/β-actin ($p \leq 0.05$; Figure 7d and Supplementary Figure S3b), p-IRE1α Ser724/GAPDH ($p \leq 0.01$; Figure 9b and Supplementary Figure S4a), t-IRE1α/GAPDH ($p \leq 0.01$; Figure 9b and Supplementary Figure S4b), and p-SAPK Thr183,Tyr185/GAPDH ($p \leq 0.001$; Figure 9c and Supplementary Figure S4c), while decreasing the ratios of p-PERK Thr980/t-PERK ($p \leq 0.001$; Figure 8c) and p-PERK Thr980/β-actin ($p \leq 0.001$; Supplementary Figure S3a). Treatment with NI-ADSC-SM after ROT exposure did not modify BiP levels; however, BiP increased when treated in control SH-SY5Y cells ($p \leq 0.05$; Figure 8b). NI-ADSC-SM treatment decreased the levels of p-PERK Thr981/GAPDH ($p \leq 0.05$; Supplementary Figure S3c and Figure 8d), t-PERK ($p \leq 0.05$; Supplementary Figure S3b,d), p-IRE1α Ser724 ($p \leq 0.01$; Figure 9b and Supplementary Figure S4a), t-IRE1α ($p \leq 0.01$; Figure 9b and Supplementary Figure S4b), and p-SAPK Thr183-Tyr185 ($p \leq 0.05$; Figure 9c and Supplementary Figure S4c). Treatment with the NI-ADSC-SM or ADSC-SM increased the expression of p-PERK Thr980 ($p \leq 0.001$ by NI-ADSC-SM; $p \leq 0.05$ by ADSC-SM; Figure 8c and Supplementary Figure S3a). As seen in Figure 10a, the expression of p-eIF2α at Ser51 was decreased, but the levels of ATF4 and CHOP were increased by ROT in the time-dependent toxicity study. p-eIF2α Ser51 was significantly decreased ($p \leq 0.01$; Figure 10b and Supplementary Figure S5a), while ATF4 ($p \leq 0.001$; Figure 10c) and CHOP ($p \leq 0.001$; Figure 10d) were increased by ROT after 48 h. NI-ADSC-SM treatment increased p-eIF2α Ser51 ($p \leq 0.01$; Figure 10b and Supplementary Figure S5a) and decreased ATF4 ($p \leq 0.001$; Figure 10c) and CHOP ($p \leq 0.01$; Figure 10d) after ROT exposure. Treatment with the ADSC-SM showed comparably less protective effect to ROT toxicity than the NI-ADSC-SM. Treatment with ROT, the ADSC-SM, or the NI-ADSC-SM alone or combined did not change the total levels of eIF2α in SH-SY5Y cells (Supplementary Figure S5b). ## 2.8. Effects of the NI-ADSC-SM on IP3R-GRP75-VDAC Tethering Protein Expression after ROT Exposure It is interesting to understand mitochondria, the ER, and their interactions in NDD that regulate Ca2+ transfer between these organelles. IP3R1 has been shown to be relevant to ER–mitochondria Ca2+ coupling by forming a complex with VDAC1 and GRP75. We first studied the expression of the p-IP3R at Ser1756, t-IP3R1, GRP75, and VDAC in different timepoints of ROT toxicity (Figure 11a). p-IP3R Ser1756 was decreased ($p \leq 0.001$; Figure 11b and Supplementary Figure S5c), whereas GRP75 ($p \leq 0.001$; Figure 11c) and VDAC ($p \leq 0.01$; Figure 11d) were increased by ROT toxicity in SH-SY5Y cells. ROT, the ADSC-SM, and the NI-ADSC-SM did not alter the levels of t-IP3R1 (Figure 11b and Supplementary Figure S5d). In contrast, treatments with the ADSC-SM or NI-ADSC-SM increased p-IP3R Ser1756 ($p \leq 0.001$; Figure 11b and Supplementary Figure S5c) and decreased GRP75 levels ($p \leq 0.01$; Figure 11c). ADSC-SM treatment did not modify VDAC, but the NI-ADSC-SM decreased the VDAC levels after exposure to ROT ($p \leq 0.01$; Figure 11d). ## 3. Discussion ROT easily crosses biological membranes due to its high lipophilicity and inhibits complex I, which can reproduce pathological conditions of PD-like symptoms, including aggregation of α-syn [15]. LRRK2 is a ubiquitously expressed, large homodimeric protein that acts as a hub for multiprotein signaling and participates in protein–protein interactions, cytoskeletal dynamics, mitochondrial function, and autophagy [22]. This cytoplasmic protein may associate with intracellular membranes, such as the OMM, Golgi apparatus, and ER [23]. ROT increased LRRK2 levels in the Triton X-100-soluble and -insoluble cell lysates in this study, coinciding with another study suggesting that ROT-induced LRRK2 activation leads to an overall reduction of protein translation [24]. An increase in LRRK2 can disrupt its normal physiological functions, which results in synaptic dysfunction [25], increased mitochondrial Ca2+ uptake [26], and deregulation of autophagy through lysosomal degradation [27]. NI-ADSC-SM treatment inhibited the ROT-induced increase of LRRK2 in SH-SY5Y cells in this study, which also supports that LRRK2 inhibition could prevent the loss of dopaminergic neurons [28]. Therefore, inhibiting LRRK2 is potentially beneficial in PD. Mitophagy, the selective degradation of mitochondria by autophagy, is essential for maintaining neuronal health by degrading and recycling cellular material. PINK1 is a protein kinase required to recruit parkin and Ub to damaged mitochondria to initiate mitophagy on the OMM [29,30]. In this present study, the levels of PINK1 and parkin were decreased by ROT in SH-SY5Y cells. This result suggests that the degradation of cytosolic PINK1 by the Ub–proteasome system led to low levels of PINK1 [31]. Studies also reported that the loss of PINK1 or parkin in SH-SY5Y cells induced higher mitochondrial fragmentation facilitated by DRP1 [7,32]. Loss of parkin can cause uncoupling of mitochondria and the ER and a decrease in MAM under mitophagy induction [33]. The depletion of PINK1 or parkin increases ROS-induced apoptotic cell death [34]. These results suggest that activation of mitophagy could recruit ubiquitinated substrates, such as misfolded α-syn protein aggregates, for clearance [16]. The ubiquitination of mitochondria under oxidative stress accumulates aggregation of misfolded proteins, which are recognized by the autophagic adaptor protein p62 (SQSTM1; sequestome1) and cleared through the mitophagy [35]. ROT-induced toxicity downregulated the autophagic clearance [16], suggesting that the protein aggregates may accumulate with increased levels of Ub conjugates [36]. In this present study, ROT toxicity increased the Ub (monomer and polyubiquitinated) in the Triton X-100-insoluble cell lysates; however, it decreased the Triton X-100-soluble Ub. Studies indicate that phosphorylated α-syn is ubiquitinated [37], which further enhances cellular dysfunction [38]. p-S129-α-syn was increased in the Triton X-100-insoluble fractions [15], reflecting the current results that ubiquitination attempts to target misfolded proteins for degradation. In this present study, NI-ADSC-SM treatment increased parkin and decreased insoluble Ub expression, suggesting the neuroprotective potential against ROT toxicity. The NI-ADSC-SM did not recover PINK1 levels in this study, suggesting that PINK1 has other distinct and uncharacterized functions [6]. However, overexpression of parkin was able to rescue the α-syn-induced toxicity associated with PD [39]. Several substrates of OMM proteins have been ubiquitinated by the PINK1/parkin-mediated signaling pathway [40]. DJ-1 is almost ubiquitously expressed in the brain and is present in synaptic terminals, mitochondria, and membranous organelles [41]. DJ-1 colocalizes with LBs and can downregulate α-syn by forming an E3 ligase complex with PINK1/parkin [42]. The decreased levels of DJ-1 after ROT exposure seen in this present study may be attributed to increased ROS production [43]. α-syn aggregation is promoted by the loss of DJ-1 via the increased degradation of LAMP2 [44]. A decrease in DJ-1 in MAMs alters Ca2+ transfer [33], leading to mitochondrial dysfunction [45]. ROT toxicity decreased the LAMP2 levels and increased the oligomerization of α-syn in SH-SY5Y cells. Treatment with the NI-ADSC-SM increased DJ-1 in this study. NI-ADSC-SM also increased the LAMP2 levels and decreased the α-syn oligomerization in our previous results [15,16]. Mitochondrial proteins positioned within the matrix cooperate with the TOM complex via the OMM receptor TOM20 [46]. PINK1 is imported through the TOM complex in healthy mitochondria [47], while parkin ubiquitinates multiple substrate proteins, including TOM20 [40]. In PD, p-Ser129-α-syn binds to TOM20, impairing mitochondrial function [48]. In this study, TOM20 levels were decreased by ROT, whereas the NI-ADSC-SM increased TOM20 to above-normal levels. Studies reported that oligomeric, but not monomeric, α-syn binds to TOM20 causing mitochondrial dysfunction [48]. However, increased TOM20 levels in this study may be due to the reduction of oligomeric α-syn as reported earlier [15] which imports mitochondrial precursor proteins, increasing mitochondrial function [49]. Mitochondria undergo constant fission and fusion sequentially, and these functions rely on the levels of DRP1 phosphorylation and Mfn1 and 2 and OPA1 expression [50]. DRP1 is essential for the mitochondrial distribution in axons, dendrites, and synapses. However, phosphorylation of DRP1 at Ser616 activates DRP1, which promotes translocation from the cytosol to the OMM, inducing mitochondrial division and fragmentation [51]. Phosphorylation at Ser637 of DRP1 inhibits DRP1 activity, thus preventing mitochondrial fragmentation and regulating mitochondrial morphology [52]. The interplay between Ser616 and Ser637 via the PINK1/parkin pathway can drive mitophagy [51]. In this present study, p-DRP1 Ser616 was significantly increased, while p-DRP1 Ser637 was decreased by ROT. LRRK2 overexpression increases mitochondrial fragmentation and clearance by interacting with DRP1 [53]. Moreover, we found that NI-ADSC-SM treatment could almost completely inhibit the ROT-induced increase in p-DRP1 Ser616 and activate p-DRP1 Ser637, suggesting that fragmented mitotic mitochondria can escape from apoptotic cell death via mitophagy [51]. Mitochondrial fusion is controlled by MFN1 and MFN2 localized to the OMM and OPA1 located in the IMM [8]. MFN2 was reported to tether the ER to the mitochondria by directly interacting with either MFN1 or MFN2 on the OMM [54] to regulate mitochondrial Ca2+ uptake from the ER [55]. PINK1/parkin can regulate MAMs through MFN2 [56]. OPA1 has been shown to be responsible for the fusion of the IMM associated with cristae folding and regulating the respiratory chain supercomplex assembly [57]. Depletion of OPA1 during apoptosis causes mitochondrial fragmentation and modifies the shape of the cristae [58]. In this present study, the low levels of MFN1, MFN2, and OPA1 during ROT-induced toxicity suggest that mitochondrial fusion is repressed, leading to the marked accumulation of damaged mitochondria. Abnormally high mitochondrial fission induces ROS production to activate PINK/parkin-dependent mitophagy [59], uncoupling the mitochondria from the ER via the degradation of MFN2 [6]. Lowered MFN2 levels decreased the distance between the ER and OMM to impair Ca2+ uptake into the mitochondria [60]. These results suggest that ROT toxicity promotes mitochondrial fission while inhibiting mitochondrial fusion in SH-SY5Y cells. As expected, NI-ADSC-SM treatment increased these fusion proteins after exposure to ROT is likely sufficient to rescue mitochondrial dysfunction-associated pathologies. The ER controls posttranslational protein processing and transport; however, the accumulation of misfolded proteins is upregulated during ER dysfunction [61]. PERK, IRE1α, and ATF6 are associated with BiP/GRP78 in normal conditions but are released during ERS, triggering the unfolded protein response (UPR) [62] to recover protein homeostasis or induce apoptosis [63]. In this present study, BiP, p-Thr981 PERK, t-PERK, p-IRE1α, and t-IRE1α were increased, while p-Thr980 PERK was decreased during ROT toxicity. These results showed that ROT-induced ERS led to the disassociation of BiP from the luminal domains of both PERK and IRE1α, enabling auto-phosphorylation [64]. Accumulation of unfolded proteins activates IRE1α at Ser724, leading to apoptosis through stress-activated protein kinase (SAPK; c-Jun N-terminal kinase; JNK) signaling during ERS [11]. A rapid increase in p-SAPK at Thr183/Tyr185 upon ROT toxicity amplifies ERS subsequently activates pro-apoptotic cell death. Activated SAPK enters the nucleus and promotes cell death associated with CHOP transcription [65]. However, the NI-ADSC-SM reverted the changes on PERK, IRE1α, and SAPK induced by ROT. In addition, the NI-ADSC-SM did not change BiP levels after exposure to ROT, and NI-ADSC-SM-treated control cells showed increased BiP levels in this study. Another study showed that BiP was increased to protect cells from oxidative stress. Thus, BiP can momentarily bind to hydrophobic residues on proteins to refold or prevent aggregation [66]. PERK activation blocks the entrance of synthesized proteins into the ER [67], thus inactivating the global protein translation initiation key target eIF2α, which causes the destruction of protein translation and dropping of ER protein load [68]. In this present study, ROT decreased p-Ser51 eIF2α levels, while the NI-ADSC-SM increased them in SH-SY5Y cells. Dephosphorylation of eIF2α by ROT may halt protein synthesis [69]. We suggest that increased p-eIF2α by the NI-ADSC-SM may upregulate basal autophagy, antioxidant responses, and amino acid metabolism in the UPR [63]. These results coincide with other studies suggesting that p-eIF2α may be protective [70,71]. These protective responses result in enhanced protein degradation and subsequently increase the ER protein folding capacity [61]. Induction of the transcription factors ATF4 and CHOP by ERS is dependent on PERK [72] and is also evidenced in this study during ROT toxicity. When the UPR pathway is compromised and can no longer restore ER homeostasis, PERK induces CHOP to stimulate ERS-dependent cell death [73]. ATF4 also controls the expression of pro-apoptotic CHOP [74]. ATF4 expression in the axon triggers a cascade [75]. CHOP-promoted cell death in PD has been linked to increased ROS and decreased Bcl-2 [2]. ERS includes the release of Ca2+ from ER stores and the physical interaction of the ER and mitochondria [76]. Ca2+ is required inside the mitochondria for the production of ATP. ER–mitochondria tethering regulates Ca2+ homeostasis, lipid transfer, mitochondrial dynamics, and autophagy [29]. LRRK2 mutations have been linked to impaired autophagic regulation through altered ER and lysosomal Ca2+ signaling pathways [77]. Ca2+ exchange between the ER and mitochondria [13] is mediated by a molecular tripartite tethering complex, IP3R-GRP75-VDAC [14], in the MAM. IP3R, responsible for Ca2+ release from the ER, interacts with VDAC1 at the OMM via a chaperone, GRP75 [29]. In this present study, ROT-induced toxicity decreased the p-Ser1756 IP3R while increasing the levels of GRP75 and VDAC. ROT also disrupts intracellular Ca2+ homeostasis [61]. IP3R plays important roles in protecting cells against apoptosis [54], and high Ca2+ concentrations can inhibit IP3R [78] function, leading to apoptosis by depressing the mitochondrial membrane potential [79]. Loss of IP3R activity activates AMP-activated protein kinase (AMPK), which in turn inhibits mammalian target of rapamycin (mTOR) signaling [80], which was also reported in our previous publication [16]. Impaired tethering of the ER and mitochondria can be mediated by altered proteins involved in MAMs. Upregulated GRP75 and VDAC expression is crucial for the increased Ca2+ load, leading to mitochondrial dysfunction in neurons [81] and a higher susceptibility for cell death [54]. In addition, PD-associated α-syn mutations decrease ER–mitochondria connections [82]. NI-ADSC-SM treatment increased p-Ser1756 IP3R and inhibited the expression of GRP75 and VDAC during ROT toxicity. The increased anti-apoptotic protein Bcl-2 upregulates the phosphorylation of IP3R and lowers pro-apoptotic ER–mitochondrial Ca2+ fluxes [83], suggesting that IP3R is central for tethering mitochondria close to the ER [84]. ## 4.1. Secretome-Containing Culture Medium Collection from Primary ADSCs and Neural-Induced ADSCs Adipose tissues from human donors were attained according to the Ethics Committee of Chonnam National University Medical School (IRB: I-2009-03-016). Primary ADSCs were isolated, and adherent cells were grown at 37 °C in a humidified incubator ($5\%$ CO2/$95\%$ air) with Dulbecco’s modified Eagle’s medium (DMEM; Hyclone, Logan, UT, USA) containing $10\%$ fetal bovine serum (FBS, Hyclone), $1\%$ penicillin–streptomycin (Gibco BRL, Grand Island, NY, USA), and $0.2\%$ amphotericin B (Gibco). Approximately $80\%$ confluence of the primary ADSCs (passages 3–5) were maintained in DMEM supplemented with reduced FBS at $1\%$ for seven days. The secretome-containing culture medium from primary ADSCs (ADSC-SM) was collected, pooled, filtered with a sterile 0.2 μm syringe filter, and kept at −80 °C until used for treatment. For the neural-induced secretome, primary ADSCs (passages 3–5) cultured in DMEM supplemented with $1\%$ FBS were supplemented with 100 ng/mL bFGF (Invitrogen Co., Carlsbad, CA, USA) for the first seven days and further incubated for another seven days with 10 μM forskolin (Sigma Chemical Co., St. Louis, MO, USA) as per our previous studies [19,20,21]. The neural-induced secretome-containing culture medium (NI-ADSC-SM) was collected without NI-ADSCs, pooled, filtered using a sterile 0.2 μm syringe filter, and kept at −80 °C until used for treatment. Several batches of the ADSC-SM and NI-ADSC-SM were collected from multiple cell cultures and neural induction for the consequent experiments. ## 4.2. Cell Culture The human neuroblastoma cell line SH-SY5Y (RRID: CVCL_0019; ATCC® CRL-2266; American Type Culture Collection, Manassas, VA, USA) was cultured with $10\%$ FBS and $1\%$ penicillin–streptomycin supplemented DMEM (Welgene Inc., Gyeongsan, Republic of Korea) at 37 °C in a humidified incubator containing $5\%$ CO2/$95\%$ air. Confluent cultures from passages 15–22 were used for experiments. Briefly, cultured cells were rinsed with phosphate-buffered saline (PBS), dissociated with $0.25\%$ trypsin–EDTA solution, then reseeded at an equal density of 50,000 cells/mL in DMEM with $1\%$ FBS, and kept for overnight before being used for the experiments. ## 4.3. Rotenone Preparation A ROT (R8875, Sigma) stock solution at 10 mM in a polar aprotic solvent, dimethyl sulfoxide (DMSO; D2650, Sigma), was aliquoted and kept at −80 °C and used for experiments within six months. A ROT working solution (250 μM) was prepared with DMEM (without FBS) for each experiment. The remaining working solution diluted from the stock solution was discarded. ## 4.4. ROT Toxicity and ADSC-SM and NI-ADSC-SM Treatments Time-dependent effects of ROT (0.5 μM)-induced toxicity on SH-SY5Y cells were assessed to characterize the protein signaling pathway changes (Supplementary Figure S1a). SH-SY5Y cells were incubated for 24 h in the presence of 0.5 μM ROT or DMSO (control). The cell culture medium was collected with floating cells, centrifuged at 3000 rpm for three minutes, and the supernatant was discarded. The pelleted cells were resuspended in a fresh medium and added to their respective culture plate. Either the ADSC-SM or NI-ADSC-SM (each diluted at $50\%$ in DMEM with $1\%$ FBS) was added, and the cells were incubated in the presence of 0.5 μM ROT or DMSO for another 24 h (Supplementary Figure S1b). FBS at $1\%$ was maintained throughout the study. Several sets of experiments were performed with different passages of SH-SY5Y cells treated with multiple sets of the ADSC-SM or NI-ADSC-SM against ROT-induced toxicity. ## 4.5. Estimation of Intracellular Calcium (Ca2+) by Fura-2AM Fura-2AM (1 mM; F-1221, Molecular Probes, Carlsbad, CA, USA) was added and incubated for one hour at 37 °C in a dark incubator. The fura-2AM-containing cell culture medium was then removed, the cells were washed twice with fresh DMEM (without FBS), and a suspension was prepared. Fluorescence was measured using a SpectraMax M2 fluorescence spectrometer (Molecular Devices, Sunnyvale, CA, USA) by SoftMax Pro 5.4.6 software (Molecular Devices) with excitations at 320 nm and 355 nm and emission at 538 nm. The levels of Ca2+ were calculated by the ratio of $\frac{320}{355}$ nm excitation and expressed as a percentage of the control. The assay was performed in triplicate. ## 4.6. Preparation of Triton X-100-Soluble and -Insoluble Fractions and Western Blotting Detached and adherent cells were collected by scraping and centrifugation before being washed with PBS. Then, the cells were immersed with Triton X-100-soluble cell lysis buffer consisting of rapid immunoprecipitation assay (RIPA) buffer (#89901, Thermo Scientific, Rockford, IL, USA), Halt protease inhibitor cocktail (#87789, Thermo Scientific), Halt phosphatase inhibitor cocktail (#78420, Thermo Scientific), and $1\%$ Triton X-100 (X100, Sigma). The cells were incubated for 30 min on ice at 8 °C. Thereafter, the lysates were centrifuged at 13,200 rpm (16,000× g) for 20 min at 4 °C, and the cell lysate supernatants (Triton X-100-soluble fractions) were collected. The remaining cell pellets were washed with PBS, dissolved in a Triton X-100-insoluble cell lysis buffer consisting of $2\%$ sodium dodecyl sulfate (SDS, L3771, Sigma) and Triton X-100-soluble cell lysis buffer, and sonicated for one minute on ice at intervals of 10 s (Triton X-100-insoluble fractions). The BCA Protein Assay Kit (#23225, Thermo Scientific) was used to estimate the protein levels, and equal amounts (10 μg) were loaded on 5–$12\%$ SDS–polyacrylamide gels. The proteins were separated according to their molecular weight in the gels and were transferred onto polyvinylidene difluoride (PVDF) membranes (IPVH00010, Millipore, Bradford, MA, USA). The membranes were blocked with $5\%$ nonfat dried milk or $1\%$ bovine serum albumin (BSA) dissolved in the washing buffer (TBS-T; Tris-buffered saline, pH 7.6 containing $0.1\%$ Tween 20). The membranes were then incubated with primary and secondary antibodies. The antibodies used (acquired from Abcam, Cambridge, MA, USA; Biorbyt, Cambridge, UK; Cell Signaling Technology Inc., Danvers, MA, USA; and Santa Cruz Biotechnology, Santa Cruz, CA, USA) are listed in Supplementary Table S1. Lastly, the bands were visualized by an enhanced chemiluminescence (ECL) system (WBLUR0500, Millipore, Billerica, MA, USA) and a luminescent image analyzer (LAS 4000, GE Healthcare, Little Chalfont, UK). After imaging the phosphorylated proteins, the membranes were stripped with Western Blot Stripping Buffer (#21059, Thermo Scientific) and subsequently used to detect total protein forms. β-actin or GAPDH were used to normalize the target protein levels. Phospho-protein signals were normalized against the total (non-phosphorylated) forms of the same target protein. ImageJ software (National Institutes of Health, Bethesda, MD, USA) was used for densitometric analysis. ## 4.7. Statistical Analysis Data are shown as the mean ± standard error of the mean (SEM) of three independent cell culture experiments. Microsoft Excel and GraphPad Prism® 5.0 software (GraphPad Software Inc., San Diego, CA, USA) were used for data processing, analyzing statistical comparisons, and preparing the bar charts. One-way analysis of variance (ANOVA) followed by Tukey’s post hoc multiple-comparison tests were performed, and p-values of less than 0.05 were considered statistically significant for toxicity or treatment groups. ## 5. Conclusions ROT-induced toxicity in SH-SY5Y cells resulted in impaired cellular homeostasis of mitochondria, the ER, and MAM tethering proteins. Additionally, increased cell-death-associated Ca2+ is crucial for understanding the pathogenesis of PD. Increased LRRK2 disrupts PINK1/parkin-dependent mitophagy, and mitochondrial fusion target increased mitochondrial fission. In addition, misfolded proteins during ERS induced by ROT toxicity triggered the release of PERK and IRE1α from BiP, promoting the activation of ATF4, CHOP, and SAPK. Increased expression of GRP75 and VDAC may be accompanied by mitochondrial Ca2+ overload and reduced IP3R tethering between the ER and mitochondria. NI-ADSC-SM treatment attenuated the ROT-induced dysfunction in mitochondria and the ER. Taken together, our findings may help uncover the molecular mechanisms of ROT-induced neurotoxicity contributing to the signaling pathways of mitochondria, the ER, and their interaction in NDD (Figure 12). Therefore, the “secretome” released during neural differentiation from MSCs into the conditioned medium may have a vital role in treating NDDs. Thus, the NI-ADSC-SM is suggested to have therapeutic potential through the various biological molecules released during neural differentiation and may be sufficient to rescue pathologies in PD. ## References 1. 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--- title: 'Premature Pubarche: Time to Revise the Diagnostic Approach?' authors: - Federico Baronio - Alice Marzatico - Rosaria De Iasio - Rita Ortolano - Antonio Fanolla - Giorgio Radetti - Antonio Balsamo - Andrea Pession - Alessandra Cassio journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054674 doi: 10.3390/jcm12062187 license: CC BY 4.0 --- # Premature Pubarche: Time to Revise the Diagnostic Approach? ## Abstract Premature pubarche (PP) could represent the first manifestation of non-classic congenital adrenal hyperplasia caused by 21 hydroxylase deficiency (NC21OHD) (10–$30\%$ of cases). In the last 20 years, the necessity of performing an ACTH test to diagnose NC21OHD in all cases with PP has been questioned, with conflicting results. This study aims to retrospectively evaluate the predictive value of the basal androgens, 17-OHP levels, and auxological features in suggesting the presence of NC21OHD and, thus, the need for a standard ACTH test to confirm the diagnosis. In all, 111 consecutive patients (87 females) with PP and advanced bone age underwent an ACTH test. Of these, $\frac{6}{111}$ cases (1 male) were diagnosed with NC21OHD. The mean baseline 17 hydroxyprogesterone (17-OHP), dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEA-S), delta 4 androstenedione (Δ4A), and testosterone serum levels were higher in NC21OHD patients than in the others ($p \leq 0.05$). We found three predictive features for NC21OHD: basal 17 OHP of >200 ng/mL, bone age advance of >2 years, and DHEA-S levels of >228 ng/mL with sensitivity and specificity of $83.3\%$ and $97.1\%$, $83.3\%$ and $65.7\%$, and $83.3\%$ and $96.2\%$, respectively. Our data confirm that the prevalence of NC21OHD is low among patients with PP. Serum 17-OHP of >200 ng/mL could be helpful to decide, in most cases, which patients should undergo the ACTH test. Bone age advance represented an inadequately specific predictive marker of NC21OHD. ## 1. Introduction Adrenarche is a physiological condition that usually occurs after five years of age due to the maturation of the adrenal cortex (zona reticularis): it is characterized by the rising of adrenal androgens dehydroepiandrosterone (DHEA) and DHEA sulfate (DHEA-S) [1]. The clinical manifestation of adrenarche is called pubarche, which consists of the appearance of pubic hair, axillary hair, adult body odor, and acne. Pubarche is considered premature if it appears before the age of eight years in girls and nine years in boys. In 70–$90\%$ of cases, premature pubarche (PP) simply represents an anticipation of the prepubertal physiologic adrenarche; in this case, it is called idiopathic premature pubarche or premature adrenarche (PA), and it is characterized by the elevation of serum DHEA-S from 1.08 μMol/L (40 μg/dL) to 3.5 μMol/l (130 μg/dL) [1]. Premature pubarche could also be a manifestation of an increased sensitivity of the hair follicle to normal androgen levels, and in this case, it is generally called “isolated premature pubarche” (IPP) [2]. In patients with PA or IPP, stature, bone age, and growth velocity are not affected; however, some cases show significant bone age advancement and growth acceleration [3,4,5,6]. In the other 10–$30\%$ of cases, PP is the first manifestation of non-classic congenital adrenal hyperplasia due to mild 21 hydroxylase deficiency (NC21OHD), an autosomal recessive genetic condition due to homozygous or compound heterozygous variants on CYP21A2. The biochemical marker of the disease is represented by adrenal hyperandrogenism with increased levels of 17 hydroxyprogesterone (17-OHP) and delta 4 androstenedione (Δ4A) [7]. NC21OHD, if left untreated, leads to accelerated growth velocity, early puberty, reduced adult height, irregular menses, hirsutism, and acne later in adolescence and adulthood [8,9]. The measurement of serum androgens and 17-OHP by the 250 μg Synachten test (standard ACTH test) has been classically utilized to discriminate children with NC21OHD among cases with premature pubarche. The diagnosis of NC21OHD is made by plotting the stimulated 17-OHP levels against the basal values in the nomogram created by New et al. [ 10]; stimulated 17-OHP above 30 nmol/l (1000 ng/dL) has $100\%$ diagnostic sensitivity and specificity [8,10,11,12,13,14]. Final diagnostic confirmation of NC21OHD should be made by molecular analysis of CYP21A2. Although in clinical practice, in patients with PP, the standard ACTH test is still often performed, it is also well known that in a large proportion of cases, its use is “unnecessary”, as up to $80\%$ of patients with PP are not affected by NC21OHD [15]. The test’s continued use mainly depends on the difficulty of finding predictive clinical markers of NC21OHD, which many authors have researched in the last decades, with conflicting results. Due to these uncertainties, even now, in our Centre, the clinical and laboratory management of children with PP is cautious and well-consolidated. Once a rapid and severe progression of hyperandrogenism has been excluded by clinical and anamnestic evaluation, for which specific investigation is promptly started, the patient undergoes a hand X-ray: if their bone age is at least one year ahead of their chronological age, the patient undergoes a standard ACTH test to exclude NC21OHD. This study aims to retrospectively evaluate the predictive value of the basal androgens, 17-OHP levels, and auxological features in suggesting the presence of NC21OHD and, thus, the need for a standard ACTH test to confirm the diagnosis. ## 2. Materials and Methods We evaluated clinical, radiological, and laboratory data of all children who were referred to our Centre between January 2017 and July 2020 who, according to the diagnostic protocol of the Centre, underwent standard ACTH testing for premature pubarche associated with advanced bone age of at least one year with respect to chronological age. We collected information about perinatal history (gestational age, neonatal weight) and auxological parameters at the first clinical evaluation. Height was measured by using a Harpenden stadiometer (Holtain Ltd., Crymych, UK; accuracy of 0.1 cm), weight was measured by using a steelyard scale (with an accuracy of 0.1 kg), and BMI was calculated by the formula (weight (kg)/height2 (m)); anthropometric parameters (height, weight, BMI) were normalized by age and sex according to the Italian standards of Cacciari et al. [ 16] and expressed as the standard deviation score (SDS); and clinical data about hyperandrogenism (age at pubarche onset as reported by the patient or her/his parents) and pubertal development (Tanner stage of pubic and axillary hair, testicular volume in males by Prader orchidometer, and breast button in females) were recorded. The patients born with body weight or length below −2 SDS were defined as small for gestational age (SGA). The standard ACTH test (250 mg of Synachten i.v.) with a measurement of baseline and 60 min serum 17-OHP was performed in all cases to exclude NC21OHD due to 21 hydroxylase deficiency [17,18]. During the standard ACTH test, the baseline and after-stimulus levels of the following androgens other than cortisol and 17-OHP are usually measured at our Center: DHEA, DHEA-S, and Δ4A. The level of Δ4A was evaluated using an immunochemiluminescence (CLIA) commercial kit Immulite 2000-XPi, while DHEA-S was assessed using the immunochemiluminescence (CLIA) method via Access DXI 800 (Beckman Coulter® Brea, California, USA). DHEA and 17-OHP were assessed using radioimmunological assay kits DSL-9000 and kit DSL-5000, respectively. Basal testosterone levels were also evaluated using the immunochemiluminescence (CLIA) method via Access DXI 800 (Beckman Coulter® Brea, California, USA). Bone age (BA) was estimated by hand X-ray utilizing the method of Greulich and Pyle by experienced pediatric radiologists at our Centre [19]. ACTH-stimulated 17-OHP of >30 nmol/l (1000 ng/dL) was considered to be diagnostic for NC21OHD [11]; otherwise, those with basal serum DHEA-S levels of >40 mcg/dL were considered affected by premature adrenarche (PA), and others without PA or NC21OHD were labeled as idiopathic premature pubarche (IPP) [10,20,21]. All patients with stimulated 17-OHP of >30 nmol/l (1000 ng/dL) underwent diagnostic confirmation by mutational analysis of the CYP21A2 gene. ## Statistical Analysis To explore the data, preliminary analyses were performed. Continuous data are presented as the mean (SD) or with $95\%$ CIs. Mean values were tested for statistical significance using 2-tailed t-tests. Pearson correlation coefficients were calculated to assess the relationship between test indexes. ANOVA analysis was performed to compare group means for each test index, and the Bonferroni test was used for multiple comparisons. Receiver operating characteristic (ROC) curves were then generated to obtain the values of the area under the curve (AUC) with $95\%$ CIs, sensitivity, and specificity. In addition, the likelihood ratio (LR+ and LR-) and positive and negative predictive values (+PV and -PV, respectively) were also examined. Adjusted ROC analysis using clinical cut-points was performed to identify the best predictor for each index. To determine the optimal cut-off, the Youden index was calculated. The significance threshold was set at $p \leq 0.05.$ *The data* were analyzed using SAS Enterprise Guide 4.3 (SAS Institute Inc., Cary, NC, USA). ## 3. Results During the study period, 111 children underwent standard ACTH tests for premature adrenarche associated with advanced bone age: 87 ($78.4\%$) were female, and 24 ($21.6\%$) were male. Five out of the eighty-seven females were already on therapy with GnRH analogue for early central puberty at the time of the ACTH test. The clinical data of the patients are reported in Table 1. At the time of the ACTH test, the most frequently encountered symptom was pubic hair (84 patients, $75.6\%$), followed by axillarche (45 patients, $40.5\%$) and adult body odor (37 patients, $33.3\%$), variably associated. ## 3.1. Adrenal Steroid Evaluation Patients were subdivided into three groups: $\frac{15}{111}$ cases (2 males) were defined as affected by IPP (Group 1); $\frac{90}{111}$ cases (21 males) were diagnosed with PA (Group 2); and $\frac{6}{111}$ cases (1 male) were diagnosed with NC21OHD (Group 3) (Table 2). The mean baseline 17-OHP, Δ4A, testosterone, DHEA, and DHEA-S serum levels were significantly higher in Group 3 than in Groups 1 and 2 ($p \leq 0.05$), and baseline testosterone was also significantly higher in Group 2 than in Group 1 ($p \leq 0.05$) (Table 2). ## 3.2. Anthropometric Parameters and Bone Age The anthropometric features evaluated (height SDS, weight SDS, BMI SDS, age at pubarche onset) and mean delta BA-CA did not significantly differ among Groups 1–3. Patients with IPP underwent standard ACTH tests significantly earlier than the others (Table 2). To evaluate whether the severity of bone age advancement correlates with basal androgen and 17-OHP levels, the patients were subdivided into three groups: group A, $\frac{59}{111}$ patients ($53\%$) with BA-CA of 1 to 2 years; group B, $\frac{41}{111}$ patients ($37\%$) with BA-CA of 2 to 3 years; and group C, $\frac{11}{111}$ patients ($10\%$) with BA-CA of ≥3 years. The mean baseline 17-OHP, Δ4A, and DHEA-S were significantly higher in patients of group C than in those of groups A and B, whereas mean baseline testosterone was higher in patients of group C than in those of group A ($p \leq 0.05$) (Table 3). Five out of six patients ($83\%$) with NC21OHD at the time of the ACTH test showed bone age advancement of more than two years. ## 3.3. Puberty None of the subjects showed clinical signs of pubertal development (enlarged testicular volume of >4 mL or Tanner stage B2), except for five patients who were on GnRH analogue at the time of ACTH test. Three out of these five patients turned out to also be affected by NC21OHD. One showed basal 17 OHP of 112 ng/mL with a bone age advance of 1.4 years. ## 3.4. NC21OHD Patients The clinical features of the NC21OHD patients are reported in Table 4. The diagnosis of NC21OHD was confirmed in these patients by mutational analysis of the CYP21A2 gene. ## 4. Statistical Correlations Basal 17-OHP, Δ4A, testosterone, and DHEA-S strongly correlated with each other and with stimulated 17-OHP levels. Bone age advance (BA-CA) positively correlated with basal 17-OHP, Δ4A, testosterone, and stimulated 17-OHP. When patients with basal 17-OHP serum levels of >1000 ng/mL were excluded from the analysis (Pearson’s analysis), basal Δ4A positively correlated with other basal hormone levels (17-OHP, DHEA, DHEA-S, testosterone), testosterone positively correlated significantly with basal Δ4A and DHEA-S, and only basal 17 OHP and Δ4A positively correlated with stimulated 17-OHP levels. Bone advance (BA-CA) did not correlate with basal or stimulated 17-OHP and androgens. In Table 5, the sensitivity, specificity, negative likelihood ratio (NLR), positive likelihood ratio (PLR), negative predictive value (NPV), and positive predictive value (PPV) of basal and stimulated 17-OHP, basal Δ4A, DHEA-S, testosterone, and bone age advance (BA-CA) are reported. Figure 1 reports the ROC curve and AUC for basal 17-OHP. In our analysis, we also found a cut-off for DHEA-S of 228 ng/dL with $83\%$ sensitivity and $96\%$ specificity (AUC 0.9) and another for bone advance of ≥2 years with $83\%$ sensitivity and $66\%$ specificity (AUC 0.7) in predicting NC21OHD. The positive and negative predictive values of the DHEA-S basal threshold were 55.6 and $99\%$, respectively, while for bone age advance, they were 12.2 and $98.6\%$, respectively. The AUC did not show any statistical differences. For basal 17-OHP, DHEA-S (Figure 2 and Figure 3), and testosterone, it was not possible to find a threshold with $100\%$ specificity and sensitivity due to the presence of hormonal overlap between NC21OHD and PA patients. ## 5. Discussion In our cohort, the prevalence of NC21OHD was low ($5.4\%$ of cases), with a large proportion of cases showing PA ($81\%$) or IPP ($13.6\%$). Our results confirm that, a posteriori, the ACTH test was unnecessary in more than $90\%$ of cases. These results are in line with several research papers published in the last 20 years [7,15,20,21]. To reduce the use of this time-consuming, stressful, and expensive procedure, it seems reasonable to follow the more recent CAH guidelines [17], which indicate that it is possible to exclude or diagnose NC21OHD without performing an ACTH test for 17-OHP levels of <200 ng/mL and >1000 ng/mL, respectively. The same guidelines suggest performing ACTH testing in cases with intermediate basal 17-OHP levels (200–1000 ng/dL) [17]. We agree that in a large proportion of our patients with premature pubarche, basal 17-OHP of <200 ng/mL could have been sufficiently accurate to exclude, per se, the diagnosis of NC21OHD [15,21]. In our series, a basal 17-OHP level of <200 ng/dL represented a threshold with $99\%$ negative predictive value. However, we must underline that in one NC21OHD case, baseline 17-OHP serum levels were 112 ng/dL; therefore, without the ACTH test, we would have missed the diagnosis. In this case, the early pubertal onset associated with elevated DHEA-S serum levels represented two significant clinical and biochemical findings useful to support the decision to perform the standard ACTH test. In agreement with other authors, we did not find any other secure biochemical predictors of NC21OHD [22]. A DHEA-S threshold of 228 ng/dL showed good sensitivity and specificity but low predictive positive value and evident overlap between NC21OHD and other patients. Moreover, we could not find a significant difference between NC21OHD patients and the others with PP with regard to height SDS, BMI SDS, or the onset of symptoms. This is in accordance with other authors, such as Armengaud et al., who found no clinical feature predictive of NC21OHD among cases with PP apart from slight overweight [15]. This is partially in contrast with Bizzarri et al., who found that patients with NC21OHD were thinner, with an earlier onset of symptoms compared to the other cases with precocious pubarche [23]. These findings are probably due to differences in cohort size or local cultural and environmental factors. NC21OHD should be investigated in case of early puberty associated with PP due to the high frequency of diagnoses in this group (three cases out of five). We are not surprised by these results because sustained hyperandrogenism can lead to maturation of the hypothalamus–pituitary–gonadal axis in prepubertal children, as reported by Neeman et al., who showed a significant prevalence of central precocious puberty ($4.8\%$) in a ten-year cohort of 147 girls with NC21OHD [24]. In our Centre, bone age evaluation is often performed as the first examination test in patients with PP as the first step in the diagnostic workup. Nearly all our cases with NC21OHD showed significantly advanced bone maturation (mean BA-CA, 2.7 years; range, 1.4–3.4). Bone age advance of >2 years is a sensitive feature ($83\%$) but with relatively low specificity ($67\%$). As reported by other authors, bone advance in PP could be considered a common and benign occurrence in most cases and should not prompt, per se, an invasive diagnostic workup [4]. ## 6. Conclusions Our data confirm the low prevalence of NC21OHD in patients with PP and the difficulty of finding effective clinical predictive markers of the disease. A 17-OHP basal threshold of 200 ng/mL could be considered a safe and helpful cut-off for clinicians to decide which patients should undergo the ACTH test. Bone age advance represented an inadequately specific predictive marker of NC21OHD in our PP patients. Early central puberty associated with PP should be considered a robust clinical suggestion to exclude NC21OHD carefully. 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--- title: Changes in Diet and Physical Activity among 18–65-Year-Olds after the First National COVID-19 Lockdown in Denmark authors: - Jeppe Matthiessen - Anja Biltoft-Jensen - Anders Stockmarr - Sisse Fagt - Tue Christensen journal: Nutrients year: 2023 pmcid: PMC10054679 doi: 10.3390/nu15061480 license: CC BY 4.0 --- # Changes in Diet and Physical Activity among 18–65-Year-Olds after the First National COVID-19 Lockdown in Denmark ## Abstract COVID-19 lockdowns affected everyday life significantly and made it challenging to achieve or maintain a healthy lifestyle. The aim of the present study was to examine longitudinal changes in Danish adults’ eating habits and physical activity (PA) assessed during and after the first national lockdown in 2020. Furthermore, changes in body weight were examined during the first lockdown period. The whole diet (semi-quantitative Food Frequency Questionnaire), sociodemographic factors, moderate-to-vigorous intensity PA (MVPA), leisure screen time, anthropometrics, change in body weight, and stress level were assessed with a self-administered web-based questionnaire among 839 18–65-year-old Danes during and 5–6 months after the lockdown. Both favorable (decreased intake of saturated fat) and unfavorable (decreased intake of whole grain and fish, and increased intake of red meat) changes were found in the diet after the lockdown, while favorable changes in MVPA (increase in couples) and leisure screen time (decrease with a combined effect of family status and education) were found for PA. More Danish adults reported to gain weight (mean 3.0 kg) than to lose weight (mean 3.5 kg) during the first lockdown period ($27\%$ vs. $15\%$). The study showed favorable changes in PA and mixed results regarding diet among Danish adults after the lockdown. Furthermore, the first lockdown period unfavorably impacted the body weight of many Danes. ## 1. Introduction The COVID-19 pandemic is a serious infectious outbreak globally and has so far (7 December 2022) caused 642 million confirmed cases of SARS-CoV-2 and more than 6.6 million deaths [1]. In Europe, 266 million cases and 2.1 million deaths have been confirmed (7 December 2022). As one of the European countries, Denmark implemented several restrictions in the spring of 2020 to prevent spread of the COVID-19. One key restriction was a national lockdown from 11 March to 14 April 2020 that changed everyday life significantly and made it challenging to achieve or maintain a healthy lifestyle. With the lockdown, followed closure of workspaces, day care centers, schools, universities, gyms and sports venues, shopping centers, and restaurants, a ban on social events with more than 10 people, and travel restrictions (Supplementary Materials: Outbreak management of COVID-19). This implied that many Danes had to work from home or were sent home without work, including parental teaching and day-caring for younger children, online education for school children and students, less shopping, social gatherings, and dining out. Despite the restrictions, Danes were allowed to be outdoors and to do grocery shopping during the lockdown period. After the lockdown, restrictions were eased in Denmark to better maintain everyday life with work, education, restaurant visits, leisure time activities, etc. In September–October 2020, up to 50 people were allowed to assemble: restaurants, bars, and cafes were open to 22:00 and conducting smaller social events and private gatherings was allowed. Still, employees were encouraged to work from home and social events in workplaces, schools, leisure-time activities, etc., were cancelled. Even if restrictions such as national lockdowns, social distancing, and isolation might have been successful to prevent the spread of the COVID-19, these efforts seem to have unintended consequences and may have affected people’s eating habits, physical activity (PA), and body weight unfavorably. It may have also worsened public health and the obesity epidemic in the general population [2,3,4,5]. A Norwegian study reported on more emotional eating of sugar-rich food and drinks among those with COVID-19-related worries and psychological distress [6]. These findings are supported by data from Denmark, where higher intakes of sweet food and drinks were found during the lockdown [7,8,9]. A review showed a decrease in PA level and an increase in sedentary behavior during the COVID-19 lockdowns [3]. A global survey on PA found a $27\%$ reduction in daily step counts after COVID-19 was declared a global pandemic on 11 March 2020 [10]. Several Danish as well as international COVID-19 studies have been published examining changes in selected eating habits and PA during the lockdown compared to before [7,11,12,13,14,15]. A few studies have also assessed the whole diet and PA [16,17,18]. The authors are not familiar with other studies that have assessed changes in the whole diet and PA during and after a national lockdown in the general adult population; thereby, exploring the impact of the lockdown on behavioral changes in diet and PA onwards when restrictions were eased. The purpose of this study was to examine the effect of the COVID-19 pandemic on Danish adults’ eating habits and PA by collecting data during the first national lockdown (March–April 2020) and again at a follow-up five to six months after, when restrictions were eased (September–October 2020), to compare diet and PA between the two periods in the first year of the pandemic. Our main aim was to examine:Longitudinal changes in Danish adults’ eating habits and PA assessed during and after the first national lockdown in the same study population. Sociodemographic characteristics and weight status of those with changed eating habits and PA after the lockdown. Changes in body weight during the lockdown period and how these changes were associated with diet, PA, and stress level. Results from this study can provide new knowledge about how the extent of restrictions during the COVID-19 pandemic have affected eating habits and PA in the general adult population. These data may help to inform public health authorities and be valuable when planning future outbreak management of infectious diseases, so restrictions may go hand in hand with public health prevention. Promotion of the benefits of achieving or maintaining healthy and balanced eating habits and regular PA to strengthen health, wellbeing, and stress management in the general population is crucial in the prevention of infectious diseases such as COVID-19 [19,20,21,22]. Regular moderate-to-vigorous intensity PA (MVPA) strengthens the immune system and is associated with a reduced risk of at least $30\%$ of infectious diseases and mortality and increases the potency of vaccination [23]. Studies from the US and Korea showed that meeting PA guidelines reduces the risk for severe COVID-19 outcomes such as hospitalization, illness, and death significantly [24,25]. Maintaining an optimal nutritional status was also documented as important for the health of the immune system. Intake levels of micronutrients such as vitamin D, C, B12, and iron are inversely associated with higher COVID-19 incidence and mortality [26]. ## 2.1. Study Design and Population The study was conducted longitudinally and included assessment of the whole diet and questions about sociodemographics, PA, screen time, anthropometrics, and stress level during and after the first national lockdown in Denmark. Furthermore, changes in body weight were assessed during the first lockdown period (March to May 2020). Two online panel surveys were conducted by the consumer agency YouGov during and after the first COVID-19 lockdown in 2020. The first survey was conducted in the spring of 2020 (3–8 April) and the second in the fall of 2020 (16 September to 1 October). We chose to reassess participants in September 2020 because restrictions were eased in Denmark, and at the time, it was uncertain if previous or new restrictions would be reinstated. Moreover, we were concerned about the loss of web-panelists, making it difficult to reassess diet and PA in the same participants a long time after the lockdown. Other studies showed a significant loss of the initial sample by repeated data collection during the COVID-19 pandemic [27,28]. A self-administered web-based questionnaire was used to collect data in the two surveys. Participants were recruited from YouGov’s Denmark Panel with quota sampling for sex, age, education, and region. YouGov’s Denmark Panel comprises approximately 35,000 Danes aged 15–75 years living in Denmark. Web-panelists aged 18–65 years received an invitation and a link to participate in the study by email. All participants who responded to the first survey during the lockdown were reinvited to the second survey after the lockdown. Participants received an incentive bonus to be exchanged for a gift card, coupon, or participation in raffles. The number of bonus points participants receive depends on the response time of the survey. The average response time to complete the questionnaire was approximately 21 min. in both surveys. Figure 1 shows a participant flowchart of the current study. The population sample contains 839 participants with valid dietary data and 815 participants with valid PA data for the two surveys during and after the lockdown. ## 2.2. Diet A web-based semi-quantitative food frequency questionnaire (FFQ) was used to assess the whole diet. The FFQ was an updated and modified version of the questionnaire that has been used in the Danish pregnancy planning study. The FFQ from the Danish pregnancy planning study has been validated among Danish females [29]. The validation study shows that the FFQ is appropriate for collecting data on dietary intake, although measures of energy intake is $10\%$ lower compared to the 7-d pre-coded food diary used in The Danish National Survey of Diet and Physical Activity 2011–2013 (DANSDA). The recall frame in the FFQ was changed from the usual month in the previous year to the last two weeks to capture eating habits during the first national lockdown in 2020. Furthermore, photographs with portion sizes were added. The original questionnaire was also updated with data from market research on retail food sales to extend its use for 18–65-year-old Danes. This includes new food items on the intake of vitamin water, plant-based meat-, fish-, and dairy-alternatives, as well as candy, chocolate, cake, and sweet and salty snacks. Examples of commonly consumed food and drinks in a typical Danish meal pattern were also updated under each item. In the modified and updated FFQ, participants were asked to record how often they consumed food and drinks in the previous two weeks and the portion size (see Questionnaire). Data on consumption frequencies and the portion sizes of 209 food and 36 drinks were collected. Frequency scales differed between foods and drinks due to a larger variation in foods than drinks consumed. Portion sizes were specified in household measures, e.g., glasses, drinks, slices etc., or estimated from photographs. Eight series of color photographs with portion sizes of food and dishes in a typical Danish meal pattern were included. Intakes of energy, nutrients, food, and drinks were calculated for the study population using the software system webGIES 2019 (National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark), the recipe collection from DANSDA 2021–2023, and the Danish Food Composition Databank Frida ver. 4, 2019 (National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark). Validation of the diet recording was done by evaluating extreme estimated dietary intakes in the FFQ. Reporting status of energy was defined according to the Goldberg method, which is used to define mis-reporters of energy intake [30]. The Goldberg method appears to be a reasonable technique for categorizing mis-reporters on a FFQ [31]. Basal Metabolic Rate (BMR) was estimated according to equations from the Nordic Nutrition Recommendations 2012 [32]. The key indicator variable was a dietary index score that evaluates the overall diet quality by means of an index based on five food and nutrient guidelines from the Official Danish Dietary Guidelines 2013: saturated fat (<10 E%), added sugars (<10 E%), fruit and vegetables (≥600 g/10 MJ/day), fish (≥350 g/10 MJ/week), and whole grain (≥75 g/10 MJ/day) [33]. A slightly modified version of the diet index has previously been validated [34]. An individual score between 0 and 1 was calculated according to the compliance with each of the five guidelines. The dietary index score was calculated as the sum of the five scores, ranging from 0 to 5: Most far from compliance to compliance with all five dietary guidelines. ## 2.3. Physical Activity The Nordic Physical Activity Questionnaire (NPAQ) was used to assess PA and leisure screen time [35]. NPAQ has been used to monitor PA and sedentary behavior in large-scale Danish, Nordic, and international population surveys [36,37,38]. NPAQ has been validated against accelerometry in adults and the validation studies find that the questionnaire reflects the objectively measured levels of PA and is sufficiently reliable and valid to monitor PA in the general population [35,39]. NPAQ comprises two questions on leisure PA spent on MVPA and vigorous intensity PA (VPA) during the last 7 days and two questions on average daily leisure time spent sedentary in front of a TV or computer screen during the last 7 days (see Questionnaire). Moderate intensity PA (MPA) was estimated by subtracting VPA from MVPA. Compliance with guidelines on PA was classified as reporting at least 150 min of MPA per week or at least 75 min of VPA per week or an equivalent combination of MPA and VPA throughout the week [40]. Physically inactive was defined as adults who fail to meet the PA guidelines [32]. Guidelines for processing and classifying data from NPAQ have been described elsewhere [41]. Leisure screen time (TV and computer time) was used as an indicator of sedentary behavior. Very high leisure screen time was defined as individuals spending more than 6 h of their daily leisure time in front of a TV or computer screen. We also used a combined measure of MVPA and leisure screen time that was named ‘Sedentary leisure time’ to examine the public health challenge of those with insufficient PA and sedentary behavior. Sedentary leisure time was defined as individuals that have both been physically inactive and have had very high leisure screen time (>6 h/day). Our key variables were MVPA and leisure screen time. ## 2.4. Anthropometrics, Change in Body Weight, and Stress Level Questions on self-reported height and weight was used to calculate BMI (kg/m2) by dividing weight (kg) by the square of height (m). BMI was used to classify individuals according to their weight status using WHO’s cut-off values for overweight and obesity as indicators of excessive body fat accumulation presenting a health risk [42]. Self-reported weight was also used to estimate BMR [32]. Anthropometrics and self-reported change in body weight during the early period of the pandemic (March to May 2020) covering the first lockdown were only part of the second survey questionnaire. Weight gain or weight loss were reported in intervals of kilograms. Stress level was assessed by a question that has been used in DANSDA 2011–2013; however, the recall frame was modified from last month to last two weeks to capture stress level during (and after) the lockdown. ## 2.5. Statistical Analyses Diet, PA, and stress level were analyzed to detect changes in diet and PA assessed during and after the first lockdown using descriptive statistics as the first step. Variables were compared with t-tests. We used a level of $p \leq 0.05$ to indicate statistical significance in all analyses. The second step comprised statistical modeling that was carried out to identify effects on changes in diet, PA, and stress level in more detail between during and after the lockdown. Effects of sociodemographic factors, weight status, and time (assessed during and after the lockdown) were investigated. Each independent variable was modeled with a main effect (changes in diet, PA, and stress level) and an interaction with time. For continuous dependent variables, the dependent variable was transformed based on results from a box-cox analysis to achieve appropriate normality. For data containing zeroes, data were slightly perturbed prior to box-cox transformations and a sensitivity analysis was carried out. Logistic regression models were used to analyze categorical dependent variables. Dual analyses were performed for ordinal variables (three categories) considering the top category or the collapsed two top categories as dependent variable. A random-effect element was used in all models to handle the paired structure of data obtained during and after the lockdown for the same participant, i.e., a mixed model. We corrected for effect of reporting status of energy by including it as an independent categorical variable in all dietary analyses, where the reference group was acceptable reporters, allowing interaction with time. Results were reported for acceptable reporters, thus correcting other effects for decreased or increased reporting levels of energy for under- and over-reporters. Effect of an independent variable on the difference between time categories (during vs. after the lockdown) was reported if the interaction of the independent variable and time was statistically significant, thereby interpreting such an interaction as effect of the change after the lockdown. The direction of the effect of time was shown for levels of subgroups of significant independent variables, which significantly singled themselves out from other subgroups, e.g., the age group 18–34-year-olds significantly singled itself out from the other age groups for the independent variable added sugars. Non-significant levels were assumed to have no association with time. Green arrows were used to indicate favorable changes and red arrows unfavorable changes. Black arrows indicated a neutral change. If no level of subgroup stood significantly out from the rest for the significant independent variables, only the p-value was reported. Odds ratios (OR) and confidence intervals were calculated for categorical dependent variables. Logistic regression models were also used to analyze Danish adults with a large change in overall diet quality, MVPA, and leisure screen time after the lockdown, defined as their model residual in the original analysis being outside ±1 standard deviation. We analyzed whether sociodemographic factors and weight status impacted the probability of having a large positive or, respectively, negative residual difference in separate analyses. Moreover, logistic regression analyses were carried out to analyze the effect of sociodemographic factors and weight status on the probability distribution of self-reported weight gain, weight maintenance, or weight loss during the lockdown period. Numerical body weight change was reported with descriptive statistics, and differences in diet, PA, and stress level were analyzed according to self-reported body weight change (gain, maintenance, loss) with independent sample t-tests. Finally, we performed additional analyses: firstly, to compare the diet between mis-reporters and acceptable reporters; and secondly, to compare diet and PA with public health data before the lockdown. Comparison of sociodemographic characteristics and diet among acceptable reporters and mis-reporters of energy during the lockdown were analyzed with t-tests and chi-square tests. Additional data for diet and PA before the lockdown from DANSDA 2011–2013 and the Nordic Monitoring System 2014 are presented Supll. Furthermore, we examined the seasonal effect of diet and PA in previous research for reason of comparison with data in the present study. Seasonal variation for diet and PA were analyzed with independent sample t-tests, one-way ANCOVA with sex as covariate, and chi-square tests using data from DANSDA 2011–2013. Statistical analyses were carried out using R version 4.02 (R Core Team [2021]) and IBM SPSS Statistics, IBM Corp., New York, NY, USA version 25. ## 3.1. Characteristics of the Study Population Sociodemographic characteristics showed that the study population was close to the distribution of sex, age, education, and region in the general Danish adult population (Table 1). Still, 18–34-year-olds were somewhat under-represented and 50–65-year-olds were somewhat over-represented. Self-reported anthropometrics showed the prevalence of being overweight (including obesity) and obesity among 18–65-year-old Danes were $56.6\%$ and $20.8\%$, respectively. All reported results are statistically significant unless otherwise stated when comparing changes between the first lockdown and at a follow-up 5–6 months after. ## 3.2.1. Diet Descriptive statistics showed a large decrease in energy intake (0.6 MJ/day) after the lockdown among Danish adults compared to during the lockdown; however, the proportion of under-reporters of energy intake also increased (Table 2). The proportion of mis-reporters of energy intake was high during and after the lockdown due to a high proportion of under-reporters ($45\%$ vs. $51\%$). We found more mis-reporters among males and adults who were overweight/obesity (Table S1). Overall, mis-reporters registered a healthier diet composition than acceptable reporters during the lockdown. A lower percentage of carbohydrate, including added sugars, and a higher percentage of protein was found among mis-reporters. Furthermore, a higher content (g/10 MJ) of fruit and vegetables, fish, and water as well as a lower content of alcoholic drinks was registered among mis-reporters. A less healthy diet composition among mis-reporters was only seen for red meat. Analyses of macronutrients showed a decrease in the intake of dietary fiber after the lockdown, but otherwise, no change was seen in the macronutrient distribution. We found both favorable and unfavorable changes in the intake of food groups between the two survey periods. Intake of whole grain (unfavorable), fish (unfavorable), and candy and snacks (favorable) decreased after the lockdown, while the intake of water increased (favorable). No changes were found in the overall diet quality (dietary index score) and the consumption of fruit and vegetables, red meat, and sweetened or alcoholic drinks. The statistical modeling showed an effect of region and education on the change in energy intake after the lockdown. However, no regional or educational group stood out as significant (Table 3). Overall, we found a decrease in the consumption of saturated fat (favorable) and whole grain and fish (both unfavorable), and an increase in the intake of red meat (unfavorable) after the lockdown. The detailed analyses revealed effects for saturated fat, added sugars, and red meat that were not apparent from the crude descriptive statistics. The decrease in the consumption of whole grain was linked to a lower intake of rye bread among acceptable reporters (during: 68 ± 2 g/day vs. after: 57 ± 2 g/day, $$p \leq 0.001$$). The group of 18–34-year-olds stood out from other age groups with favorable changes after the lockdown: Their intake of added sugars decreased, and their intake of protein (neutral change) and water increased. Educational level had a significant impact on the change in dietary fiber intake as those with upper secondary school and medium/long higher education or held a Ph.D. decreased their intake after the lockdown (unfavorable). Sex, family status, household income, and weight status had no effect on dietary changes after the lockdown, according to the statistical modeling. We found no change in the overall diet quality, the consumption of total fat, carbohydrates, fruit and vegetables, and candy and snacks, as well as sweetened and alcoholic drinks after the lockdown. The modeled findings were consistent with the descriptive statistics, except for the decreased intake of candy and snacks that could not be confirmed in the more detailed analysis. ## 3.2.2. Physical Activity and Stress Level Descriptive statistics showed favorable changes for key PA variables after the lockdown (Table 2). Time spent in MVPA increased after the lockdown (0.5 h/wk) and leisure screen time decreased (0.5 h/d). These changes were mirrored in a decreased proportion of physically inactive (from $43\%$ to $37\%$), those with very high leisure screen time (from $43\%$ to $37\%$), and those with sedentary leisure time (from $19\%$ to $13\%$), respectively. Moreover, time spent in VPA increased and computer time decreased after the lockdown. Statistical modeling found that couples increased their time spent in MVPA after the lockdown (favorable; Table 3). Overall, Danish adults were less likely to be physically inactive after the lockdown. We found a decrease in leisure screen time after the lockdown that was moderated by a combined effect of family status and education: Leisure screen time decreased among adults with basic school in both singles and couples and among adults with medium/long higher education or Ph.D. in singles (favorable). Moreover, 35–49-year-olds were less likely to have very high leisure screen time (>6 h/day) after the lockdown (favorable), compared to 18–34- and 50–65-year-olds, who did not show a decrease in very high leisure screen time. Couples without children were more likely to have had very high leisure screen time after the lockdown compared to couples with children and singles (unfavorable). When analyzing sedentary leisure time, i.e., those that have both been physically inactive and have had very high leisure screen time, adults who had normal weight and were overweight were less likely to have had sedentary leisure time after the lockdown (favorable) compared to adults with underweight and obesity who did not show a decrease in sedentary leisure time. Sex, region, and household income had no effect on changes in PA and leisure screen time after the lockdown. Descriptive and modeled findings for key PA variables were overall consistent. We found no change in stress level after the lockdown. A proportion of 16–$17\%$ of Danish adults reported feeling stressed often or all the time during and after the lockdown. ## 3.3. Characteristics of Those with a Large Change in Diet and PA after the Lockdown Individuals with a large increase or decrease in the overall diet quality (dietary index score), MVPA, and leisure screen time after the lockdown were defined as having a large change in diet or PA: at least +1 SD residual difference corresponds to the $16\%$ of the study population with a large increase, while −1 SD residual difference corresponds to the $16\%$ of the study population with a large decrease. Sex, family status, and household income had significance for those with a large change in the overall diet quality. Females and individuals with a household income below 600,000 DKK (approximately €81,000) were more likely to have had a large increase in the overall diet quality after the lockdown, compared to men and individuals with a household income of least 600,000 DKK, respectively (favorable; Table 4 upper part). We also found a favorable change in the overall diet quality after the lockdown among couples without children, as they were less likely to have had a large decrease compared to couples with children and singles. Effects of family status and weight status were found for a large change in MVPA: Adults with obesity were more likely to have had a large increase in MVPA after the lockdown than those who were underweight, normal weight, and overweight (favorable), while no group stood out as significant with a large increase in MVPA regarding family status. However, we found a favorable change in MVPA among couples with children after the lockdown as they were less likely to have had a large decrease in MVPA compared to couples without children and singles. The large change in leisure screen time were moderated by family status and education: couples without children were both more likely to have had a large increase in leisure screen time and less likely to have had a large decrease after the lockdown compared to couples with children and singles (both unfavorable changes). In contrast, singles with children were more likely to have had a large decrease in leisure screen time after the lockdown compared to singles without children and couples (favorable change). A favorable change in leisure screen time was also found among those with basic school and medium/long higher education or Ph.D. as they were more likely to have had a large decrease compared to those with upper secondary school, vocational education, and short higher education. Age and region had no effect on a large change in key variables for diet and PA. ## 3.4. Change in Body Weight during the First Lockdown Period and Associations with Diet, Physical Activity, and Stress Level A proportion of $27\%$ of Danish adults reported they gained weight during the first lockdown period, while $58\%$ maintained their body weight and $15\%$ reported that they lost weight (Figure 2). On average, weight gainers gained 3 kg and weight losers lost 3.5 kg from March to May 2020 (Table 5). A mean weight gain of 0.3 kg was found among Danish adults during the lockdown period. Results showed that the overall diet quality (dietary index score) and MVPA were lower and leisure screen time higher among weight gainers than among weight maintainers. Moreover, stress level was higher among weight gainers and weight losers compared to weight maintainers. Logistic regression analysis showed that the probability of gaining weight was dependent on sex, age, family status, and weight status (Table 4 lower part). The age range of 50–65-year-olds were less likely to have gained weight than 18–34- and 35–49-year-olds during the lockdown period. Females were more likely than males to have gained weight. Singles without children and adults with overweight or obesity were also more likely to have gained weight compared to singles with children and couples and those with underweight and normal weight, respectively. Overweight adults were also more likely to have lost weight during the lockdown period compared to those who were underweight, normal weight, and obese. We found no effect of region, education, and household income on change in body weight during the first lockdown period. ## 4. Discussion The findings of the present study indicate that, five to six months after the first national lockdown in 2020, there were favorable changes in PA among Danish adults, but mixed results regarding their diet. However, the first lockdown period had an adverse effect on the body weight of many Danes. To the best of our knowledge, this is one of the first studies to report on the whole diet, PA, and sedentary behavior during and after a national lockdown with eased restrictions in the general adult population. Consequently, we will primarily compare our results with studies that have investigated changes in diet and PA before and during the COVID-19 lockdown. After the lockdown, there were both favorable (decreased intake of saturated fat and added sugars (18–34-year-olds) and increased intake of water (18–34-year-olds)) and unfavorable changes in the diet (decreased intake of dietary fiber (upper secondary school and medium/long higher education or Ph.D.), whole grain and fish, and increased intake of red meat). Since $43\%$ of Danish adults worked from home during the first national lockdown, this influenced their eating habits as they spent more time cooking and preparing home-cooked meals [7,8,43]. Open whole grain rye bread sandwiches were frequently eaten with fish as cold cuts for lunch and dinner as some of the home-prepared meals during the lockdown. After the lockdown, more Danes worked at the workplace, which may explain the decrease in the intake of whole grain rye bread and fish. Rye bread is the main contributor to whole grain and fish eaten as cold cuts contributes to half of the total fish consumption among Danish adults [44]. The increase in intake of red meat after the lockdown might be associated with eating out more. Other Danish COVID-19 studies reported a higher degree of emotional eating of sugar-rich foods such as cake during the lockdown period [7,8,9,43]. Our data do not show changes in the consumption of candy and snacks (including cake) and stress level after the lockdown using statistical modeling. However, Danes were world champions in buying candy before the lockdown [45]. This habit is strongly linked to “hygge”—an important aspect of Danish culture and associated with enjoying simple pleasures such as eating candy and watching television and spending time with loved ones such as family members. “ Hygge” may have increased during the lockdown but may have been difficult to change after the lockdown. The reported intakes of candy and snacks during and after the lockdown were high. Still, we found a decreased intake of added sugars among 18–34-year-olds after the lockdown. Changes in eating habits after the lockdown were among other factors moderated by age. The group of 18–34-year-olds stood out as a group with favorable changes in the diet. These results may indicate that 18–34-year-olds resumed to healthier eating habits more rapidly after the lockdown than 35–49- and 50–65-year-olds. A large increase in the overall diet quality after the lockdown was found among females and adults with household incomes below 600.000 DKK. The healthier eating habits among females after the lockdown could be explained by inclines in weight loss promoting behaviors as they were more likely to have gained weight during the first lockdown period than men. When we compare 18–65-year-old Danes’ diet during the COVID-19 pandemic with national data before the pandemic (Table S2 upper part), mixed findings were identified. Eating habits during the pandemic were more favorable compared to the average Danish diet before COVID-19 due to a lower intake of saturated fat, red meat, and alcoholic drinks, but less favorable due to a lower intake of fruit and vegetables and fish, and a higher intake of candy and snacks and sweetened drinks, respectively. This comparison should be viewed in the light of differences between study populations, dietary assessment methods, energy intake, and survey years. Overall, our findings are in line with a systematic review of the global changes in eating habits during the lockdown, except for the lower intake of fruits and vegetables that was also found in other Danish COVID-19 studies [7,8,46]. Favorable changes were found in PA (increased MVPA in couples) and sedentary behavior (decreased leisure screen time with a combined effect of family status and education) among Danish adults after the lockdown. These changes were mirrored in a decreased proportion of physically inactive, those with very high leisure screen time (35–49-year-olds), and those with sedentary leisure time (adults who had normal weight and were overweight), i.e., those that have both been physically inactive and have had very high leisure screen time. A study from Scotland also found decreased sitting time among 18 years or older 2–3 months after the first national lockdown when restrictions started to ease, but no change in MVPA [27]. It is worrying, from a public health point of view, that 460,000–700,000 Danish adults have had sedentary leisure time during and after the first lockdown. On average, Danes spent around 6 h daily of their leisure time in front of a TV or computer screen during the first wave of the COVID-19 pandemic: this value is somewhat above the threshold of 3–4 h/day for increasing the risk of disease and mortality [47]. A large French study found the presence of children at home to be associated with unfavorable changes in PA during the lockdown [17]. Family status also seems to have been a key sociodemographic factor for the changes in PA in our study. We found favorable changes in MVPA after the lockdown among couples and in leisure screen time among couples with basic school, but also among singles with basic school or medium/long higher education and a Ph.D. The favorable change in MVPA may suggest that couples increased their level of exercise and sports activities more rapidly than singles after the lockdown. Our findings also indicate that favorable changes in PA and sedentary behavior do not always go hand in hand for all population groups, as couples without children have had an increase in MVPA and a large increase in leisure screen time after the lockdown. A comparison of PA and sedentary screen time in the Danish adult population during the pandemic with national data before shows that the proportion of physically inactive (before: 26–$34\%$ vs. during: 37–$55\%$) and those with very high leisure screen time (>6 h/day: before: 9–$16\%$ vs. during: 37–$43\%$) were higher during the pandemic [36,48] (Table S2 lower part). Danish adults have, on average, spent 0–1.4 h less weekly on MVPA and 1.7–3.0 h more daily on sedentary leisure screen time during the pandemic. These data suggest that many Danes have used the increased ‘free’ time during the pandemic by being sedentary in front of a TV or computer screen. Overall, results indicate that the COVID-19 pandemic has had a highly unfavorable effect on PA and sedentary behavior in the Danish adult population. Our findings are in line with previous research [3,4,10,17,36,38,49,50]. Less exercise and sports activities, as well as less active transportation, especially among the large number of Danes working from home, may explain the decrease in MVPA during the pandemic. A French study showed that active transport such as walking and bicycling was among the activities that was most affected by restrictions during the lockdown [51]. Even 2 years after the beginning of COVID-19, worldwide and European daily step counts have not returned to pre-pandemic levels, indicating that unfavorable changes of PA during the pandemic have become established habits for some time [52]. Of public health concern is that adults may never return to pre-pandemic PA levels. It is also a public health concern that approximately one in five Danish adults live with obesity due to the adverse health effects that, among other factors, also comprise a higher risk for severe COVID-19 related disease and mortality [19,53]. The prevalence level of overweightness, including obesity, in the present study is comparable to data from the Danish National Health Profile 2021 [36]. We found more Danish adults that reported gaining weight than losing weight during the first lockdown period ($27\%$ vs. $15\%$). On average, weight gainers put on 3.0 kg and weight losers lost 3.5 kg. Our findings are consistent with the documented global trend of weight gain during the first COVID-19 lockdown period [50,54]. Still, results from 4.25 million US adults showed that mean weight gain in first year of the COVID-19 pandemic was small (0.1 kg) [55]. In our study, an average weight gain of 0.3 kg was found among Danish adults in the first three months of the pandemic. According to previous research, one explanation for the high proportion of weight gainers could be that social isolation during the lockdown period might have deteriorated psychosocial health, altered eating behavior in the direction of more snacking, decreased exercise, and increased sedentary time [2,5,50]. Our data confirm that weight gainers had less healthy eating habits, less MVPA and more screen time during the first lockdown period compared to weight maintainers. On average, weight gainers spent 1 h less per week on MVPA and 0.8 h more per day on leisure screen time than weight maintainers. We also found higher levels of stress among weight gainers and weight losers than among weight maintainers during the lockdown period which is in line with other studies [56]. Females, singles without children, and adults with overweight or obesity were more likely to have gained weight during the first lockdown period. These population groups could therefore have been more exposed to COVID-19 related stress that can lead to emotional eating and reduction in PA, thus causing declines in weight gain protective behaviors [6,56,57]. The finding of females to be more likely to have gained weight than men is consistent with other studies that found females to be at increased risk for weight gain due to increases in unhealthy lifestyle behaviors during the lockdown period [2,58]. School and daycare closures, followed by childcare and homeschooling, may have affected females more as primary childcare givers. Singles without children were also more likely to have gained weight during the lockdown period. These data are supported by a French study showing that living alone was a strong risk factor for unhealthy behavior during the lockdown [59]. However, in contrast to what has been reported elsewhere, we found 50–65-year-olds to be less likely to have gained weight during the lockdown period than 18–34- and 35–49-year-olds [2]. We found that adults who were overweight and obese were more likely to have gained weight during the lockdown than those who were underweight and had normal weight. These results align with previous research [2]. Studies from the UK showed that individuals living with obesity were most likely to report declines in weight gain protective behaviors such as eating healthily, exercising, and getting sufficient sleep during the first COVID-19 lockdown, which may have increased their risk of weight gain [12,60,61]. However, we also found favorable changes in PA after the lockdown among adults living with obesity that were more likely to have had a large increase in MVPA compared to those who were underweight, had normal weight, and obese. These findings support research from the UK, where adults living with obesity increased their PA and were attempting to lose weight after the first COVID-19 lockdown [62]. Adults who were overweight were both more likely to have gained and lost weight during the lockdown period than those in other categories: underweight, normal weight, and obesity. These data suggest that the lockdown may have resulted in a polarized effect among adults who were overweight with both weight gainers and losers. ## 5. Strengths and Limitations One of the strengths in the present study is the longitudinal design that makes it possible to examine changes in eating habits and PA assessed during and after the first lockdown. Another strength is the study sample that was close representative of the general Danish adult population regarding sex, age, education, and region. This increases the generalizability of the results. Data collection with validated questionnaires to assess diet and PA over a short period (6–16 days) may also be viewed as a strength when the aim is to get a snapshot of current eating habits and PA during and after the lockdown. The short recall frames might have increased participants’ ability to accurately recall their diet (last two weeks) and PA (last 7 days). A further strength is the assessment of the whole diet that reflects the usual eating habits. Most studies reporting on eating habits during the COVID-19 pandemic have used indicator questions and therefore did not assess the whole diet [7,8,11,12,13,14,15]. It is also a strength that our findings increase the limited knowledge in Denmark regarding sociodemographic factors associated with changes in eating habits and PA after the lockdown and changes in body weight during the first lockdown period. There are several limitations in this study. One limitation is the large percentage of excluded participants (38–$39\%$) from the initial sample caused by dropout, invalid dietary or PA data, non-participation in both surveys, and for not giving informed consent for scientific publication. The high response time to complete the questionnaire may be one of the reasons for dropping out and for not reporting valid dietary and PA data. A large percentage of excluded participants was also found in other Danish and international COVID-19 online surveys [8]. Despite the large number of excluded participants in the present study, the sample was still close to be representative for the general Danish adult population. Another limitation is the high proportion of under-reporters of energy intake; however, we accounted for misreporting in the statistical modeling. Correction of misreporting was important in the present study as under-reporters registered a healthier diet than acceptable reporters. Under-reporting is a common problem with FFQ’s [63] because they do not cover all participants’ usual eating habits perfectly. Furthermore, it may have been challenging for participants to report their intake of food and drinks with a frequency scale that was somewhat different for food and drinks and with no personal instruction before fulfilling the first FFQ. Still, we believe that overall, the dietary assessment method reflected Danish adults’ eating habits during the COVID-19 pandemic quite well. Our data also place a question mark about the interpretation of the size of change in energy intake with descriptive statistics when under-reporting is high and increases between survey periods. This may also be the case for the decreasing intake of candy and snacks after the lockdown that we found with descriptive statistics but that could not be confirmed with the statistical modeling. A limitation with the assessment of PA and sedentary behavior could be self-report bias, leading to over-reporting of MVPA and under-reporting of sedentary screen time [64]. However, screen time may not have been underestimated that much; it cannot be ruled out that even if TV and computer time have been questioned separately, participants may have reported some TV and computer time that took place simultaneously. Self-report bias has likely been present in both surveys, making data comparable during and after the lockdown. A final but important limitation is to separate a seasonal effect on diet, and especially PA, from the COVID-19 effect. A scoping review documented a seasonal difference in MVPA, but not in sedentary behavior between spring and autumn, because people tend to be more active in spring than autumn [65]. Still, weather reports showed that it was less attractive to be physically active outside in Denmark in March–April 2020, during the lockdown, compared to after the lockdown, in September 2020. This is because it was eight degrees Celsius colder on average, even if it was less rainy and with more hours of sunshine [66]. Additional analyses of the seasonal effect in PA in Denmark showed no difference in MVPA and the proportion of physically inactive, but 0.5 h/day more leisure screen time in March–April compared to September (Table S3 lower part). Comparison of the results from the present study with additional seasonal data suggest that the increase in MVPA after the lockdown may be attributed to a COVID-19 effect with easing restrictions, whereas the decrease in leisure screen time may be a combined COVID-19 and seasonal effect. Changes in diet may be attributed to a COVID-19 effect (Table S3 upper part). ## 6. Conclusions This study shows that the extent of restrictions during a pandemic, such as COVID-19, has a significant impact on people’s eating habits, PA, and body weight. Therefore, future outbreak management should prioritize promoting healthy eating and regular PA during a pandemic, taking public health concerns such as unhealthy diet, physical inactivity, and overweightness into account. Additionally, we identified sociodemographic factors that were associated with changes in diet, PA, and body weight after the lockdown, which could guide public health authorities in targeting specific sub-populations during pandemic conditions, such as COVID-19. ## References 1. **WHO Coronavirus (COVID-19) Dashboard** 2. Chew H.S.J., Lopez V.. **Global Impact of COVID-19 on Weight and Weight-Related Behaviors in the Adult Population: A Scoping Review**. *Int. J. Environ. Res. Public Health* (2021.0) **18**. DOI: 10.3390/ijerph18041876 3. 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--- title: Understanding the Diurnal Oscillation of the Gut Microbiota Using Microbial Culture authors: - Guilherme Amando - André Tonon - Débora Constantino - Maria Paz Hidalgo - Pabulo Henrique Rampelotto - Francisco Montagner journal: Life year: 2023 pmcid: PMC10054680 doi: 10.3390/life13030831 license: CC BY 4.0 --- # Understanding the Diurnal Oscillation of the Gut Microbiota Using Microbial Culture ## Abstract The composition of the gut microbiota oscillates according to the light–dark cycle. However, the existing literature demonstrates these oscillations only by molecular methods. Microbial cultures are an interesting method for studying metabolically active microorganisms. In this work, we aimed to understand the diurnal oscillation of the intestinal microbiota in Wistar male rats through microbial culture analysis. Over a 24 h period, three animals were euthanized every 6 h. Intestinal segments were dissected immediately after euthanasia and diluted in phosphate-buffered saline (PBS) for plating in different culture media. The CFU/mL counts in feces samples cultured in the *Brucella medium* were significantly higher at ZT0, followed by ZT6, ZT18, and ZT12 ($$p \leq 0.0156$$), which demonstrated the diurnal oscillation of metabolically active anaerobic bacteria every 6 h using microbial culture. In addition, quantitative differences were demonstrated in anaerobic bacteria and fungi in different gastrointestinal tract tissues. ## 1. Introduction The circadian system provides rhythmicity to several physiological processes of living beings (e.g., hormonal secretion, temperature, and blood pressure) and is synchronized to cyclic environmental signals (i.e., external clues of temporality) in a process known as entrainment. Daily rhythms of approximately 24 h are called circadian rhythms [1,2,3]. The entrainment of the circadian system (endogenous) with environmental signals (exogenous) is crucial for maintaining health [4,5] and occurs mainly by light, the main zeitgeber (“time giver” in German; environmental cue of the passage of time) [6,7]. Moreover, circadian misalignment (mismatch between internal and external rhythms) is often observed to be associated with metabolic and gastrointestinal disorders [8,9,10,11]. Recent studies have demonstrated that the intestinal microbiota also undergoes diurnal compositional and functional oscillations, which are driven by the light–dark cycle [12,13,14]. This oscillation has been demonstrated in adults (and associated with short-chain fatty acid levels) [15] and in mice kept under different light exposure protocols, where the group in a forced jet lag protocol showed arrhythmicity of these populations [12]. Diurnal microbial pattern drives, in turn, the host physiology and metabolism in many ways [16]. Additionally, diabetes type 2 was associated with disrupted rhythmicity of microbial populations in the gut of a longitudinal population-based cohort [17]. Similarly, another study suggested that this microenvironment could be an independent contributor to elevated serum amino acid levels in participants with insulin resistance [18]. In addition to its diurnal oscillation, gut microbiota is influenced by biogeography, allowing the establishment of different microbial populations in each intestinal microenvironment [19,20]. Assessing microbial populations at different times is crucial for understanding such diurnal oscillations. Different studies have showed that pathological outcomes are associated with circadian rhythm disruption [21,22], which also induces microbiota dysbiosis [9,23]. Furthermore, a recent study demonstrated the oscillation of different microbial phyla in healthy mice, but also the lack of rhythmicity of mice in constant conditions (e.g., 24 h of constant darkness every day) and knockout for clock genes [24]. Thus, it is important to address multiple time points to better characterize any gut microbiota change. Different approaches can be used to characterize the gut microbiota. With the advent of high-throughput sequencing, most studies nowadays characterize these microbial communities by metagenomics [25,26]. However, metagenomics does not discriminate viable from non-viable cells as well as active or quiescent microorganisms. This may be mitigated using RNA sequencing, but metatranscriptomics is still a high-cost technology inaccessible to most researchers. The microbial culture method can be used to study the metabolically active populations that represent major components of the intestinal microbiota, such as cultivable bacteria and fungi [27,28]. In addition, this traditional method can be the first step toward culturomics [27,29], where new microbial species can be taxonomically validated and officially named. Moreover, the microbial culture could complement the microbiota characterization provided by metagenomics because this molecular method may also detect inviable microorganisms, giving a false assumption about their role [30]. To date, a few studies have evaluated the diurnal oscillations in intestinal microbial populations, but none have used the microbial culture method. To fulfill this need, the aim of this study was to analyze the microbial cultures of different tissues of the gastrointestinal tract (i.e., cecum and rectum) as well as feces taken directly from the rectal ampoule at different zeitgeber times to understand the diurnal oscillation of the gut microbiota of male Wistar rats. ## 2.1. Animals Male Wistar rats ($$n = 12$$) at 13 weeks of age were obtained from the Centro de Reprodução e Experimentação em Animais de Laboratório (CREAL, Porto Alegre, Brazil). The sample size calculation was based on work by Thaiss et al. [ 2016] and was defined based on the evaluation of circadian variation in the composition of the gut microbiota [13]. Before the protocol started, the rats had been moved daily among cages to ensure that all animals were housed with all other animals for at least 2 days. This procedure enables the induction of a uniform baseline microbiota across all of them. All animals were fed ad libitum with a regular chow diet and kept under the same controlled conditions of temperature (22 ± 2 °C), humidity, reduced noise exposure, and a standard photoperiod (12 h light and 12 h dark, with lights on at 7:00 am). These conditions are the standard for a bioterium of rats that is not intended to cause any intervention or stress on the animals. The research protocol was approved by the Institutional Animal Research Ethics Committee at the Hospital de Clínicas de Porto Alegre (CEUA/HCPA, protocol number 2019–0413), following the recommendations set out in the ARRIVE guidelines [31]. ## 2.2. Experimental Protocol Over the course of a 24 h period, 3 animals were euthanized every 6 h. Immediately after euthanasia, the intestines were dissected on a sterile field. The small intestine was separated and sectioned to obtain samples of cecum and rectum. Feces were taken directly from the last portion of rectal ampoule. The fragments of each sample (i.e., cecum, rectum, and feces) were weighed and stored per animal in separate Falcon tubes, preparatory to microbial culturing. After collecting the sample, sterilized phosphate-buffered saline (PBS) solution was added to the tube, maintaining the proportion of 1 mg of sample to 1 μL of PBS. The procedures for the use of scientific animals were also conducted in accordance with the Guide for the Care and Use of Laboratory Animals [32]. This study was registered with the National System of Genetic Resource Management and Associated Traditional Knowledge (SisGen), under registration number ABFDC4F. ## 2.3. Serial Dilutions and Culture Media Serial dilutions were performed starting from the initial sample to $\frac{1}{10}$, $\frac{1}{1000}$, and $\frac{1}{100}$,000 using PBS solution. The undiluted sample was pipetted at the center of a Petri dish. Each Petri dish (90 × 15 mm) was divided into three equally distributed sections. Three 25 μL drops of each dilution were pipetted into one of the three sections, one section per dilution, with no contact between drops [33]. The periods, conditions of incubation, and purpose of each culture medium used are described in Figure 1. The culture media (purchased from HiMedia®, Mumbai, India) chosen were selected to cover the main groups of cultivable microorganisms from the gut. This method was used only for the purpose of counting these microorganisms. The number of colony-forming units (CFU) present in a single drop (25 μL per drop) was determined for each culture media by multiplying the number of CFU observed during counting by 40, 400, 40,000, or 4,000,000, depending on the dilution being counted, as obtained by the following equation: CFU initial sample/mL (total) = CFU count × 40 × dilution factor. These dilutions were chosen to allow better visualization of the cultivated colonies. In cases where an extremely high number of colonies made counting of CFU impossible, it was decided to use the maximum number possible of CFU in a 25 μL drop (i.e., 75 CFU) at dilution of 10−5, as described by Naghili et al. [ 2013] [33]. Petri plates with patterns indicative of contamination were excluded from analyses. ## 2.4. Time Measurements The exact time referring to the light and dark phase is of major importance to our study because it is directly linked to the outcome. Thus, the results were described through the measure of time called zeitgeber time (ZT), commonly used to measure time in chronobiological studies. The ZTs correspond to six-hour intervals within a 24 h period, starting at the beginning of the light phase. The experimental protocol started at ZT0, which corresponded to the moment when the lights in the bioterium were turned on, namely 7 am for the researchers. ## 2.5. Statistical Analysis All analyses were performed in GraphPad Prism version 8.4.2, with significance at $p \leq 0.05.$ Study variables are described as median (interquartile ranges) because there was no parametric distribution of the data (see Table S1). For comparisons of CFU/mL counts between different sites and ZTs, the Kruskal–Wallis test followed by Dunn multiple comparison was used. ## 3. Results The CFU/mL results for each culture medium for samples collected at each ZT are expressed as their respective medians (see Figure 2 or Table S1). ## 3.1. Differences between ZTs In samples plated in BA medium, the CFU/mL count in feces was significantly higher ($$p \leq 0.0156$$) at ZT0, followed by ZT6, ZT18, and ZT12. This indicates that the microorganisms cultivated in this medium peaked their concentration in the beginning of the light phase (ZT0), decreased in the middle of the light phase (ZT6), reached the lowest point at the end of light phase (ZT12), and started to increase their concentration again in the middle of the dark phase (ZT18). There was a trend towards statistical significance ($$p \leq 0.0662$$) for the RT samples in the MS medium, with the highest CFU/mL count observed at ZT6, followed by ZT18, ZT12, and ZT0. Similarly, as observed in BA medium, this trend indicates that higher concentrations of microorganisms were observed during the light phase (ZT0 and ZT6 = light phase). Specifically, the concentration of CFU/mL peaked in the middle of the light phase (ZT6), reached the lowest point at the end of the light phase (ZT12), increased its concentration again in the middle of the dark phase (ZT18), and decreased again in the beginning of the light phase (ZT0). There was no statistical difference between ZTs in BHI and SA media. ## 3.2. Biogeographic Differences In samples plated in BHI medium, the CFU/mL count was higher in FC than in CE and higher in CE than in RT at both ZT6 ($$p \leq 0.0321$$) and at ZT12 ($$p \leq 0.0036$$). This indicates that there is a different concentration of microorganisms and could indicate a distinct diversity in the middle of the light phase (ZT6) when comparing sample sites. There was a trend towards statistical significance at ZT18 ($$p \leq 0.075$$) following the same pattern (i.e., FC > CE > RT) (Figure 2), indicating the same difference observed in BHI medium, but in the middle of the dark phase (ZT18). In samples plated in SA and MS media, there were statistically significant differences at ZT0 ($$p \leq 0.0214$$; $$p \leq 0.0107$$) following the same pattern, also indicating the same biogeographic differences observed in other media, but at the beginning of the light phase (ZT0). There was no statistical difference in samples plated in BA medium. ## 4. Discussion In this preliminary work, we present evidence of the diurnal oscillation of microbial populations in the gut and differences in their composition using microbial culture methods. Our results also indicated differences among sampling sites, demonstrating biogeographical differences in different GI tract sites. Our main findings showed that the feces samples cultivated in Brucella agar (i.e., facultative anaerobic bacteria) exhibited microbial variation between ZTs, with higher concentrations of CFU/mL at the beginning and in the middle of the light period (i.e., resting phase). Using a metagenomic approach, Thaiss et al. [ 2014] found evidence of rhythmic disruption in microbial populations of Ruminococcaceae, a family belonging to Firmicutes (predominantly anaerobic) [12]. Two other species from this phylum also exhibited changes in relative abundance over the course of the day. These species had a higher relative abundance value in the resting phase [12]. Here, our results suggested a similar oscillation of bacterial concentration, although we used a microbial culture method, collecting species from different sites. In this study, the laboratory growth conditions favored facultative anaerobic bacteria of the genus *Streptococcus to* be cultivated in the BA medium. There was a high number of microorganisms at the beginning of the light phase, observed by the peak in CFU/mL counting at ZT0. Li et al. [ 2017] observed that the gastrointestinal microbiome of rats is predominantly composed of the phylum Firmicutes, regardless of the tissue collected [20]. Similarly, Thaiss et al. [ 2016] demonstrated that Mucispirillum schaedler, a species from the *Deferribacterota phylum* that is also anaerobic, had higher concentrations at the beginning of the light phase [13]. Both studies seem to agree with the results of this study. Our findings also revealed differences between collection sites in CFU counts during the middle of the light phase (ZT6), and afterward at the end of the light phase (ZT12) in BHI media (facultative anaerobic bacteria). These differences indicated that feces exhibited higher concentrations of microorganisms than the cecum and rectum, respectively. Relative abundance regarding the rhythmicity of bacterial communities in different sample sites of the intestinal tract of rats has also been reported throughout the day [12,13,14]. The control group exhibited a different configuration of bacterial genera depending on the time of day. However, rats submitted to a chronodisruption protocol lost the oscillatory pattern [12]. Another study observed similar rhythmicity of several microbial taxa once every 4 h [34]. We observed different CFU counts depending on the time of day for bacteria cultivated in the BHI media, representing highly abundant and metabolically active microorganisms. Results from the Mitis Salivarius and BHI culture media indicate biogeographical interference due to the highest CFU/mL values for FC, followed by CE and RT. Recently, the bacterial communities present in each segment of the gastrointestinal tract (feces and the contents of the large and small intestine) of male rats were described using metagenomics [35]. Higher bacterial diversity and proportion for bacterial components of different genera and families in the large intestine, but mainly in feces, were observed. *These* genera and families are mostly represented by anaerobic bacteria. Furthermore, Li et al. [ 2017] also presented results consistent with the study mentioned before. The diversity found was attributed to a more complex micro-ecosystem in the large intestine of rats, resulting in higher bacterial concentrations in feces [20]. Although cultures do not enable all microorganisms to be cultivated separately, our results from Mitis Salivarius and BHI are consistent with the studies mentioned above. Fungi are an important component of the gut microbiome, but they are frequently neglected in most studies [36]. Here, we observed a higher CFU/mL count at the beginning of the light phase (i.e., rest period). Chen et al. [ 2018] demonstrated that *Aspergillus fumigatus* colonization in rats knocked out for different clock genes differed depending on the time at which the animal was infected. Moreover, there was a difference in CFU counts between the times, with the ZT0 having the highest number of CFU counts in the lung compared to ZT12. The authors suggested that the interaction between the host and this particular fungus may be under some circadian control [37]. In our study, higher fungal counts were also observed at the beginning of the morning (ZT0) in feces when compared to the other collection sites. However, A. fumigatus cannot be cultured in the SA medium. In our study, we incubated the SA media plates at room temperature (25 °C ± 2 °C) following incubation at 37 °C (see Figure 1). As described by Hazen and Hazen [1987], Candida albicans room-temperature-grown cells were generally less sensitive to environmental perturbation and germinated more uniformly than cells grown at 37 °C [38]. Furthermore, a different study suggested that there is a synergy between this fungus and species of Bacteroides. The authors observed that while Bacteroides’ growth was significantly enhanced in co-culture with C. albicans, the cell concentrations of some strains of C. albicans were unaffected by the presence of specific Bacteroides species. This result suggests the cells of C. albicans may serve as an additional nutrient source for the bacteria in anaerobic regions of the gut [39]. Here, this synergy could explain the higher concentrations of CFU/mL in feces when compared to other collection sites. Bacteroides species are mainly represented in BA media and, as described before, the concentration of CFU/mL in feces peaked at ZT0. This peak may have influenced the concentration of CFU/mL of fungi evaluated in the SA culture medium. Furthermore, this influence could have led to differentiation in the number of microorganisms between sites, resulting in a higher concentration of fungi in feces than in other sites. To date, this is the first study to highlight the diurnal oscillation and biogeographical differences of the gut microbiota using culture media, and the results presented here have relevant implications. First, the identification of a diurnal oscillation of metabolically active anaerobic bacteria once every 6 h indicates that this component possibly impacts most studies involving the gut microbiota. Therefore, the evaluation of this oscillation is of major importance to ensure the reproducibility and reliability of future research. Furthermore, it is important to emphasize how different microorganisms can be in one day. For instance, in the same direction of melatonin’s phase response, it is extremely important that every study focused on evaluating microbial communities should aim to assess at least three different moments during a day. Thus, future studies should consider a chronobiological design for the collection and evaluation of the outcome of interest, regardless of the microbiota. Moreover, our study provides a model of what to expect from regular variations of intestinal microorganisms because the rats were kept in normal conditions in every aspect (i.e., food intake, light exposure, no stressors). It is important to note that our preliminary results were obtained over the course of one 24 h period. Additional studies should be performed with longer periods of time to confirm the periodicity of our findings, but also to compare with different photoperiods. It is important to understand the extension of how metabolically active microorganisms behave in constant photoperiods (i.e., 24 h of constant light or darkness) to elucidate the role of light and its influence on the gut microbiota. It is also important to note that our small sample size was based on a sample size calculation, which supports the fact that our procedure and results derived from our methodology are not random. Similarly, there are plenty of studies evaluating outcomes related to the rhythmicity of the gut microbiota using small samples similar to ours [12,13]. In addition, these studies usually use some type of intervention, whether light (e.g., constant darkness) or medication (usually antibiotics). Thus, future studies should aim to increase the protocol time to assess whether the rhythmicity observed in some culture media is maintained over longer periods. Second, the use of different culture media enables the detection of changes in intestinal microbial compositions at different collection sites, providing the baseline for the application of more advanced culture methods in future studies analyzing the circadian rhythm of the gut microbiota. Thus, this traditional method can be the first step toward the use of culturomics in circadian rhythm research, where new microbial species could be taxonomically validated and officially named. Moreover, it is important to note that one of our goals here was to observe the diurnal oscillation of anaerobic microorganisms more carefully because they also constitute a large portion of the gut microbiota. Furthermore, we also aimed to observe these oscillations in fungi, which are also an important component of the gut microbiome, though they are frequently neglected in most studies. Hence, we chose culture media that could fulfill these goals. More specifically, BA and MS culture media were chosen to cover most anaerobic bacteria, whereas BA and SA would cover aerobic microorganisms (bacteria and fungi, respectively; see Figure 1). Additionally, there is a portion of the gut microbiota that comprises non-culturable microorganisms and that plays an extremely important role in the physiology and homeostasis of this microenvironment. To meet this need, next generation sequencing techniques, such as amplicon sequencing (e.g., 16S rRNA), could be used to address non-culturable taxa characterization. Currently, this technique is the most widely applied in microbiome studies [25,26] and has plenty of standardized analytical pipelines aiming to produce accurate and reproducible results, thereby allowing comparison between studies [40]. It is important to note that we only used male rats due to uncertainty regarding whether there is any interaction with the estrous cycle and microbial communities in the gut. The literature has shown that the estrous cycle interferes with several physiological processes in rats [41,42,43]. We do not know for sure whether this process interferes with the rhythmicity of the gut microbiota, but to avoid the risk of influencing this microenvironment, we chose not to use female rats. Future studies should evaluate whether there is some interaction between the estrous cycle and microbial communities while controlling the phases of the estrous cycle that occur after the vaginal opening. Third, we chose to use non-specific culture media in conditions to favor the growth of strict and facultative anaerobes, allowing the growth of a large group of cultivable microorganisms. Therefore, it is expected that they vastly cover the expected populations in the gut microbiota. It would also be interesting to evaluate the oscillation of specific targets, such as Klebsiella spp., which is fundamentally important in studies of hospital-acquired infections and antibiotic resistance [44,45], as well as Escherichia coli, which has been observed to be associated with several intestinal diseases and virulence potential [46,47,48]. Furthermore, future studies should focus on evaluating lactic acid bacteria due to their relevance as one of the major components of microorganisms in the gut microbiota. Furthermore, plenty of culture media could be used to grow these microorganisms, such as MRS (De Man, Rogosa, and Sharpe) agar, for example. Other physiological and molecular aspects may be associated with these diurnal oscillations in the gut microbiota and should be observed in future studies. Wang et al. [ 2021] aimed to explore the effect of different feeding patterns on intestinal health through, among other parameters, the expression of short-chain fatty acids (SCFA), intestinal tight junction proteins, clock genes, and the diurnal rhythm of microbial populations in rabbits [49]. At the beginning of the dark phase (ZT13), levels of butyric acid (SCFA) were higher in the control group when compared to the restricted food group (intervention group). However, in the same ZT, levels of CLAUDIN-1 (intestinal tight junction proteins) and PER1 (clock gene) were significantly higher in the intervention group. In addition, there were different percentages of relative abundance in Firmicutes and *Bacteroidetes phyla* in ZT13; the first were cited higher in the intervention group but the second were cited lower in the same group [49]. Here, we observed different CFU/mL counting at ZT12 among the culture media, and the BA medium had the lowest count. This suggests a similar behavior observed of the Bacteroidetes phylum’s relative abundance in the control group. Anaerobic bacteria are also present in this phylum. Therefore, the results of Wang et al. [ 2021] seem to agree with our results. Furthermore, aiming to fully understand the mechanisms that underlie the diurnal rhythmicity of the gut microbiota, future studies should aim to evaluate specific molecules that underlie the physiology of the gastrointestinal tract. Lastly, it is important to emphasize that every methodology of assessing microbial populations has both advantages and limitations. The microbial culture-based method is time-consuming, dependent on culture media and incubation characteristics, and unsuitable for fastidious bacteria growth with complex nutritional requirements. Furthermore, as stated before, some microorganisms that cannot be cultivable and are crucial to understanding gut microbiota complexity. Remarkably, advances in molecular approaches contribute to several topics of microbiology research and have brought about a significant body of new knowledge regarding not only diseases, but also health aspects. However, as stated before, most molecular methods are not able to fully demonstrate the aspects of several microbiotas. The characteristics of both culture-based and molecular methodologies were previously elucidated by Siqueira and Rôças [2005] [30]. The authors suggest a workflow on how to combine both methodologies to achieve a better understanding of the microenvironment landscape. 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--- title: Cross-Sectional Association of Dietary Patterns and Supplement Intake with Presence and Gray-Scale Median of Carotid Plaques—A Comparison between Women and Men in the Population-Based Hamburg City Health Study authors: - Julia Maria Assies - Martje Dorothea Sältz - Frederik Peters - Christian-Alexander Behrendt - Annika Jagodzinski - Elina Larissa Petersen - Ines Schäfer - Raphael Twerenbold - Stefan Blankenberg - David Leander Rimmele - Götz Thomalla - Nataliya Makarova - Birgit-Christiane Zyriax journal: Nutrients year: 2023 pmcid: PMC10054689 doi: 10.3390/nu15061468 license: CC BY 4.0 --- # Cross-Sectional Association of Dietary Patterns and Supplement Intake with Presence and Gray-Scale Median of Carotid Plaques—A Comparison between Women and Men in the Population-Based Hamburg City Health Study ## Abstract This population-based cross-sectional cohort study investigated the association of the Mediterranean and DASH (Dietary Approach to Stop Hypertension) diet as well as supplement intake with gray-scale median (GSM) and the presence of carotid plaques comparing women and men. Low GSM is associated with plaque vulnerability. Ten thousand participants of the Hamburg City Health Study aged 45–74 underwent carotid ultrasound examination. We analyzed plaque presence in all participants plus GSM in those having plaques ($$n = 2163$$). Dietary patterns and supplement intake were assessed via a food frequency questionnaire. Multiple linear and logistic regression models were used to assess associations between dietary patterns, supplement intake and GSM plus plaque presence. Linear regressions showed an association between higher GSM and folate intake only in men (+9.12, $95\%$ CI (1.37, 16.86), $$p \leq 0.021$$). High compared to intermediate adherence to the DASH diet was associated with higher odds for carotid plaques (OR = 1.18, $95\%$ CI (1.02, 1.36), $$p \leq 0.027$$, adjusted). Odds for plaque presence were higher for men, older age, low education, hypertension, hyperlipidemia and smoking. In this study, the intake of most supplements, as well as DASH or Mediterranean diet, was not significantly associated with GSM for women or men. Future research is needed to clarify the influence, especially of the folate intake and DASH diet, on the presence and vulnerability of plaques. ## 1. Introduction Atherosclerotic cardiovascular disease (CVD) is widespread and is a leading cause of morbidity and mortality worldwide [1,2]. Atherosclerosis refers to a slowly progressive process of plaque formation in the vessel wall. Plaque rupture, platelet activation and, consequently, secondary thrombosis may occur during the progression of the disease [3,4,5,6]. Thereby, the risk of cardio- and cerebrovascular events is increased. Ischemic strokes are caused by the rupture of plaques in the carotids in about $15\%$ of cases [7,8]. The stability and vulnerability of plaques have a major impact on the risk of plaque rupture [9]. Stable plaques consist of a high amount of fibrous tissue and calcification. Unstable plaques, in contrast, are rupture-prone due to high lipid content, an oftentimes necrotic core and intra-plaque hemorrhage [10,11]. Measurement of carotid intima-media thickness (cIMT) and its progression is an established and widely used prognostic biomarker for future CVD events [12,13]. However, it does not provide any information about plaque composition and, thus, the vulnerability of plaques. Therefore, the measurement of plaque gray-scale median (GSM) may improve the detection of vulnerable plaques. GSM provides additional information on plaque morphology due to the measurement of densitometry of the plaque [14,15]. The previous literature has demonstrated that GSM is a suitable measurement to quantify and assess the vulnerability of carotid plaques based on their echogenicity on B-mode ultrasonography [14,16,17]. GSM correlates with histopathological findings in patients after carotid endarterectomy and thus reflects the composition of plaques [10,18,19,20,21,22]. More precisely, high GSM values correlate with predominantly echogenic, stable plaques with a higher grade of calcification and fibrosis, whereas low GSM values are associated with echolucent, vulnerable plaques [11,14]. Low GSM values in carotid plaques are associated with an increased risk for CVD events, especially ischemic strokes [23,24,25]. GSM and cIMT are associated with different risk factors. While cIMT correlates with traditional risk factors such as hypertension and smoking status, GSM correlates with other traditional risk factors like dyslipidemia as well as with markers of inflammation and oxidative stress [26,27]. This suggests that cIMT and GSM may depict different aspects of atherosclerosis, with GSM relating more to metabolic aspects [28]. In addition to GSM, the presence of carotid plaque is associated with the incidence of CVD events [29,30] and is further an established ultrasound surrogate of CVD [31,32]. Nutritional aspects are known to play a relevant role in the development of atherosclerosis and in the formation of plaques [33]. Hence, it is of great interest how both can be influenced through diet. CVD may be prevented in up to $90\%$ of cases by a healthy lifestyle [34]. Numerous studies investigating the association between dietary patterns and CVD have included Dietary Approaches to Stop Hypertension (DASH) diet and the Mediterranean diet. Both adherence to the DASH diet and the Mediterranean diet are usually higher in women than in men [35,36,37]. Mediterranean diet has shown a primary prevention effect on CVD events as well as a tendency to slow down carotid plaque progression [38,39,40,41,42,43,44]. However, data on the association with GSM has been missing until now, and even the association between the Mediterranean diet and cIMT remains to be confirmed [45]. DASH diet is associated with fewer CVD events and lower cIMT values, while data regarding the association with GSM or plaque presence is not available [35,46,47]. Furthermore, dietary supplement intake is widespread in the general population [48]; for example, more than half of US adults take at least one supplement daily [49,50]. For Germany, the EPIC-Heidelberg cohort has shown an increasing prevalence of up to about $45\%$ for vitamin/mineral supplement intake in a follow-up reassessment (2004–2006) [51]. The EPIC-Heidelberg cohort and many other studies have also revealed that women, in particular, are more likely to take supplements compared to men [49,51,52,53,54]. The main reasons for intake are general health and well-being and filling nutrient gaps [55]. According to previous studies, the associations between dietary supplements and CVD or cIMT remain unclear. Some data on B vitamins exist, especially for folic acid supplementation, which appears to be associated with benefits for CVD and, in particular, stroke risk [56,57,58,59]. Studies investigating associations between dietary supplement intake with GSM or plaque presence are lacking. This study, therefore, aimed to examine associations between the dietary patterns Mediterranean diet and the DASH diet as well as dietary supplements (specifically multivitamins, multiminerals, calcium, magnesium, vitamin B and folate) and (a) the presence or (b) GSM of carotid plaques as predictors of CVD in women and men. ## 2.1. Study Population and Study Design This study is part of the Hamburg City Health Study (HCHS). HCHS is a prospective, single-center, population-based cohort study. It aims to identify risk and prognostic factors of main chronic diseases. Participants must be inhabitants of Hamburg, Germany, at the time of enrollment, aged 45–74 years and must provide sufficient language skills for participating in the study. Participants are chosen randomly via the registration office. They sign an informed consent and undergo an extensive baseline evaluation. Detailed information on the HCHS has been published separately [60]. For this study, data from the first sub-cohort ($$n = 10$$,000) was used. Data acquisition took place between 8 February 2016–30 November 2018. ## 2.2. Ultrasound Images B-mode duplex sonography was performed by trained study assistants using a Siemens SC2000® Ultrasound System and a 7.5 Mhz broadband linear transducer. Measurement of the cIMT was performed three times. The carotid bulb, common carotid artery and internal and external carotid artery were then scanned for plaques using the longitudinal view of carotid artery. A plaque was defined as a local cIMT ≥ 1.5 mm. ## 2.3. Gray-Scale Median Carotid ultrasound scans were saved in DICOM (digital imaging and communications in medicine) format after performing the sonography. In the next step, echogenicity of carotid plaques was analyzed using software that was specifically written for this project’s purpose, based on the open-source project JS Paint [61,62]. Plaques were segmented manually by outlining the plaques using the computer mouse. One additional marker was drawn in the vessel lumen, and a second in the adventitia. Each plaque was segmented twice by different operators to minimize interobserver reliability. Interobserver reliability was determined based on a random sub-sample of 135 ($5\%$) participants that were evaluated by all observers. Remeasurements of outliers were performed. Images were saved as portable network graphics (PNG) files after segmentation. Next, image brightness was normalized using the vessel lumen as the reference structure for darkness (GSM = 0) and the adventitia as the reference structure for brightness (GSM = 190). Both grayscale values were chosen based on the existing literature [63]. *In* general, GSM values range from 0, indicating total black, to 255, indicating total white. Noise reduction and cropping of the images were performed automatically. Finally, minimum, maximum, mean and median grayscale values were calculated and output in a comma-separated values (CSV) file. Primary outcome of the present study was the mean value over all individual echogenicity measurements as numerical variable. ## 2.4. Questionnaires and Dietary Scores Dietary habits and intake of nutrition supplements were assessed in questionnaires. For dietary intake, the food frequency questionnaire (version 2, FFQ2) developed for the European Perspective Investigation into Cancer and Nutrition (EPIC) study was used [64]. It samples information on frequency and portion size of 102 food items consumed during the previous year. Information was collected and analyzed in terms of energy intake, food groups and nutrients. The validated German translation of the Mediterranean Diet Adherence Score (MEDAS) was used for evaluating adherence to a Mediterranean diet [65]. It contains twelve questions on food items and two questions on food habits (Supplementary Material Table S1). For each item, a score of 0 indicates a non-adherence, whereas a score of 1 indicates adherence. Finally, the score was grouped by quantiles into the categories 0–3, 4, 5 and 6+. Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet was assessed using a scoring system adapted from Folsom et al. [ 66]. The score includes ten items on consumption of grains, vegetables, fruits, dairy, meat/poultry/fish, nuts/seeds/legumes and sweets (obtained from raw data) and average daily intake of nutrients (saturated fat, fat, sodium) (Supplementary Material Table S2). Each item was scored from 0 to 1. Finally, the score was grouped by quantiles into the categories 0–3.5, 3.6–4.5, 4.6–5.0 and 5.1+. The FFQ2 continued to ask about the use of dietary supplements for at least one month in the last twelve months, specifically multipreparations (multivitamin or multimineral preparations or both) or 14 single and simple combination preparations, as well as nine natural health products. For this study, data on multivitamin and multimineral preparations as well as calcium, magnesium, vitamin B complex and folic acid, were included. ## 2.5. Statistical Analysis In the descriptive analysis, continuous data are presented as the median and interquartile range (IQR), and categorical data as absolute numbers and percentages. Multiple linear regressions were used to assess the association between echogenicity and dietary and supplement intake, i.e., nutritional supplements, DASH diet, MEDAS within GSM-sub-cohort ($$n = 2163$$). All models were estimated separately for males and females and adjusted for not performing any sports (examined as ‘never performing sports except for cycling or walking’), age, socioeconomic status index (including education, profession, salary), body mass index (BMI), smoking status, energy intake (kcal), dyslipidemia, hypertension, diabetes mellitus, myocardial infarction, heart failure, atrial fibrillation, history of stroke or transient ischemic attack (TIA), peripheral arterial disease, estimated glomerular filtration rate (eGFR), lipid-lowering drugs, antihypertensive medication, antidiabetic medication, use of antiplatelets. Central results were presented as betas with $95\%$ confidence intervals. We did not adjust for multiple comparisons. We imputed missing values by multivariate imputation by chained equations separately for twenty copies of the data with ten iterations. Subsequently, estimates were averaged, and standard errors were adjusted using Rubin’s rules [67]. We performed additional analysis regarding the presence of at least one carotid plaque using multiple logistic regressions within a full cohort of 10,000 participants. For the full-adjusted model, age, sex, education, body-mass index, diabetes mellitus, arterial hypertension, hyperlipidemia, smoking status, heart failure, atrial fibrillation, myocardial infarction, stroke and sports were used for adjustment. Education was divided into three categories (low, medium and high) based on the International Standard Classification of Education (ISCED 1011). Statistical significance was defined as an α = 0.05. We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [68]. All analyses were performed in R version 4.0.3. ## 3.1. Baseline Characteristics of GSM-Sub-Cohort From the HCHS cohort of 10,000 participants, GSM was assessed for 2163 participants having at least one carotid plaque (Figure 1). The baseline characteristics of these participants, consisting of 921 ($42.6\%$) women and 1242 ($57.4\%$) men, are shown in Table 1. Here, the median age of women and men at recruitment was 68 (IQR [62, 73]) years. Obesity was found in 272 ($21.9\%$) men and 187 ($20.3\%$) women. Overall, 486 ($22.5\%$) were current smokers. Of men, 397 ($32.0\%$) were not performing any sports, whereas 249 ($27.0\%$) women were not exercising. Women reached higher MEDAS scores more often than men; women reached a score of 6+ points in $37.8\%$ of the cases, whereas men reached a score of 6+ points in $16.1\%$. A similar trend holds true for the DASH score: $31.1\%$ of women and $14.2\%$ of men achieved a score of 5.1+ points. Men reached the largest distribution range at 0–3.5 points ($31.8\%$) and 3.6–4.5 points ($30.4\%$). In comparison, fewer women had low score values. A total of 755 ($34.9\%$) participants had an intake of any supplement. Intake was higher among women ($43.8\%$) than men ($23.8\%$). As Table 1 shows, for each of the examined supplements, intake was higher in women than in men, with the exception of multivitamins. Here, an equal supplementation distribution of $7.7\%$ each for women and men was assessed. Figure 2 shows the distribution of GSM levels separately for men (shown in blue) and women (shown in red). The median GSM was 56.50 with IQR between 46.00 and 68.50 for men and 55.80 with IQR between 44.25 and 70.33 for women. ## 3.2. Linear Regression of Nutrition Parameters and Examined Supplements with GSM in Women and Men Table 2 shows the results of multivariate linear regression models of nutrition parameters, examined supplements and GSM in men and women of the GSM-sub-cohort ($$n = 2163$$). A significant correlation could only be found for folic acid intake in men (GSM 9.12 ($95\%$ CI (1.37, 16.86), $$p \leq 0.021$$). A non-significant opposing trend was found in women with GSM of −2.50 ($95\%$ CI −9.31, 4.31), $$p \leq 0.472.$$ No significant associations could be found between dietary patterns or intake of the other examined supplements and GSM. ## 3.3. Results of Logistic Regression Regarding the Presence of Carotid Plaques The results of logistic regressions with multivariable adjustments as OR related to the reference category for the presence of at least one carotid plaque in full HCHS-sub-cohort, including 10,000 participants, are shown in Table 3. In all three adjusted logistic regression models, the odds for the presence of at least one carotid plaque were significantly higher among the categories men, older age, low education, arterial hypertension, hyperlipidemia and smoking status (Supplementary Material Table S3). A high DASH score showed significantly increased odds for the presence of at least one plaque compared to intermediate score values in adjusted models (OR = 1.18, $95\%$ CI (1.02, 1.36), $$p \leq 0.027$$). In adjusted models, no significant association between MEDAS or any supplement intake and the presence of carotid plaque was found. ## 4. Discussion GSM was not associated with Mediterranean or DASH nutritional patterns and most supplements in an elderly German population. Folic acid intake was significantly associated with higher GSM only in men. A high DASH score was significantly associated with increased odds for the presence of carotid plaques compared to intermediate score values. However, in all other fully adjusted analyses, no significant associations were found between DASH/Mediterranean diet and plaque presence. This study is the first to investigate associations between GSM and the Mediterranean Diet or DASH diet as well as the supplements examined in this study, plus the relation between the presence of carotid plaques with the DASH diet or supplement intake. There are only a few studies that have investigated plaque prevalence and MEDAS. The study’s baseline data fit with the demographics of previous studies, which have also shown that both following healthy dietary patterns—measured by high adherence scores—and taking supplements are more prevalent among women [35,36,37,49,53,69,70]. The significantly increased GSM in men taking folic acid should be considered with caution because only 30 men ($2.4\%$) supplemented folic acid. Future studies should investigate the effect of folic acid on plaque vulnerability. In addition to that, the clinical implication should be mentioned. If the observed evidence of a 9.12 increased GSM by folic acid intake ($95\%$ CI (1.37, 16.86), $$p \leq 0.021$$) is not coincidental, this positive effect, however, is not necessarily clinically relevant. However, three reviews revealed a reduced stroke risk for folic acid supplementation and, thus, beneficial effects for stroke prevention [57,58,59]. Again, further studies are necessary to determine which GSM changes are clinically relevant to outcomes related to CVD, e.g., ischemic stroke. Thus, the findings probably exist due to confounders like traditional cardiovascular risk factors considering that supplement users tend to have more healthy habits than non-users [55]. Several studies have shown that the presence of carotid plaques is particularly associated with older age, male sex [71] and smoking [72], but also linked to diseases such as hypercholesterolemia [31], hypertension, diabetes mellitus [73,74] and cardiac disease [75]. Our findings are in line with previous studies that revealed the following associations: In adjusted regression models, the odds of having at least one plaque significantly increased in men, older age, low education, arterial hypertension, hyperlipidemia and smoking status. Evidence for correlations between supplement intake or DASH diet with plaque presence is missing in the existing literature. For any supplement intake, the odds of carotid plaque presence were lower, although no significant trend was observed after adjustment. Contrary to our expectations, we have found a significant association between high DASH scores and a more frequent occurrence of carotid plaques in adjusted models. In contrast, Fung et al. showed that adherence to the DASH diet is associated with a reduced risk of CVD events such as stroke [46]. The reason for our findings could be that people having cardiovascular diseases are more willing to follow healthy nutrition recommendations. Likewise, individuals who have received nutritional counseling cause of their CVD are more likely to report healthy nutrition in questionnaires (recall/reporting bias). We found an absence of proof regarding the association between MEDAS or supplement intake and the presence of carotid plaque. Previous studies confirm that there may be no association between MEDAS and the presence of carotid plaques. For example, neither Gardener et al. in the Northern Manhattan Study (NOMAS) [38] nor Mateo-Gallego et al. in the Aragon Workers’ Health Study (AWHS) [41] observed an association between the Mediterranean diet and plaque presence. Jimenez-Torres et al. also did not find any effect of the Mediterranean diet on the number of carotid plaques [39]. In contrast, a Croatian study in a population of HIV-infected patients found that lower adherence to the Mediterranean diet was associated with increased odds of subclinical atherosclerosis defined as cIMT ≥ 0.9 mm or ≥ 1 carotid plaque [76]. Although no clinically relevant association between the Mediterranean/DASH diet or supplement intake and GSM has been found, some studies have shown associations between these lifestyle adjustments and the CVD predictor cIMT. For example, Maddock et al. describe significantly lower cIMT for greater adherence to the DASH diet [35]. Because GSM and cIMT may be associated with different risk factors [26,27] and represent different aspects of atherosclerosis [28], it is worth doubting whether GSM is an appropriate parameter for detecting associations with dietary adjustments. Perhaps other methods are more useful for investigating associations and, finally, causal influences on clinical outcomes related to diet or supplements. For example, using a juxtaluminal black area (JBA) instead of GSM could provide even more information [22]. While the GSM value is based on the echolucency measurement of the whole plaque, JBA focuses on a low GSM plaque area near the vessel lumen. Salem et al. found a stronger association between histological findings and JBA than with GSM [21]. In summary, further research regarding the relationship between GSM and the presence of carotid artery plaques with nutrition patterns or supplement intake is needed. ## Strengths and Limitations The present study consists of an exceptionally large sample size of 2163 participants within the GSM-sub-cohort and 10,000 participants in an additional analysis with the presence of at least one plaque. Almost no exclusion criteria (only insufficient German language skills and incapability to travel to the study center and to cooperate in the investigations) and random invitations via the registration office are used for the selection of study participants for HCHS. Still, selection bias cannot be excluded for certain. HCHS participants tend to be more health-conscious and educated, showing fewer cardiovascular risk factors than the general German population [77]. Furthermore, the HCHS study population consists of middle-aged individuals living in Hamburg, so generalizations to other age groups and individuals living in rural areas should not be made without careful consideration. Being a cross-sectional analysis, no causal conclusions can be made. Data on dietary parameters were collected by self-reporting in questionnaires, so there is a risk of reporting and recall bias. In addition, no data were collected on the dose of the supplements nor on the continuity or duration of intake. Furthermore, adjustments for multiple comparisons were not performed. This could lead to dismissing the null hypothesis hastily, especially in consideration of the wide variety of supplements. Another limitation could be our grouping of the dietary scores in the GSM regression models (MEDAS $\frac{4}{5}$/6+ points, DASH 3.6–4.5, 4.6–5, 5.1+) since differences in adherence between the groups are small. Comparison of, for instance, the highest tertial of adherence vs. the lowest tertial of adherence might have been more informative. In addition, adherence to the Mediterranean diet was low in our northern German participants. Another dietary pattern, e.g., an anti-inflammatory or Nordic diet, could have shown higher prevalence rates and thus more information. Additionally, in the present study, GSM measurement was performed based on 2D ultrasound scans and thus cannot present information on the whole plaque as 3D files may have done. Lastly, multiple trained operators drew in the plaques for the GSM determination. This leaves room for intra-observer and inter-observer variability. Plus, the reference values for normalization of the image brightness also had to be drawn in. This can lead to a bias in true GSM values if, for instance, an expert draws in an area that is too dark for the adventitia, the normalization thus becoming incorrect [78]. ## 5. 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--- title: Effects of Semaglutide and Empagliflozin on Inflammatory Markers in Patients with Type 2 Diabetes authors: - Ingrid Reppo - Maili Jakobson - Vallo Volke journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10054691 doi: 10.3390/ijms24065714 license: CC BY 4.0 --- # Effects of Semaglutide and Empagliflozin on Inflammatory Markers in Patients with Type 2 Diabetes ## Abstract Low-grade inflammation is associated with complications of type 2 diabetes. Glucagon-like peptide-1 receptor agonists and sodium-glucose transporter-2 inhibitors have shown cardioprotective effects that are independent of their glucose-lowering effects. Cardio-protection could be mediated by the anti-inflammatory effects of these medications, but there is currently limited evidence to support this hypothesis. We conducted a prospective clinical study in patients with type 2 diabetes requiring treatment intensification. Ten patients were assigned to receive empagliflozin 10 mg and 10 patients to receive s/c semaglutide (titrated to 1 mg once a week) in a non-randomised manner. All parameters were measured at baseline and after 3 months. Fasting plasma glucose and glycated haemoglobin improved significantly in both treatment groups, with no between-group differences. Body weight and body mass index reduced significantly more in the semaglutide group, whereas waist circumference decreased only in the empagliflozin group. There was a trend for high-sensitivity CRP reduction in both treatment groups that did not reach statistical significance. Interleukin-6 and the neutrophil-to-lymphocyte ratio did not change in either group. Ferritin and uric acid decreased significantly only in the empagliflozin group, and ceruloplasmin decreased significantly only in the semaglutide group. Though there were clinically meaningful improvements in diabetes control in both treatment arms, we could detect only minor changes in some inflammatory markers. ## 1. Introduction The use of novel classes of diabetes medications, such as glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium-glucose transporter-2 (SGLT-2) inhibitors, has been associated with cardiovascular benefits. The cardioprotective effects of these drugs seem to be independent of their glucose-lowering effects [1,2,3]. Both of the drug classes have multiple auxiliary effects besides glucose control, and the potential mechanism mediating cardiovascular benefit remains elusive. Low-grade inflammation is associated with insulin resistance and hyperglycaemia [4,5,6,7,8] and is a known driver of complications of type 2 diabetes [9]. Both of these new drug classes have demonstrated inconsistent anti-inflammatory effects in clinical trials. The SGLT-2 inhibitor canagliflozin has been shown to reduce interleukin-6 (IL-6) levels compared to sulphonyl urea (glimepiride) in patients with type 2 diabetes, but a trend towards a decrease in C-reactive protein (CRP) levels in the canagliflozin group did not reach statistical significance [10]. In another study, empagliflozin and canagliflozin reduced circulating levels of IL-6 in men with type 2 diabetes [11]. Moreover, Iannantuoni et al. showed a significant decrease in high-sensitivity C-reactive protein (hsCRP) levels in type 2 diabetic patients, after a 24-week treatment with empagliflozin [12]. In a trial comparing oral semaglutide (14 mg) and empagliflozin (25 mg) in type 2 diabetic patients only semaglutide reduced CRP [13]. In a weight management trial in non-diabetic obese patients, oral semaglutide reduced hsCRP by $43\%$ compared to placebo, but the statistical significance was lost after adjusting for changes in body weight [14]. Liraglutide has been shown to decrease IL-6 in type 1 diabetic patients [15] and hsCRP in patients with type 2 diabetes [16]. Data regarding the possible direct effect of SGLT-2 inhibitors and GLP-1 RAs on immune cells in type 2 diabetes patients are scarce. Borzouei et al. found that empagliflozin showed anti-inflammatory effects by reducing the proliferation of Th cells, decreasing Th17-related factors, and increasing regulatory T cell properties [17]. Hence, the anti-inflammatory effect is one of the potential mechanisms to consider in the context of the cardiovascular benefits of novel antidiabetics, but the evidence is still limited. The current study thus aims at directly comparing the effects of s.c. semaglutide and empagliflozin. ## 2. Results The baseline characteristics of the study participants are given in Table 1 and Supplementary Table S1. All recruited patients completed the 3-month treatment period with either empagliflozin or semaglutide. On week nine, all patients in the semaglutide group reached the target dose of 1 mg once a week. ## 2.1. Glycaemic Control The HbA1c and fasting plasma glucose decreased significantly in both treatment groups. There was no between-group difference in the change in HbA1c or fasting plasma glucose levels (Table 1, Figure 1A). ## 2.2. Body Weight, BMI, and Waist Circumference The body weight and body mass index (BMI) changed more in the semaglutide group. There was a significant decrease in waist circumference in the empagliflozin group but not in the semaglutide group (Table 1, Figure 1B). ## 2.3. Inflammatory Parameters The classical inflammatory markers hsCRP and IL-6 did not change during the 3-month treatment period in either treatment group (Table 1, Figure 2A,B). Acute-phase protein ferritin decreased significantly in the empagliflozin group but not in the semaglutide group (Table 1, Figure 2C). Ceruloplasmin, another acute-phase protein produced in the liver that plays a role in copper metabolism and may have a role in the pathogenesis of metabolic diseases such as type 2 diabetes [18], decreased significantly in the semaglutide group but not in the empagliflozin group (Table 1, Figure 2D). ## 2.4. Neutrophil-to-Lymphocyte Ratio The neutrophil-to-lymphocyte ratio (NLR) is an indicator of inflammation and a predictor of mortality [19], and an increased NLR is positively associated with diabetes complications [20,21,22]. The neutrophil-to-lymphocyte ratio did not change in either treatment group (Figure 3). ## 2.5. Uric Acid The uric acid level has been positively related to many inflammatory markers, including CRP [23]. In the semaglutide group, there was no significant change in uric acid level ($$p \leq 0.256$$). In the empagliflozin group, there was a significant decrease in the uric acid level ($$p \leq 0.0104$$) (Figure 4). ## 2.6. Glycaemic Control The HbA1c and fasting plasma glucose decreased significantly in both treatment groups. There was no between-group difference in the change in HbA1c or fasting plasma glucose levels (Table 1, Figure 4A). ## 2.7. Body Weight, BMI, and Waist Circumference The body weight and body mass index (BMI) changed more in the semaglutide group. There was a significant decrease in waist circumference in the empagliflozin group but not in the semaglutide group (Table 1, Figure 4B). ## 2.8. Erythrocyte and Iron Metabolism Parameters The results of red blood cells and iron metabolism parameters are shown in Supplementary Table S2. Haemoglobin and haematocrit increased significantly in the empagliflozin group. Mean corpuscular haemoglobin, iron, soluble transferrin saturation, and transferrin did not change in either treatment group. ## 3. Discussion The principal finding of our study is that subtle changes in some inflammatory markers occurred during a 3-month treatment with s.c. semaglutide and empagliflozin in this small clinical trial on T2DM patients with suboptimal glycaemic control. Patients who received s.c. semaglutide had a significantly longer diabetes duration, used fewer statins, and tended to receive more anti-diabetic drugs than patients in the empagliflozin group. Though the differences in background medications did not reach statistical significance, their effect on the study results cannot be excluded. The 3-month treatment resulted in clinically meaningful reductions in fasting glycaemia, HbA1c, body weight, and BMI in both treatment groups. The improvement in glycaemic control was comparable between the groups; hence, any inter-group differences can be considered independent of the medications’ anti-hyperglycaemic effect. Interestingly, the waist circumference decreased significantly in the empagliflozin group but not in the semaglutide group, where the weight and BMI reductions were more prominent. This finding may indicate an initial difference in the pattern of weight loss between the drug classes. However, a longer study has demonstrated a rather similar change in waist circumference with empagliflozin and oral semaglutide after 52 weeks of treatment [13]. We could not detect any significant changes in hsCRP with either medication, although there was a trend towards a decrease in hsCRP in both treatment groups. Studies with GLP-1 RAs have consistently shown reductions in hsCRP [13,14,16], but the effect of SGLT-2 inhibitors on hsCRP has been less obvious [10,12]. Ianntuoni et al. reported a significant reduction in hsCRP in 15 type 2 diabetic patients who received empagliflozin 10 mg once a day for 24 weeks [10,12]. On the other hand, Garvey et al. evaluated the effect of canagliflozin and glimepiride on inflammatory biomarkers in a much larger group of type 2 diabetic patients (200 patients in total) and a longer study (52 weeks), which only detected a trend towards a decrease in CRP levels [10]. We could not see significant changes in IL-6 in either treatment arm, though IL-6 has decreased in previous studies with SGLT-2 inhibitors [10,11]. Our results are in line with a study showing no effect of liraglutide on IL-6 in type 2 diabetic patients [24]. Our study showed clinically significant improvements in fasting plasma glucose and HbA1c in both treatment groups, but contrary to previous studies with type 2 diabetic patients [22,25] where improved glycaemia was associated with NLR reduction, we did not detect any significant changes in the neutrophil-to-lymphocyte ratio in either treatment arm. There was a significant decrease in ferritin levels in the empagliflozin group, whereas ferritin levels were stable in semaglutide-treated patients. It is important to point out that the baseline ferritin level was significantly higher in the empagliflozin group vs. the semaglutide group, a drawback of the non-randomised design of the study. This baseline difference can be partially explained by the predominantly male patients in the empagliflozin group, as men have higher ferritin levels [26]. Moreover, six patients in the empagliflozin group had ferritin levels over the upper limit of normal (ULN), while all levels in the semaglutide group were within the reference range. Empagliflozin has been shown to decrease ferritin levels in previous studies [27,28]. In our study, there were no changes in other inflammatory markers in the empagliflozin group, and the decrease in ferritin was accompanied by a significant increase in haemoglobin and haematocrit. Hence, we can conclude that these changes probably reflect better iron handling and not an anti-inflammatory effect. This is further supported by the trend towards an increase in sTfR in the empagliflozin group, which reflects increased erythropoietic activity. It would be interesting to see whether SGLT-2 inhibitors may change the membrane fluidity of red blood cells, a potential novel marker of diabetes complications [29,30]. In our study, ceruloplasmin levels behaved differently from ferritin. The ceruloplasmin level decreased significantly in the semaglutide group but not in the empagliflozin group. This finding is in line with previous studies by Savchenko et al. [ 31] and Ekhzaimy et al. [ 32], which have also demonstrated a decrease in ceruloplasmin levels after treatment with GLP-1 RA liraglutide. Interestingly, the study by Sharma et al. [ 33] showed that hyperglycaemia correlates positively with ceruloplasmin level and helps to discriminate diabetic patients from non-diabetics. However, we cannot exclude the possible confounding effect of weight change in our study. Uric acid decreased significantly after treatment with empagliflozin but not with semaglutide. As other inflammatory markers did not accompany the decrease in uric acid, and SGLT-2 inhibition has been demonstrated to increase the urinary excretion of uric acid [34], this decrease does not seem to reflect a direct anti-inflammatory effect. To summarise, the treatment effects on biomarkers of inflammation in the current study remained modest, and semaglutide outperformed empagliflozin. The key change was a decrease in ceruloplasmin levels with semaglutide. We could also detect a decrease in hsCRP with both drugs that did not reach statistical significance. It is possible that a larger sample size or longer duration could result in statistical significance. The hsCRP has been considered a novel risk factor for cardiovascular events [35]. However, linking the change in hsCRP directly with the treatment effect of cardioprotective drugs has been challenging. Colchicine is a potent anti-inflammatory drug that prevents cardiovascular events after an acute myocardial infarction. Still, the drug did not change hsCRP or leukocyte counts in these patients [36]. In our study, there were no changes in IL-6 and NLR. Collectively, we were unable to confirm major effects on inflammatory parameters after treatment with s.c. semaglutide or empagliflozin. There are important limitations to our study. These include the open and non-randomised design, the small sample size, and the uneven sex distribution between treatment groups. Despite the non-randomised design of the study, the recruited patients had similar baseline characteristics regarding anthropometric and biochemical parameters. Due to the post hoc nature of the analyses, there are no prior power calculations for determining an adequate sample size. The list of measured inflammatory markers is not fully comprehensive, as the dataset of inflammatory markers was collected as part of exploratory outcomes and markers not routinely used were not measured. The strengths of our study include the prospective design, the use of an active comparator, and the exclusion of patients who were using medications that could affect inflammatory markers. We conclude that GLP-1 RAs and SGLT-2 inhibitors reduce the inflammatory markers to some extent, but this effect is not robust enough to explain the cardio-protection seen with these drug classes in type 2 diabetic patients. ## 4.1. Study Design We report the results of a prospective pragmatic clinical trial conducted in the Tartu University Hospital endocrinology outpatient clinic in patients with type 2 diabetes. The trial was designed to study the effects of semaglutide and empagliflozin on the secretion of adrenal hormones and intestinal microbiota composition. The primary endpoint of the trial will be reported elsewhere. The dataset of inflammatory markers reported here was collected as part of exploratory outcomes. ## 4.2. Inclusion Criteria The study inclusion criteria were: [1] age ≥ 18 years; [2] type 2 diabetes; [3] HbA1c < $10\%$; [4] body mass index (BMI) ≥ 32 kg/m2; [5] no change in diabetes treatment ≥ 90 days before recruitment to the study; [6] daily metformin dose ≥ 1.5 g; and [7] no prior GLP-1 RA or SGLT-2 inhibitor use. ## 4.3. Exclusion Criteria The exclusion criteria were: [1] use of oral or intravenous antibiotics ≤ 60 days before recruitment; [2] use of spironolactone ≤ 60 days before recruitment; [3] use of glucocorticoids, cytostatic medications, and biological treatments; [4] pregnancy; [5] use of oral contraceptives or hormone replacement therapy; [6] malignancy; [7] heart failure (NYHA class III-IV); and [8] liver failure. ## 4.4. Study Medications The decision to start GLP-1 RA semaglutide or SGLT-2 inhibitor empagliflozin was based on clinical judgement of the need for treatment intensification. The patient classification was completed by one investigator (IR). Semaglutide was started at 0.25 mg (s/c) once a week. If well tolerated, the dose of semaglutide was increased to 0.5 mg in week five and to 1 mg in week nine. In the empagliflozin group, a 10 mg daily dose was used. ## 4.5. Study Time Points The pre-specified time points for blood samples and clinical status reported here are baseline and 3 months after recruitment. Weight, height, waist circumference, and blood pressure were also measured at baseline and 3 months after recruitment. ## 4.6. Study Approvals The trial was approved by the Research Ethics Committee of the University of Tartu (290/T-20) and registered at Clinicaltrials.gov (NCT04151849). The study was conducted following the Declaration of Helsinki. Written informed consent was obtained from all subjects involved in the study. ## 4.7. Laboratory Analyses Fasting blood samples were obtained between 8 and 10 a.m. All laboratory parameters were measured at the accredited laboratory of Tartu University Hospital using standard methods. A turbidimetric immunoassay was used to measure hsCRP (Cobas 501, Roche Diagnostics GmbH, Germany), ceruloplasmin (Cobas Integra 400 Plus, Roche Diagnostics GmbH, Germany), soluble transferrin receptors (Cobas Integra 400 Plus, Roche Diagnostics GmbH, Germany), transferrin (Cobas 501, Roche Diagnostics GmbH, Germany), and transferrin saturation (Cobas 501, Roche Diagnostics GmbH, Germany). The enzymatic colorimetric method was used to measure uric acid (Cobas 501, Roche Diagnostics GmbH, Germany), and the electrochemiluminescence assay (ECLIA) was used to measure ferritin (Cobas e601, Roche Diagnostics GmbH, Germany) and IL-6 (Cobas e402, Roche Diagnostics GmbH, Germany). The complete blood count was analysed with a Sysmex XN-9000/XN-9100 analyser (Sysmex Corporation, Kobe, Japan). ## 4.8. Statistical Analyses and Data Presentation All data were analysed with GraphPad Prism 9.4.1 (GraphPad Software, Inc., Boston, MA, USA) and Microsoft Excel. The D’Agostino-Pearson normality test was used to verify a normal distribution. Normally distributed data were analysed with the paired or unpaired t-test as appropriate. The Wilcoxon matched-pairs signed-rank test or Mann–Whitney test was used to test paired and unpaired data that were not normally distributed. Fischer’s exact test was used for categorical variables. The level of statistical significance was set at $p \leq 0.05.$ Data are presented as mean ± standard deviation (SD). ## 5. Conclusions The current study compared the effects of 3-month treatment with s.c. semaglutide and empagliflozin on inflammatory markers in patients with type 2 diabetes. Though there were clinically meaningful improvements in diabetes control in both treatment arms, we could detect only minor changes in some inflammatory markers. ## References 1. 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--- title: 'Cardiovascular Risk Factor Control in 70- to 95-Year-Old Individuals: Cross-Sectional Results from the Population-Based AugUR Study' authors: - Ferdinand J. Donhauser - Martina E. Zimmermann - Anna B. Steinkirchner - Simon Wiegrebe - Alexander Dietl - Caroline Brandl - Ralph Burkhardt - André Gessner - Frank Schweda - Tobias Bergler - Elke Schäffner - Carsten A. Böger - Florian Kronenberg - Andreas Luchner - Klaus J. Stark - Iris M. Heid journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054695 doi: 10.3390/jcm12062102 license: CC BY 4.0 --- # Cardiovascular Risk Factor Control in 70- to 95-Year-Old Individuals: Cross-Sectional Results from the Population-Based AugUR Study ## Abstract Cardiovascular risk factors such as high glucose, LDL-cholesterol, blood pressure, and impaired kidney function are particularly frequent in old-aged individuals. However, population-based data on the extent of cardiovascular risk factor control in the old-aged population is limited. AugUR is a cohort of the mobile “70+”-year-old population of/near Regensburg, recruited via population registries. We conducted cross-sectional analyses assessing the proportion of AugUR participants with LDL-cholesterol, HbA1c, or blood pressure beyond recommended levels and their association with impaired creatinine- and cystatin-based estimated glomerular filtration rate (eGFR, <60 mL/min/1.73 m2) or urine albumin–creatinine ratio (UACR, ≥30 mg/g). Among 2215 AugUR participants, $74.7\%$ were taking lipid-, glucose-, blood-pressure-lowering, or diuretic medication. High LDL-cholesterol at ≥116 mg/dL was observed for $76.1\%$ ($51.1\%$ among those with prior cardiovascular events). We found HbA1c ≥ $7.0\%$ for $6.3\%$, and high or low systolic blood pressure for $6.8\%$ or $26.5\%$, respectively (≥160, <120 mmHg). Logistic regression revealed (i) high HbA1c levels associated with increased risk for impaired kidney function among those untreated, (ii) high blood pressure with increased UACR, and (iii) low blood pressure with impaired eGFR, which was confined to individuals taking diuretics. Our results provide important insights into cardiovascular risk factor control in individuals aged 70–95 years, which are understudied in most population-based studies. ## 1. Introduction The proportion of septuagenarians and octogenarians is constantly increasing in Western societies [1]. Moreover, the life expectancy of old-aged individuals is on the rise, which underlines the increased importance of the primary and secondary prevention of diseases, particularly cardiovascular disease, in the elderly. Common cardiovascular risk factors are increased blood pressure, LDL-cholesterol, and glucose concentrations. These risk factors are particularly often elevated among old-aged individuals [2,3,4]. Elevated levels are associated with an increased risk of cardiovascular disease, kidney damage, and increased mortality [5,6,7,8,9]. For old-aged individuals, also low blood pressure is associated with increased mortality [10,11,12]. There is a substantial debate on the old-aged individual’s benefit after lowering cholesterol levels [13,14], blood pressure [15,16], and HbA1c [17]. This debate can benefit from an understanding of the extent of cardiovascular risk factor control in the old aged. Several guidelines provide recommended levels to control LDL-cholesterol, HbA1c, and blood pressure, with partly different levels for the general population, for individuals at high cardiovascular risk, and for the old aged [7,8,9,18,19]. Medications to control these risk factors are the most commonly used drugs in the elderly [20]. Since impaired kidney function poses a substantial risk for cardiovascular events in itself [21], individuals with achieved lipid, glucose, or blood pressure control can be still at risk because of impaired kidney function. Unachieved control of LDL-cholesterol, HbA1c, and blood pressure is particularly relevant for individuals with concomitant low kidney function. Thus, a quantification of cardiovascular risk factor control should not lose sight of kidney function. Despite this debate, and the growing proportion of elderly in the population, observational data on the older population is scarce and the knowledge of the extent of cardiovascular risk factor control in old-aged individuals is limited [16,22,23]. This is related to challenges in conducting population-based studies in the elderly [24]. Including the old aged in population-based studies requires a study protocol and study program that is specifically tailored to their needs. Thus, most large-scale population-based studies exclude the old aged (e.g., UK Biobank and NAKO up to 69 years old [25,26]). We thus aimed to understand the extent of cardiovascular risk factor control—with and without medication intake—in the elderly. We also aimed to provide a joint view with concurrent impaired kidney function: with low creatinine and cystatin-based eGFR, which assess impaired filtration, and with high UACR, which is a marker of kidney damage. For this, we conducted a cross-sectional analysis of 2215 participants of the AugUR study. AugUR is a population-based study of individuals aged 70 to 95 years from Regensburg, Germany. This included a detailed assessment of medication intake, medical history, blood pressure, HbA1c, LDL-cholesterol, estimated glomerular filtration rate (eGFR) based on creatinine as well as cystatin C, and urine albumin–creatinine ratio (UACR). Our specific aims were (i) to assess the taken medication; (ii) to quantify the proportion of individuals with LDL-cholesterol, HbA1c, and blood pressure beyond recommended levels, among those treated and untreated; and (iii) to test the association of unachieved risk factor control with concurrent kidney function impairment. ## 2.1. Study Design and Study Population AugUR (Age-related diseases: understanding genetic and non-genetic influences—a study at the University of Regensburg) is a prospective cohort study, designed to understand the extent and determinants of common diseases in the elderly. Study design, protocols, and inclusion criteria were described in detail previously [27]. Briefly, a random sample of individuals aged at least 70 years, living in the area of Regensburg, a city of around 150,000 inhabitants in the south-east of Germany, was obtained from a population registry and contacted by mail. Among 13,522 individuals contactable by mail, 2449 individuals participated in the baseline assessment conducted in the years 2013 to 2019 (net response: $18.1\%$). Participants were required to reach the study center independently and answer all questions personally. Therefore, the AugUR participants were physically and mentally relatively healthy and reflected the mobile proportion of the old-aged population. The study program at the study center, the University Hospital Regensburg, included a standardized in-person interview, medical exams, as well as blood and urine collection. This work presents cross-sectional analyses using the AugUR baseline data. The study was approved by the Ethics Committee of the University of Regensburg, Germany (vote 12-101-0258) and conducted according to the principles expressed in the Declaration of Helsinki. All study participants provided written consent after being informed about the study. ## 2.2. Assessment of Medication Intake AugUR participants were requested to take their medication packages/blisters and medication lists to the study center. Trained staff recorded all currently taken medication in the database. This database was linked with the Anatomical Therapeutic Chemical (ATC) classification to determine and record the active ingredient(s) [28]. For this work, three broad medication groups were defined as established previously [29]: (i) lipid-lowering agents (ATC group C10); (ii) glucose-lowering drugs (ATC group A10); (iii) blood-pressure-lowering drugs as any of the following—diuretics (except high-ceiling diuretics), beta blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, renin inhibitors, calcium channel blockers, and other antihypertensives (ATC group C02). Refined subgroups according to active substances were defined where applicable. Plant, homeopathic, and anthroposophical substances were not considered. ## 2.3. Blood and Urine Biomarkers Collection and processing of biosamples were conducted following standard operation procedures developed for this study based on established methods and recommendations [30], as described previously [27]. Briefly, non-fasting blood samples were drawn in a sitting position after at least 5 min of resting. Mild venous stasis was applied for a maximum duration of 1 min. Blood was taken using a 21G multifly needle. Immediate measurements in fresh whole blood and serum were carried out on the same day. Samples for biobanking were processed immediately and stored at −80 °C. Midstream urine was collected and directly stored at −80 °C. Measurements in fresh samples were carried out by an external laboratory (Synlab, Regensburg, Germany). HbA1c was measured from EDTA-anticoagulated whole blood by applying ion-exchange high-performance liquid chromatography on a Bio-Rad Variant II Turbo, applying the Variant II Turbo HbA1c Kit 2.0 (Bio-Rad, Munich, Germany). LDL-, HDL-, and total cholesterol were quantified as mg/dl from serum on a Beckman AU 5400 analyzer using enzymatic tests OSR6183, OSR6187, and OSR6116, respectively (Beckman Coulter, Krefeld, Germany). Laboratory analyses from biobanked samples for creatinine, cystatin C, and albumin were performed in compliance with the “Guidelines of the German Medical Association for Quality Assurance of Medical Laboratory Tests” (RiLiBäK) at the Central Laboratory of the University Hospital Regensburg, which is accredited in accordance with the standard DIN EN ISO 15189. Creatinine from serum and midstream urine was enzymatically measured in individuals recruited in the years 2013–2015 (AugUR1, $$n = 1133$$) on a Siemens Dimension Vista 1500 (assay ECREA, Siemens Healthcare, Erlangen, Germany) or in those recruited from 2017 to 2019 (AugUR2, $$n = 1316$$) on a Roche cobas e801 (assay CREP2, Roche, Mannheim, Germany). Serum cystatin C was measured with immunoassays for AugUR1 on a Siemens Dimension Vista 1500 (assay CYSC) or for AugUR2 on a Roche cobas e801 (assay CYSC2). Urine albumin was measured with immunoassays for AugUR1 on a Siemens Dimension Vista 1500 (assay MALB) or for AugUR2 on a Roche cobas e801 (assay ALBT2). Comparability of methods for creatinine, cystatine C, and albumin was assessed following Clinical & Laboratory Standards Institute (CLSI) guidelines. ## 2.4. Assessment of Lifestyle Factors, Medical Conditions, and Chronic Diseases At the study center, lifestyle factors and medical history were assessed in a standardized face-to-face interview. Specifically, participants were asked if they had ever been diagnosed by a physician with hypertension, diabetes, stroke, or heart failure. Additionally, they were asked about any history of myocardial infarction, stent implantation, or bypass surgery; coronary artery disease (CAD) was defined if at least one of these three conditions was reported. We built a variable that included CAD or stroke (CAD/stroke). Previous work has shown high agreement for the self-report of diabetes, stroke, CAD, and physician-reported comorbidities in AugUR, but limited reliability of self-reported heart failure [31]. Smoking status was defined as ever versus never smoking. Measurements at the study center included height, weight, and blood pressure. Systolic and diastolic blood pressure (SBP/DBP) was measured by an automatic device 3 times after >5 min resting, using the average of the second and third measurements in the analyses. Obesity was defined as body mass index (BMI) ≥ 30 kg/m2. Hypertension was defined as blood pressure ≥ $\frac{140}{90}$ mmHg or if the individual reported a prior hypertension diagnosis and antihypertensive medication intake, as established previously [29]. Individuals who self-reported diabetes and/or antidiabetic medication intake were defined as diabetic [32]. Estimated glomerular filtration rate (eGFR) was assessed both creatinine-based and cystatin-based using the CKD-Epi equation [33,34]. Impaired glomerular filtration rate was defined as eGFR < 60 mL/min/1.73 m2, and albuminuria as UACR ≥ 30 mg/g [21]. Echocardiography was conducted in a subgroup of 796 participants. Ejection fraction was measured in the apical four-chamber view using Simpson’s method [35,36]. ## 2.5. Statistical Analysis We conducted cross-sectional analyses using the AugUR baseline data, including all participants with valid values for LDL-cholesterol, HbA1c, blood pressure, and medication intake. Continuous variables were reported as mean and standard deviation or as median and interquartile range. For categorical variables, percentages were reported. The distributions of cardiovascular risk factors were shown using box plots, separately for individuals with respective medication intake or without. We derived the proportion of participants at achieved cardiovascular risk factors as the proportion of individuals who had LDL-cholesterol, HbA1c, or blood pressure levels below recommended thresholds. For LDL-cholesterol, we considered the thresholds of the European Society of Cardiology and European Atherosclerosis Society (e.g., <116 mg/dL) [8]; for HbA1c, those of the American and the German Diabetes Association (<$7.0\%$, ≤$7.5\%$, respectively) [6,7]; for blood pressure, those of the European Society of Cardiology and the European Society of Hypertension (120–$\frac{140}{80}$–90 mmHg) [9]. Proportions of achieved levels were derived overall, by medication intake status, and separately for individuals with or without a prior diagnosis of CAD/stroke. In exploratory analyses, we tested whether women or men, old aged or very old aged (70–79, 80+), were more likely to have unachieved levels using logistic regression adjusting for CAD/stroke and, if applicable, diabetes (model I) and for respective medication intake (model II). We tested the association of unachieved levels with impaired kidney function: with creatinine- or cystatin-based eGFR < 60 mL/min/1.73 m2 or with UACR ≥ 30 mg/g. For this, we used multivariable logistic regression adjusted for age (continuous), sex, CAD/stroke, diabetes (if applicable), obesity, smoking, respective medication intake, and an interaction of unachieved levels with medication intake. Adjustment for CAD/stroke and diabetes was included to account for potential confounding by indication. No adjustment was made for heart failure, as self-reported heart failure is rather unreliable and the ejection fraction was only measured in a subgroup. In the sensitivity analyses, we applied a model without adjustment for CAD/stroke and diabetes and a model without obesity and smoking. The level of significance was set at $p \leq 0.05$, except for interaction terms ($p \leq 0.1$). RStudio for Windows, Version 1.4.1717, was used for the Loess function. Forest plots were designed with Microsoft Excel, Version 2022. For all other analyses, SPSS Statistics for Windows (IBM), Version 26.0, or R version 4.1.2 was used. ## 3.1. Three Quarters of the Participants Aged 70 to 95 Years Were Taking Medication for Cardiovascular Risk Factor Control Among the 2449 AugUR participants, we here analyzed the 2215 participants with valid values for LDL-cholesterol, HbA1c, blood pressure, and medication intake (Supplementary Figure S1). These individuals were aged 70 to 95 years (mean = 78.4 years), $47.4\%$ were men, $72.9\%$ had hypertension, $21.0\%$ diabetes, $15.0\%$ CAD, $29.9\%$ a creatinine-based eGFR < 60 mL/min/1.73 m2, $47.1\%$ a cystatin-based eGFR < 60 mL/min/1.73 m2, and $17.4\%$ had UACR ≥30 mg/g (Table 1). Among the 2215 participants, $34.9\%$ were taking lipid-lowering and $16.5\%$ glucose-lowering medication (Table 2). This was similar for the old and the very old aged ($$n = 1469$$, 70–79 years; $$n = 746$$, 80+ years, respectively; Table 2), but lipid-lowering medication was less frequent among women than among men ($29.5\%$ versus $40.8\%$, respectively; Table 2). Blood-pressure-lowering medication was taken by $67.7\%$, mostly RAAS inhibitors ($54.0\%$ of the 2215); few were taking GLP1 analogues or SLGT2 inhibitors. High-ceiling diuretics were taken by $12.9\%$, with a marked increase among the very old aged versus old aged ($18.6\%$ versus $9.9\%$); further, $27.5\%$ were taking other diuretics as part of antihypertensive therapy. Any of these medications were taken by $74.7\%$, and $25.3\%$ were taking none of these. A characterization of individuals by treated versus untreated status is given in Supplementary Table S1. ## 3.2. LDL-, HbA1c, and Blood Pressure Levels Differed between Treated and Untreated We compared quantitative risk factor levels by respective medication intake among the 2215 AugUR participants. We found (i) on average, lower LDL-cholesterol among treated compared to untreated (Figure 1A; mean = 118.4 mg/dL vs. 153.1 mg/dL, respectively; age- and sex-adjusted $p \leq 0.001$); (ii) markedly higher HbA1c among antidiabetic treated versus untreated (Figure 1B; mean = $6.73\%$ vs. $5.60\%$, respectively, age- and sex-adjusted $p \leq 0.001$); and (iii) similar systolic blood pressure values between treated and untreated (Figure 1C,D; SBP: mean = 131.9 mmHg vs. 131.7 mmHg, age- and sex-adjusted $$p \leq 0.552$$; DBP: mean = 75.4 mmHg vs. 77.6 mmHg, age- and sex-adjusted $p \leq 0.001$). There were few differences between the old and the very old or between men and women (Supplementary Figure S2). ## 3.3. Cardiovascular Risk Factor Control Was Partly Unachieved and Some Individuals Appeared Potentially Overtreated We quantified the proportion of the 2215 participants who had cardiovascular risk factors above recommended levels, indicating unachieved risk factor control. This yielded a diverse pattern (Table 3). ( i) LDL-cholesterol control was rather poor—few reached the recommended thresholds at <70 mg/dL or <100 mg/dL ($0.9\%$, $12.1\%$, respectively), while most ($76.1\%$) had high LDL-cholesterol levels ≥116 mg/dL [8]. Among individuals with lipid-lowering medication ($$n = 772$$, 322 of these with previous CAD or stroke), values at <116 mg/dL were achieved by $50.3\%$. This was similar for individuals with previous CAD or stroke ($$n = 473$$), who were mostly treated. However, 151 individuals with a previous CAD or stroke diagnosis reported no lipid-lowering medication intake and $83.4\%$ of these had values ≥116 mg/dL. (ii) HbA1c control was excellent; only $6.3\%$ had HbA1c ≥ $7.0\%$ [6]. However, 71 individuals treated with antidiabetic medication had levels <$6.0\%$ ($19.5\%$), considered too low by the American Diabetes Association [6]. Among the 1850 untreated individuals, $$n = 14$$ ($0.8\%$) had HbA1c ≥ $7.0\%$, which might indicate undetected diabetes. (iii) High SBP at ≥160 mmHg or DBP at ≥100 mmHg was rare ($6.8\%$ or $2.3\%$, respectively). However, a large number of individuals were at low levels (<120 mmHg or <80 mmHg) considered undesirable for old-aged individuals: $26.5\%$ had SBP <120 and $64.8\%$ DBP <80 mmHg. These low levels were particularly frequent among individuals taking diuretics ($31.7\%$ and $72.3\%$ among the $$n = 802$$). One may be interested in whether individuals with a prior CAD or stroke diagnosis were similarly or even better controlled for high blood pressure: this was rather similar ($94.1\%$ and $98.5\%$ at SBP < 160 or DBP < 100, respectively). In order to identify potential disparities in the proportion of unachieved levels, we evaluated the association of sex, age group (80+, 70–19 years), and their interaction on the risk of unachieved control. For this, we used logistic regression adjusted for CAD/stroke and diabetes (if applicable). We found that (i) women were more likely to be at unachieved LDL-cholesterol levels or too low blood pressure, and (ii) old men more likely at unachieved HbA1c or too high blood pressure levels compared to women or very old men (Supplementary Table S2). This was not mediated by a prior diagnosis of CAD/stroke or diabetes diagnosis (since this was adjusted for), nor a differential probability of treatment (further model adjusting for treatment, Supplementary Table S2). However, the dosages of medication intake were not ascertained here, and differential dosages or differential impacts of similar dosages might explain at least some of these differences. ## 3.4. Regarding the Cross-Sectional Association of Unachieved Cardiovascular Risk Factor Control with Impaired Kidney Function We evaluated the cross-sectional association of unachieved cardiovascular risk factor control with eGFR < 60 mL/min/1.73 m2 and UACR ≥ 30 mg/g. We used logistic regression adjusted for age, sex, prior diagnosis of CAD/stroke, diabetes (if applicable), obesity, smoking, the respective medication intake, and its interaction with risk factor control. In the sensitivity analyses, we applied a model without adjustment for CAD/stroke and diabetes and another model without adjustment for obesity and smoking, both yielding similar results (Supplementary Tables S4 and S5). For blood pressure, we tested high as well as low blood pressure (SBP ≥ 140 vs. 120–140 mmHg or DBP ≥ 90 vs. 80–90 mmHg; SBP < 120 mmHg vs. 120–140 mmHg or DBP < 80 mmHg vs. 80–90 mmHg). We found LDL-cholesterol levels ≥116 mg/dL to be not associated with the risk for impaired creatinine-based eGFR, but with a decreased risk for impaired UACR (OR = 0.754, $$p \leq 0.049$$; Figure 2, Supplementary Table S3), without interaction by treatment status. We found unachieved HbA1c levels (e.g., ≥$7.0\%$) significantly associated with a ~3-fold increased odds for impaired creatinine-based eGFR among the participants untreated for diabetes (OR = 3.075, $$p \leq 0.044$$; Figure 2, Supplementary Table S3). The same tendency was observed for impaired cystatin-based eGFR and UACR, but was not significant. Of note, the number of individuals that were untreated for diabetes and had high HbA1c (≥$7.0\%$) were few ($$n = 14$$). Nevertheless, for these few individuals, this can be an important finding. High blood pressure (SBP ≥ 140 or DBP ≥ 90 mmHg) showed a tendency of decreased risk for impaired eGFR (e.g., creatinine-based: OR = 0.788, $$p \leq 0.051$$ or OR = 0.691, $$p \leq 0.076$$, respectively) and a significantly increased risk for impaired UACR (OR = 1.305, $$p \leq 0.049$$ or OR = 2.122, $p \leq 0.001$, respectively; Figure 2, Supplementary Table S3). There was no interaction with antihypertensive therapy intake. Low blood pressure (SBP < 120 or DBP < 80 mmHg) was not associated with impaired UACR (OR = 0.760, $$p \leq 0.078$$ or OR = 0.883, $$p \leq 0.391$$, respectively). However, it was associated with an increased risk for impaired eGFR (low SBP with creatinine-based eGFR: OR = 1.274, $$p \leq 0.045$$; low SBP and low DBP with cystatin-based eGFR: OR = 1.509, $$p \leq 0.001$$ or OR = 1.383, $$p \leq 0.005$$, respectively). For the association of low SBP and creatinine-based eGFR, we found a significant interaction with diuretic treatment (p-interaction = 0.008) and this association was predominantly among individuals taking diuretics. We visualized this cross-sectional finding between low SBP and impaired eGFR for quantitative levels using Loess splines (i.e., no linearity assumption; Figure 3): this substantiated again that the low blood pressure levels concomitant with low eGFR were mostly observed for individuals on diuretics, particularly when SBP was lower than 110 mmHg. Individuals at SBP < 110 mmHg with concomitant eGFR < 60 mL/min/1.73 m2 were undergoing particularly intense antihypertensive/diuretic therapy—with regard to the number of different agents or intake of high-ceiling diuretics (>2 antihypertensive agents: $41.1\%$; high-ceiling diuretics: $43.3\%$; Supplementary Figure S3). ## 4. Discussion Our cross-sectional study of 2215 individuals aged 70–95 years provides important insights into the extent of medication intake and cardiovascular control with or without medication in the elderly in a German population. We found partly well-achieved and partly unachieved cardiovascular risk factor control in an old-aged mobile community-dwelling population. Risk factor control was poor for LDL-cholesterol, excellent for HbA1c, and mixed for blood pressure. We obtained evidence for potential under- and overtreatment, with some potential disparities by sex and age groups. We also observed a complex pattern of association with kidney function: elevated LDL-cholesterol showed a counter-intuitive association with a decreased risk of kidney damage irrespective of treatment status. High HbA1c among individuals without antidiabetic therapy was associated with an increased risk of impaired kidney function. Too high or too low blood pressure values were associated with an increased risk for kidney damage or impaired filtration, respectively. By this, we found several lines of evidence that complemented previous data, and we contribute with insights into the interaction with treatment: whether kidney function is impaired irrespective of treatment, only among those that are untreated, or only among those that are treated. The first appeared to be the case for high LDL-cholesterol and the inverse association with kidney damage irrespective of treatment status, the second for individuals at high HbA1c without antidiabetic therapy associated with impaired kidney function, and the third for individuals with low blood pressure and simultaneously low eGFR, observed predominantly among individuals on diuretics. However, we are well aware that the cross-sectional, observational nature of our data does not allow for a clinical judgement on the best therapy, nor for a causal link between cardiovascular risk factors or therapy and impaired kidney function. Selection and indication bias need to be considered. To this end, it should be noted that our study sample reflects diseases and conditions proportional to a “mobile” elderly population, since participants were able to come to the study center and answer all questions personally [27]. Furthermore, our results are adjusted for a history of CAD/stroke to account for confounding by indication, but not for self-reported heart failure due to discrepancies with physician reports [31]. We discuss our findings more specifically in the following. LDL-cholesterol control at 116 mg/dl was unachieved by $76\%$ [8]. It is unclear whether this should be considered undertreatment, since there is an ongoing debate on the benefit of lipid control among the old aged [8,18,37]. However, still, $51\%$ of individuals with a prior CAD or stroke had LDL-cholesterol ≥ 116 mg/dL, which place them at high risk for further cardiovascular events under the “cholesterol hypothesis”. This risk is viewed as being reducible by lowering LDL-cholesterol, even at old age [8]. Nevertheless, there is substantial uncertainty in how to judge high LDL-cholesterol in the elderly: a lack of or an inverse association of LDL-cholesterol with mortality was observed in the old aged [38], with potential reasons being “inverse causation”, the beneficial effects of high LDL-cholesterol in the elderly, or the adverse effects of treatment. Our finding of high LDL-cholesterol associated with a decreased risk of kidney damage was in line with this inverse association in the elderly. That this was irrespective of treatment status might suggest other explanations than adverse treatment effects. Only $6.3\%$ had HbA1c ≥ $7.0\%$ and $2.8\%$ had HbA1c > $7.5\%$ [6,7], which indicates excellent glucose control. Nonetheless, among the individuals without antidiabetic therapy, we observed 14 individuals with HbA1c ≥ $7.0\%$ and HbA1c ≥ $7.0\%$ significantly associated with impaired filtration, and a tendency also for increased risk of kidney damage. Among the individuals with antidiabetic therapy, we observed 71 individuals with HbA1c at <$6.0\%$; this is considered too low according to guidelines due to a high risk for hypoglycemia [6]. Our data thus suggest some individuals with untreated diabetes possibly at an increased risk for impaired kidney function, and some individuals with potential overtreatment. However, clinical routine data would be required for a definitive judgement. Very high systolic or diastolic blood pressure at ≥160 or ≥100 mmHg was found for $7\%$ or $2\%$ of individuals, respectively. There is a broad consensus that such levels are considered too high also at old age. Thus, these individuals can be considered undertreated [9,18]. We found high blood pressure not associated with impaired filtration, but with a significantly increased risk with UACR ≥30 mg/g. Both were in line with the Berlin Initiative study [39] ($$n = 2069$$, aged 70+ years). This was also in line with the Leiden 85-Plus Study [40] ($$n = 550$$, aged 85+ years), which reports a lack of high blood pressure association with creatinine clearance, but without data on UACR. The benefit of lowering to $\frac{140}{90}$ mmHg or lower for the old aged is controversially discussed [10,11,18,41]. More than a quarter of AugUR participants had low blood pressure at <$\frac{120}{80}$ mmHg. Such low blood pressure might place old-aged individuals at an increased risk for falls and mortality [9,12,42]. However, the SPRINT trial provided evidence that a systolic blood pressure target at <120 mmHg compared to <140 mmHg reduced all-cause mortality in old-aged individuals [41]. Notably, SPRINT focusses on the very healthy old aged, e.g., it excludes individuals with diabetes or a history of stroke (compared to AugUR: diabetes $21\%$, history of stroke $9\%$). Regarding kidney function, SPRINT showed that individuals allocated to the lower blood pressure target suffered more likely from a reduction in eGFR. This is in line with our cross-sectional results that low blood pressure was associated with a higher risk of impaired eGFR, which confirmed previous findings on lower creatinine clearance in the presence of low blood pressure in old-aged individuals (Leiden 85-Plus Study [40]). Our data extend the previous findings in two ways: we observed low blood pressure as not associated with an increased risk of impaired UACR, but rather with a tendency towards a decreased risk. This suggests that the association between low blood pressure and impaired eGFR might not indicate structural kidney damage, but rather reduced perfusion pressure [9,43,44,45]. Furthermore, our interaction analyses showed the association of low systolic blood pressure with impaired eGFR to be predominantly pronounced among individuals taking diuretics. While we accounted for previous CAD or stroke and thus for potential confounding by indication, we did not attempt adjustment for heart failure, since self-reported heart failure is unreliable [31]. Whether this intensive therapy was warranted, e.g., due to heart failure or a potential overtreatment, cannot be judged from these cross-sectional data. Our study comprises a relatively large sample of elderly individuals with standardized assessments of cardiovascular risk factors, which fills a gap in the current literature. A strength of our study is the evaluation of taken medication, rather than relying on information about prescribed medication. The assessment of creatinine- and cystatin-based eGFR as well as UACR enables a view on kidney function beyond pure creatinine metabolism, as well as on structural kidney damage. Self-reported history of CAD, stroke, or diabetes has been shown to successfully reflect physician diagnoses [31]. Blood pressure was measured three times in the study center and the mean of the second and third measurements was used for analysis to minimize white-coat effects [27]. AugUR is designed as a longitudinal study, which will yield follow-up information in the future. Some limitations warrant mentioning. Our analysis is cross-sectional, which limits the interpretation regarding the sequence of events; we can show the co-occurrence of adverse cardiovascular risk factors and impaired kidney function, but longitudinal data or even a randomization to differential treatment regimen are warranted to enable a better judgement of over- or undertreatment and the respective consequences for cardiovascular risk factors and kidney function. Since the response to study invitations was ~$18\%$ and all participants had to come to the study center and answer all questions personally, AugUR captures a physically mobile and mentally healthy population over 70 years of age with an interest in health questions. ## 5. Conclusions In summary, our data provide important insights into the extent of cardiovascular risk factor control in individuals at 70 to 95 years of age. Our results showed that recommended target levels were partly well achieved, but also partly unachieved in the elderly, indicating some potential undertreatment. Our data also suggest hypoglycemia or too low blood pressure by overtreatment in a few individuals. We thus provide data that may foster the debate on whether old-aged individuals would benefit from more or less therapy. Our results also provide an understanding of the cross-sectional association of cardiovascular risk factors with impaired kidney function. Elevated LDL-cholesterol showed a counter-intuitive association with a decreased risk of kidney damage, an inverse association typically seen for the elderly, with reasons being elusive. High HbA1c among individuals without antidiabetic therapy associated with impaired kidney function suggested some undetected diabetes with potential involvement of the kidney. 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--- title: Diastole/Body Mass Index Ratio Can Predict Post-Thoracoscopic Surgery Metastasis in Stage I Lung Adenocarcinoma authors: - Hung-Hsing Chiang - Po-Chih Chang - Ting-Wei Chang - Kai-Hua Chen - Yu-Wei Liu - Hsien-Pin Li - Shah-Hwa Chou - Yu-Tang Chang journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10054715 doi: 10.3390/jpm13030497 license: CC BY 4.0 --- # Diastole/Body Mass Index Ratio Can Predict Post-Thoracoscopic Surgery Metastasis in Stage I Lung Adenocarcinoma ## Abstract Background: According to recent animal models for lung adenocarcinoma metastasis, cardiac function may be related to the clinical outcome. The aim of this study is to identify a predictable index for postoperative metastasis (POM) that is associated with cardiac function. Methods. Two hundred and seven consecutive patients who underwent thoracoscopic resection for stage I lung adenocarcinoma were included. Disease-free survival (DFS), overall survival (OS), and patients’ clinical and pathological characteristics were analyzed. Results. Among the 207 patients, 17 cases demonstrated metastasis, 110 cases received a preoperative echocardiogram, and six cases had POM. Mitral valve peak A velocity, which is one of the left ventricular diastolic function parameters affected by BMI (MVPABMI), was associated with a negative factor for POM (hazard ratio (HR): 2.139, $$p \leq 0.019$$) and a poor 5-year DFS in the above median ($100\%$ vs. $87\%$, $$p \leq 0.014$$). The predictable rate increased from $30.7\%$ to $75\%$ when the MVPABMI was above the median = 3.15 in the solid subtype). Conclusions. MVPABMI is a novel index for POM prediction in early-stage lung adenocarcinoma. This is a pilot study and the first attempt at research to verify that the diastole and the BMI may be associated with POM in early-stage lung adenocarcinoma. ## 1. Introduction Lung cancer is one of the most prevalent malignant diseases worldwide. In Taiwan, adenocarcinoma is the most common type of cancer, which can occur in several parts of the body [1]. The majority of cases diagnosed are late-stage and have a poor prognosis. However, early-stage patients are usually associated with a better prognosis after radical surgical excision, and their survival rate (SR) reaches $93\%$ [2]. However, regardless of the increased SR, early-stage patients are still at risk for postoperative metastasis (POM), which results in a poorer prognosis than in non-metastatic patients [2]. The echocardiogram is a common imaging screening test for cardiovascular diseases [3] and a popular tool in preoperative cardiac assessments. Among the many advantages of this imaging modality, echocardiograms can provide both structural and functional results, and they are safe, non-invasive, and cost effective. In patients undergoing non-cardiac surgery, echocardiograms can provide more precise information compared to data from their physical examination and history alone. Consequently, based on the information acquired from echocardiograms, surgeons and anesthesiologists can obtain a more detailed examination before the surgical intervention [4]. Although echocardiograms are very useful in terms of assessing the functional status of patients with cancer, they do not have the ability to determine the prognosis of malignant disease. In animal studies with lung cancer distant metastases [5,6], cancer cells must be delivered to the target organs, including the lungs or bones, through the pumping of the heart. Hence, the heart might be an organ that can influence the result of metastasis. Body mass index (BMI) is a common and useful parameter for population-based studies, including cardiovascular accidents, diabetes mellitus, and other metabolic related diseases [7]. Increased BMI might be related to increased all-cause mortality [8]. In fact, a greater BMI increases the incidence and risk of cancer-related mortality [9,10]. However, in lung cancer, patients with a normal to obese BMI have a better overall survival (OS) rate than underweight patients in stage I non-small cell lung cancer (NSCLC) [7,10,11]. The definitive reasons remain indeterminate, but this is probably related to improved tolerance for further treatment, such as chemotherapy. Nonetheless, there is a distinct lack of data pertaining to disease-free survival (DFS). Hence, our investigation is focused on the relationship between the risk of POM and BMI. Metastasis after radical resection is a serious condition for early-stage lung cancer patients. Systemic therapy is recommended, and the prognosis is poorer compared to non-metastatic conditions that do not require adjuvant therapy [2]. Parameters for NSCLC surveillance, including preoperative biomarkers (serum carcinoembryonic antigen (CEA), serum cytokeratin 19 fragment (CYFRA 21-1)), tumor size, cell subtypes, and differentiation, are useful prognostic markers [12,13]. Currently, regular surveillance with imaging modalities and/or serum biomarkers without any adjuvant therapy is recommended after radical excision in patients with early-stage lung cancer. Current literature supports that although adjuvant therapy can improve survival rates in high-risk cases, this approach may also increase the risk of harmful side effects in patients [14]. Hence, more useful, predictable parameters are needed for precision and prevention of metastasis in patients with a high risk of metastasis. Consequently, we are curious about the relationship between heart function and BMI for POM in early-stage lung adenocarcinoma. This study attempted to identify high risk POM from cardiac function and BMI. ## 2.1. Study Population From January 2014 to December 2018, lung adenocarcinoma patients who underwent curative surgery were investigated at the division of thoracic surgery, department of surgery, Kaohsiung medical university hospital (KMUH), Kaohsiung, Taiwan. If there were any recommendations or necessary preoperative assessments, an echocardiogram was performed by qualified cardiologists before general anesthesia. The left heart function was the main evaluation target. A complete staging workup was performed on all patients, including chest computed tomography (CT), brain magnetic resonance imaging (MRI), and a whole-body bone scan for operation, planning, and evaluation of distant metastases. TNM stage and POM were classified according to the American Joint Committee of Cancer Eighth Edition (AJCC 8th) Lung Cancer Staging system [15]. All patients underwent minimally invasive thoracoscopic surgery under double lumen general anesthesia, with one lung ventilated in the decubitus position. Surgical procedures, including wedge resection, segmentectomy (sublobar group), lobectomy, and bilobectomy (lobectomy group), had been previously performed after complete evaluation and assessment by each surgeon in KMUH. No patient underwent a pneumonectomy. The section margins were all free from the lesion. Systemic mediastinal lymph node sampling or dissection was also performed. Histologic subtypes of lung adenocarcinoma were classified in line with the new International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society (IASLC/ATS/ERS) multidisciplinary lung adenocarcinoma classification [16]. Lymphovascular invasion was defined as the identification of tumor cells in the lymphatic or blood vessel lumen. Histologic grade and spread through air space (STAS) were determined according to the 2015 World Health Organization (WHO) classification [16]. Pathologic classifications were conducted independently by two qualified pathologists, and rare discrepancies were resolved through reexamination of the slides and discussion. Patients’ clinical characteristics, including gender, age, BMI, history of cardiovascular (CV) diseases, and blood pressure (BP), were collected. Pathological stages IA to IB had been included, and the cancer staging was the AJCC 8th edition. Patients who received any kind of adjuvant therapy or neoadjuvant therapy and had a history of malignant tumors were excluded. Finally, 207 patients were included in this study. ## 2.2. Patient Follow-Up Evaluation The surveillance period was until December 2020, and the median follow-up period was 57 months. The surveillance schedule was as follows: follow-up in the clinic every three to four months for the first two years after the operation, every six months for three to five years, and every 12 months thereafter. A chest CT was routinely arranged at each surveillance visit for inspecting potential local recurrence and lung metastasis. In non-symptomatic patients, brain MRI, liver sonography, and bone scans were arranged every six to 12 months for the detection of distant metastasis. If any symptoms were suspicious during the surveillance, the above examinations were immediately arranged to exclude POM. DFS was defined as the time from the date of surgery to a recurrence or metastasis of the disease. OS was defined as the time from the date of surgery until death. Patients without recurrence were censored at the time of their last negative follow-up or their death without evidence of recurrence. Study inclusion criteria were pathologically confirmed stage IA/B (T1a/T1b/T1c/T2aN0M0) adenocarcinoma and complete resection with systemic lymph node sampling or dissection. This study was performed in accordance with the Helsinki Declaration. Our institutional review board approved this study (approval number: KMUHIRB-E(II)-20220075). Informed consent was waived because this was a retrospective study. ## 2.3. Statistics We used the IBM SPSS 19.0 edition software to perform all statistical analyses. All tests, including independent t and two-tailed Chi tests, were analyzed for the identification of any potential differences. The echocardiogram results were adjusted according to BMI. After the identification of differences, we used the cox regression model for prognostic factor identification, including univariate and multivariate analysis. The Kaplan–Meier method was used for the analysis of the 5-year DFS and OS, and log-rank tests were used for comparisons of DFS and OS between two categories in univariate analysis. Variables with a p value of less than 0.05 were entered into the survival analysis and cox regression. ## 3. Results A total of 273 patients conformed to the study’s eligibility criteria. Sixty patients who received adjuvant therapy, four patients who were categorized as adenocarcinomas in situ, and two patients who received neoadjuvant therapy were excluded. Consequently, 207 patients were included in the study, of whom 115 were female and 92 were male (Figure 1). The definition of POM was classified according to the AJCC’s 8th edition M status after surgery. Finally, 11 female and six male patients had POM. The lung was the most popular metastatic site, whereas metastasis in the brain, pleura, adrenal gland, bone, and liver was also observed. The mean DFS time was 23.59 months (6–53 months) in the POM group. The median ages of the non-metastatic group and POM were 60.36 and 62.41 years, respectively, at the time of diagnosis. There was no POM in the T1a and lepidic subtypes. According to the literature, BMI is a factor for lung cancer prognosis, and a high BMI has a better outcome compared to a low BMI. However, there are no definitive data for POM. To investigate the relationship between BMI and POM, we collected patients’ BMI data, and our findings showed that patients in the metastatic and non-metastatic groups were 23.54 and 24.04, respectively. The above data showed non-significant differences (Table 1). Surgical types, including wedge resection, segmentectomy (sublobar group), lobectomy, and bilobectomy (lobectomy group), are not a prognostic factor for POM. In the data from surgical specimens’, we were missing two cases of adenocarcinoma subtypes. Adenocarcinoma subtypes, including papillary and solid, visceral pleural invasion (T2a), and tumor size were independent factors for increased probability of POM (HR: 4.089, 4.070, 3.485, and 3.636, respectively). The percentage of each subtype for each lesion revealed that papillary and solid components increased the risk of POM (HR: 1.019 and 1.031, respectively), whereas the lepidic subtype percentage reduced the risk of POM (HR: 0.96) (Table 2). The Kaplan–Meier survival curve also revealed differences on the 5-year DFS in T2a, papillary, and solid subtypes ($85\%$, $75\%$, and $72\%$, respectively, $p \leq 0.05$) but not in OS (Figure 2). Kaplan–Meier survival curves of the solid subtype, T2a, and papillary subtype. Notice that each parameter increases the incidence of postoperative metastasis ($68\%$, $85\%$, and $75\%$, respectively, $p \leq 0.05$). No significant difference, except for the solid subtype, was identified in overall survival ($80\%$, $p \leq 0.05$). Preoperative echocardiogram data were collected and analyzed to evaluate whether cardiac function influences POM in early-stage lung adenocarcinoma. We performed 207 echocardiograms in 110 patients, and our findings showed that no patients demonstrated severe cardiac function abnormalities, including valvular diseases. Furthermore, there were no significant differences, including cardiovascular diseases, between the echocardiogram group and the non-echocardiogram group (Table 3). Among the 110 patients, six patients had POM, with significant differences in the percentages of lepidic and solid subtypes (Table 4). The underlying target of the echocardiogram was to perform a preoperative assessment, and thus left cardiac function was the main evaluation target. No patients had moderate-to-severe valvular diseases or left ventricular systolic function impairment. We analyzed all the results from the echocardiogram, and the data revealed that there were no significant differences in any of the investigated parameters between the two groups. Because BMI influences lung cancer survival [11], we adjusted the echocardiogram data according to the BMI. Consequently, we noticed significant differences between POM and non-POM groups when the mitral valve peak A and E velocities were adjusted by BMI (MVPABMI and MVPEBMI) (Table 5). MVPABMI and MVPEBMI were independent factors for increased POM (HR: 2.139 and 2.293, respectively), and only MVPABMI was associated with the solid subtype (Table 6). We noticed that all POMs occurred up to a median level of 3.15. The predictable rate increased from $30.7\%$ to $75\%$ when the MVPABMI reached 3.15 in the solid subtype. Furthermore, only the DFS of MVPABMI ($87\%$) showed significant differences in survival but not in OS (Figure 3). Notice that the Kaplan–Meier survival curve of the diastole/body mass index ratio (MVPABMI) up to 3.15 increased the incidence of postoperative metastasis ($100\%$ vs. $87\%$, $$p \leq 0.014$$). Since CV diseases and BP might influence the left ventricular diastolic function, we investigated the above parameters, and our findings revealed no significant differences (Table 2 and Table 3). Thus, left ventricular diastolic function and BMI might influence POM in resected early lung adenocarcinoma, especially in the solid subtype. ## 4. Discussion In this study, we found that MVPABMI can predict POM in stage I lung adenocarcinoma before resection, especially in the solid subtype. There were no participants with metastasis or recurrence in tumor size less than 1 cm in diameter without visceral pleural invasion (T1a). In fact, these two parameters can be easily collected before any pathological diagnosis. In parameters from surgical specimens, the solid, papillary, and micropapillary predominant subtypes increase the metastatic incidence, i.e., metastasis does not occur in the lepidic subtype. In contrast to the lepidic components, the percentage of solid components in pathological examination increases the incidence of metastasis. Surgical types, including lobectomy and sublobar excision, were not found to influence POM in our cohort. Taken together, the solid subtype, tumor size, visceral pleural invasion, and MVEAPBMI were found to be independent factors for POM in early-stage lung adenocarcinoma. MVPABMI is related to the solid subtype but not to visceral pleural invasion. This in turn suggests that the MVPABMI value increases the probability of metastasis in the solid subtype. According to the WHO classification for lung tumors, the subtype of lung adenocarcinoma can predict the subsequent treatment outcome. However, the solid subtype has been found to be an independent negative predictive factor for outcomes, including OS and post-recurrent survival [16]. In our study, all cases were stage I, the tumor size was below 3 cm in diameter, and the solid subtype was found to be an independent negative factor. DFS and OS were shown to be poorer than other subtypes. As shown in previous studies, pleural invasion and tumor size are also independent factors that indicate a poorer outcome [17,18]. Our results are comparable with the findings of these research studies in the solid subtype, visceral pleural invasion, and tumor size. BMI is widely used in obesity studies. Obesity is linked to metabolic diseases, including cardiovascular events, diabetes mellitus, hypertension, and hyperlipidemia. Greater BMI is also related to higher morbidity and mortality rates [8]. In breast cancer, increased BMI results in a poor prognosis as a result of a complex mechanism involving inflammation, hormone, and adipokines [9,19]. In contrast, normal to overweight patients have better lung cancer outcomes compared to underweight patients. This may be related to patients’ tolerance for anti-cancer therapy, including anti-cancer agents, radiotherapy, and surgical interventions [11]. In our study, we focused on POM in stage I lung adenocarcinoma, and we did not identify any relationship between BMI and metastasis. After adjusting mitral valve peak A velocity data by BMI, our data revealed a significant difference between patients with and without metastasis. Thus, we support the idea that BMI might influence POM. An echocardiogram is an easy-to-use, non-invasive tool for cardiac function assessments. In KMUH, echocardiograms are recommended before operations on patients with a high-risk presentation of CV diseases in accordance with their medical histories. If any abnormalities are detected by the echocardiogram, further examinations, including a single photon emission CT, a treadmill test, or coronary artery catheterization, are scheduled by the cardiologist. In our study, no patients underwent additional examinations for the heart because echocardiography revealed a normal, limited left ventricular systolic function. In animal studies, intracardiac lung cancer cell line injection to the left ventricle can induce bone or brain metastasis, whereas pulmonary metastasis can be induced by tail vein injection [5,6]. The above models revealed that the heart may be a prominent factor in metastasis. Thus, we support the notion that cardiac function is related to lung cancer metastasis. In our cases, the left cardiac diastolic function might indirectly influence metastasis in lung adenocarcinoma, as evidenced by the mitral valve peak E and A velocities from the preoperative echocardiography data after adjustment for BMI. Mitral valve peak E and A velocities reflect left ventricular diastolic function. These parameters represent the pressure gradient in early and late diastole of the left heart, respectively. [ 20]. In patients with myocardial disease, LV diastolic dysfunction can be predicted by changing the E:A ratio through LV filling pressure [21]. In our study, no patient had a myocardial event before resection. These findings may be explained by the increased pulmonary venous flow velocity, which may facilitate the translocation of cancer cells to the pulmonary vein. MVPABMI, which combines BMI and diastolic function, is a novel index for POM prediction in early-stage adenocarcinoma. We support the idea that MVPABMI is dictated by a complex mechanism and that multiple factors facilitate POM. Recently, many studies have concluded that air pollution is a risk factor for lung cancer [22,23]. Moreover, air pollution is also related to the development of cardiovascular disease and diastolic and left ventricular dysfunction because pollutants, including fine particulate matter, polycyclic aromatic hydrocarbons, and NOx, induce oxidative stress and chronic inflammation [22,23]. In Taiwan, poorer outcomes for lung cancer have been shown in industrial cities compared to non-industrial ones [1]. Inflammation has also been shown to influence diastolic dysfunction in an animal study [24]. Altogether, air pollution is probably one of the main causes of POM as a result of diastolic dysfunction in lung adenocarcinoma. However, further prospective or animal studies are necessary to confirm this speculation. Our study has several limitations. First, our study is retrospective and has a relatively small sample size. Only six patients who received a preoperative echocardiogram had POM. Pathologic classifications, including histological grade, lymphovascular invasion, and STAS, were established as independent prognostic factors [25,26,27]. Before 2016, the above data were not routinely evaluated in KMUH, which unavoidably resulted in incomplete evaluations and thus were not related to MVPABMI. 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--- title: A Simple and Easily Implemented Method for the Regioselective Introduction of Deuterium into Azolo[1,5-a]pyrimidines Molecules authors: - Gevorg G. Danagulyan - Henrik A. Panosyan - Vache K. Gharibyan - Ani H. Hasratyan journal: Molecules year: 2023 pmcid: PMC10054722 doi: 10.3390/molecules28062869 license: CC BY 4.0 --- # A Simple and Easily Implemented Method for the Regioselective Introduction of Deuterium into Azolo[1,5-a]pyrimidines Molecules ## Abstract A method for the technically easy-to-implement synthesis of deuterium-labeled pyrazolo[1,5-a]pyrimidines and 1,2,4-triazolo[1,5-a]pyrimidines have been developed. The regioselectivity of such transformations has been shown. 1H NMR and mass spectrometric methods have proved the quantitative nature of such transformations and the kinetics of deuterium exchange has been studied. Spectrally, at different temperatures (+30 °C, −10 °C and −15 °C), the kinetics of the process was studied both in CD3OD and in deuterated alkali. ## 1. Introduction Azolo[1,5-a]pyrimidines derivatives, primarily pyrazolo[1,5-a]pyrimidine and 1,2,4-triazolo[1,5-a]pyrimidine, are known for their high biological activity. Several drugs containing the pyrazolo[1,5-a]pyrimidine backbone are used in medical practice. These include the sleeping pills Zaleplon [1,2], Indiplon and Lorediplon [3,4]; the sedative Ocinaplon [5]; the antifungal drug Pyrazophos [6]; the antiglycemic drug Anagliptin [7,8]; and the antitumor drug Dinaciclib [9,10] (Figure 1). Moreover, an entire series of pyrazolo[1,5-a]pyrimidine derivatives are registered, which have shown an antitumor effect [11,12,13,14,15,16,17,18,19,20], and effects on the central nervous system and serotonin receptors [21,22,23,24,25,26,27]. The same backbone of pyrazolo[1,5-a]pyrimidine is included in a number of derivatives that have shown activity as non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) [28] and respiratory syncytial virus (RSV) [29], inhibitors of RNA-polymerase of hepatitis C virus [30], as well as having antibacterial, antifungal [31] and anti-inflammatory properties [32,33,34]. The high biological activity of pyrazolo[1,5-a]pyrimidines stimulated interest in the development of methods for introducing various isotopes into its derivatives. In particular, compounds labeled with the [99mTcN]2+ isotope were synthesized and studied for their biodistribution in mice with tumors [35]. A 5-methylpyrazolo[1,5-a]pyrimidine derivative containing the 18F fluorine isotope was used as an imaging marker for positron emission tomography (PET) to detect a tumor [36]. It is known that deuterium-labeled compounds are also used as markers for studying the mechanisms of chemical reactions, as well as in biological research and medicinal chemistry [37,38]. Deuterated derivatives of known drugs differ from the drugs themselves by prolonging the half-life, which leads to an increase in the interval between taking the drug and, consequently, an increase in the effectiveness and safety for the patient [39]. Various methods for introducing a deuterium isotope into molecules of organic compounds are described. Formally, these methods can be divided into 3 groups, namely, proceeding under the conditions of acid or base catalysis and metal catalysis [40]. In the case of metal catalysis, Pd, Ni, Ir, Pt, Ru or their salts were used as metals. These reactions require special conditions. They were carried out under heating [41], under pressure [40,42], in a microwave oven [43], by passing pure deuterium [40], or in deuterated solvents, more often D2O. Deuterium atoms were introduced by H/D exchange into α-aminopyridine derivatives by heating them to 80 °C in a solution of K2CO3 in D2O [44]. Furthermore, by reaction with substituted acetylenes, the resulting deuterium derivatives were cyclized to pyrazolo[1,5-a]pyridine derivatives containing deuterium atoms. The reaction of the same pyridines with acetonitrile in basic D2O solution resulted in 1,2,4-triazolo[1,5-a]pyridine derivatives containing deuterium atoms. Another method for introducing deuterium into an azine molecule has been described for the preparation of pyrimidine derivatives containing a deuterium atom. This involves a multicomponent cyclization of amidine, benzaldehyde and deuterated triethylamine-D15 in the presence of iodine at 150 °C [45]. An example of the metal catalysis used for introducing deuterium into a pyrimidine molecule is a reaction under microwave-promoted conditions catalyzed by Ruthenium(II)–Carboxylate [46]. It is also important to note that the drug Austedo (deutetrabenazine) (Figure 2), which contains deuterium atoms, is already being used in medical practice [47]. ## 2. Results and Discussion From the above, it is clear that the methods used for obtaining deuterated derivatives are not always simple. Therefore, the development of new, easily implemented methods for introducing deuterium atoms into molecules of organic substances is of interest. This is especially important in the synthesis of deuterium-containing bioactive substances. Considering the biological activity and importance of Azolo[1,5-a]pyrimidine derivatives in medicine, interest in developing new methods for introducing deuterium atoms into their molecules is of practical interest and is undoubtedly relevant. This communication is devoted to a simple, easily and rapidly implemented method for introducing deuterium atoms into the molecules of substituted pyrazolo[1,5-a]- and 1,2,4-triazolo[1,5-a]pyrimidines. It is also essential that the proposed method is regioselective. When drops of a preliminarily prepared solution of CD3ONa in CD3OD are added to the solution of 6-acetyl-2,7-dimethylpyrazolo[1,5-a]- [1] and 6-acetyl-7-methyl-2-phenylpyrazolo[1,5-a]pyrimidine [2] in CD3OD (Scheme 1), the disappearance of the signals of two methyl groups is almost immediately observed in the 1H NMR spectrum. Comparison of the spectra of substances 1 and 2, as well as the NOESY study of the spectrum of compound 1, indicates the H/D exchange of hydrogen atoms of the methyl (7-CH3) and acetyl (6-COCH3) groups (Figure 3). Thus, in the spectrum of the deuterated product of compound 1, the signal of the methyl groups is retained, for which the NOESY spectrum shows a response between the proton signal of one of the methyl groups (2-CH3) and the aromatic proton (3-H). Note that such an interaction is impossible for other methyl groups, which unambiguously proves that the 7-CH3 and 6-COCH3 protons located in the pyrimidine ring, and not the 2-CH3 protons located in the pyrazole ring, undergo isotopic exchange. In order to confirm the deuterium exchange that had taken place (after the addition of CD3ONa), we isolated substance 3 from the NMR ampoule and compared its mass spectrum with the spectrum of compound 1 before deuterium exchange (Figure 4). As a result, the mass of product 3, as expected, was 6 units higher than the mass of the initial substance 1 (respectively, 195 and 189). This confirms the H/D exchange in the two methyl groups. A similar exchange of protons of two methyl groups was also observed in the 1H NMR spectrum of 6-acetyl-7-methyl-1,2,4-triazolo[1,5-a]pyrimidine (CD3ONa solution in CD3OD) (Scheme 2). Almost immediately after the addition of alcoholate-D3 to the NMR ampoule, the signals of both methyl groups (7-CH3 and COCH3) disappeared. Under standard conditions for recording NMR spectra, i.e., at a temperature of +30 °C, it was impossible to study the kinetics of isotope exchange because of the very high transformation rate. Therefore, we tried to study the reaction at low temperatures. According to the results of preliminary studies, the optimal temperature for this was −10 °C (Table 1, Figure 5). The rate of proton exchange in the two methyl groups was different under these conditions. The intensity of the signal of one of the methyl groups (chemical shift 3.2 ppm) (−10 °C) decreases by $6\%$ by 5 min after the addition of deuterated sodium methoxide under these conditions, by 15 min the exchange is $22\%$, by 20 min the exchange reaches almost $30\%$ and is practically completed after 2 h of measurements. According to the results of the measurements, the rate of exchange of protons of the second methyl group (chemical shift 2.28 ppm) under these conditions turned out to be significantly lower. Thus, we recorded the first results of isotope exchange only 20 min after the start of the measurements, and by 120 min only $20\%$ of the protons in this group had undergone exchange. In the 1H NMR spectrum of triazolopyrimidine 5, recorded by the NOESY method (Figure 6), only one of the methyl groups located in the region of 2.28 ppm has a cross peak with an aromatic proton (9.3 ppm). This methyl group corresponds to the acetyl group occupying position 6. Based on this, we concluded that in the examples described, the protons of the 7-CH3 methyl group (3.17 ppm) are exchanged faster. We obtained similar confirmation when studying the spectrum of pyrazolopyrimidine 2 and, consequently, compound 1. A fast H/D exchange of protons of two methyl groups upon addition of CD3ONa to a solution of compound 1 in CD3OD was observed. Due to the rapidity of the reaction, the kinetics of the process at a temperature of −10 °C could not be fixed. However, it was registered at a lower temperature (−15 °C). Therefore, the exchange of both methyl groups approached $50\%$ after 2 min and was practically completed within a few minutes (Table 2, Figure 7). When studying the deuteroexchange of the 3-pyrazolyl derivative of pyrazolopyrimidine 7 containing 4 methyl groups, after adding CD3ONa to a solution, protons of two methyl groups in the pyrimidine ring are first exchanged (Scheme 3). In the side pyrazole ring, only the signal of one of the methyl groups disappears. In this case, a cross peak was noted in the NOESY spectrum (Figure 8), indicating the interaction of the methyl group of the acetyl fragment with the aromatic proton of the pyrazole ring, which made it possible to show that the hydrogen atoms of the acetyl group of the pyrazole ring undergo exchange. Interestingly, in this example, the exchange also partially affects the aromatic protons of pyrazolo[1,5-a]pyrimidine. In the study of deuterium exchange in 2-substituted 7-methyl-5-ethoxycarbonylpyrazolo[1,5-a]pyrimidines [10, 11], after adding CD3ONa to the solution, a rapid exchange of hydrogen atoms in the pyrimidine ring for deuterium atoms was immediately noted. However, in these cases, the reaction was accompanied by another transformation, which was also recorded spectrally. Thus, when comparing the 1H NMR spectra of 2,7-dimethyl-5-ethoxycarbonylpyrazolo[1,5-a]pyrimidine [10] recorded in CD3OD at temperatures of +30 °C and −10 °C, an unusual and at first glance inexplicable difference is noted. At minus temperature (−10 °C), the spectrum of the compound corresponds to the expected one and includes the signals of two methyl (2-CH3 2.55; 7-CH3 2.84 ppm) and one ester (OCH2CH3 4.46, OCH2CH3 1.44 ppm) groups, as well as singlets of two protons 3-H and 6-H (respectively, 6.70 and 7.48 ppm). In the spectrum of the same compound, recorded at +30 °C, the signals of all groups with the corresponding integrals are preserved, but two identical pairs of proton signals of two ethyl groups are observed (two quartets—OCH2CH3 4.46 and DOCH2CH3 3.62 ppm, each of which corresponds to one proton, and two triplets—respectively, 1.44 and 1.19 ppm, 1.5 H each) (Figure 9). The study of the spectra recorded in CD3OD at −10 °C, that is, before adding CD3ONa to the ampoule, showed that over time there is a gradual decrease in the signals of the protons of the ethyl group and the proportional appearance of a new pair of signals of another ethyl group. In this case, the signals of all other groups remain unchanged in the spectra (Figure 7). Ultimately, the signals of the ethyl group of the original molecule, namely, those noted in the region of 4.5 ppm (CH2) and 1.48 ppm (CH3) completely disappear and are replaced by ethyl group signals that have chemical shifts in a stronger field, respectively, in the region of 1.2 (CH3) and 3.6 ppm (CH2). We believe that the observed dynamic change in the NMR spectra is explained by the ongoing transesterification (Scheme 4). In this case, the solvent molecules (CD3OD) interact with the ethoxycarbonyl group displacing the ethoxy group, resulting in the formation of a new 7-methyl-2-methyl-5-d3-metoxycarbonylpyrazolo[1,5-a]pyrimidine. Ethanol (C2H5OD) is formed in the solution, the signals of the groups of which are fixed in the 1H NMR spectrum in the form of a new ethyl group. At +30 °C, after adding one drop of deuterated sodium methoxide (CD3ONa) to the NMR ampoule, both processes rapidly occur—transesterification and H/D exchange, a result of which the signal of one of the methyl groups (7-CH3) disappears in the spectrum, after which 3D-methyl 2-methyl-7-(d3-methyl)-5-ethoxycarbonylpyrazolo[1,5-a]pyrimidine is immediately formed. At low temperatures (−10 °C), we were able to study the kinetics of the entire deuterium exchange. As the experiment showed, in the beginning, transesterification already begins in CD3OD, which is completed even without the addition of CD3ONa. However, when d3-sodium methoxide is added, transesterification is activated, since there are no signals from the ester group of the starting ester in the spectrum. Under the same conditions (−10 °C), the kinetics of the H/D isotope exchange was studied by NMR spectral (Table 3, Figure 10). A similar isotopic exchange, together with transesterification, was also noted for 2-phenyl-7-methyl-5-ethoxycarbonylpyrazolo[1,5-a]pyrimidine 11. Thus, in the spectrum of compound 11, which contains a phenyl group in the pyrazole ring, two processes easily occur not only in a solution of deuterated alkali (CD3ONa in CD3OD), but also in a solution of CD3OD: the deuterium exchange of protons of the methyl group and transesterification with the formation of d1-ethanol (CH3CH2OD). In the 1H NMR spectrum at a temperature of +30 °C after the dissolution of the substance, the signals of the protons of the ethyl group of the ester in the regions of 1.46 (t, CH3) and 4.47 (q, CH2O) almost completely disappear, and the signals of the ethyl group of the formed d1-ethanol CH3CH2OD (1.18—t, CH3 and 3.61—q, CH2O) become the main signals. In this case, the proton signals of all other groups of compound 11 (phenyl and methyl groups, as well as hydrogen atoms directly connected to the pyrimidine and pyrazole rings) are observed in the spectrum without changes. After adding 1–2 drops of CD3ONa solution in CD3OD to the NMR ampoule containing a solution of compound 11 in CD3OD, the 7-CH3 signal almost completely and immediately disappears (the exchange is approximately $80\%$), and the proton signals in the weak field (C6H5, 3-H and 6-H) remain unchanged. The exchange of protons of the methyl group for deuterium (H/D) according to the 1H NMR spectrum data is practically completed by 20 min after the addition of sodium d3-methoxide. N-Alkylation of the pyrazolo[1,5-a]pyrimidine skeleton leads to a significant change in the process of deuterium exchange of methyl groups noted by us. This process was studied spectrally using the example of two salts of 6-acetyl-2,7-dimethylpyrazolo[1,5-a]pyrimidine—iodomethylate and iodoethylate. Namely, 6-acetyl-2,4,7-trimethylpyrazolo[1,5-a]pyrimidinium [16] and 6-acetyl-2,7-dimethyl-4-ethylpyrazolo[1,5-a]pyrimidinium [17] iodides. It is important to note that the position of the N-alkyl groups was confirmed by 1H NMR spectral using the NOESY technique. Thus, in the spectrum of 16 iodide, NOE (Nuclear Overhauser Effect) was noted between the protons of the N-methyl group (4.43 ppm) and the protons of the pyrazole (3-H) and pyrimidine (5-H) rings (7.25 and 9.95 ppm, respectively). The cross-peaks interactions of the 5-H proton of the pyrimidine ring with the signals of two adjacent positions of the groups, methyl N-CH3 and acetyl (COCH3), are also clearly visible. Therefore, based on the above, it was unequivocally determined that alkylation occurs at the N-4 nitrogen atom of the pyrimidine ring. Similar interactions of protons were also noted in the NOESY study of iodoethylate 17. It is noteworthy, that, in this case, only the protons of the N-methylene group participate in the interaction with the neighboring 3-H and 5-H protons. In the 1H NMR spectrum of iodide 16 recorded in CD3OD without the addition of CD3ONa methylate, an H/D exchange of one of the methyl groups was noted. Instead of the expected signals of four methyl groups, the signals of only three of them were fixed in the spectrum [18] (Scheme 5). Since the signal of the N-methyl group, as a rule, appears in a weaker field (in this case, it is 4.41 ppm), and the signal of the methyl group of the pyrazole ring is usually in the strongest field, the signal in the 2.78 ppm region could correspond to either a methyl group in position 7 or an acetyl group. Based on the NOESY study carried out in DMSO-d6 solution, it was concluded that the methyl group signal was present in the spectrum of the salt 16 in DMSO-d6 in the region of 3.3 ppm and disappeared due to deuterium exchange in the spectrum registered in CD3OD corresponding to 7-CH3. Thus, methylation of the pyrimidine ring, leading to an increase in its electrophilicity, facilitates the nucleophilic isotopic exchange of hydrogen atoms of the 7-methyl group, resulting in a rapid H/D exchange even in CD3OD. It is interesting that, in contrast to the above examples of deuterium exchange of non-alkylated at the nitrogen atom Azolo[1,5-a]pyrimidines [1, 2, 5, 7, 10, 11], with the addition of sodium d3-methoxide, the subsequent exchange of hydrogen atoms of the methyl fragment of the acetyl, or any other group, is not observed for only several minutes, but also during the first two days. Only by the third day does a slight decrease in the signal of the hydrogen atoms of the acetyl group (by about $25\%$) become noticeable in the spectrum; however, new signals begin to appear, which indicates the occurrence of other processes. The possibility of destruction at this stage should be excluded, since, in the spectrum for several more days of observations, in parallel with the decrease in the integral of the signal of the protons of the acetyl group, the signals of the remaining protons of the initial molecule (N-Me, 2-Me, 3-H and 5-H) are practically unchanged. In case of N-ethylpyrazolo[1,5-a]pyrimidinium iodide 17, as well as N-methyl derivative 16, in the spectrum registered in CD3OD, i.e., without the addition of CD3ONa, H/D exchange occurs immediately (Scheme 5) with the formation of deutero-substituted compound 19. In the same way, i.e., the NOESY study, it was shown that 7-CH3 hydrogen atoms undergo rapid exchange. Further monitoring for two days did not register the H/D exchange of any other protons in the molecule. The spectra of 6-acetyl-3,7-dimethyl-1,2,4-triazolo[1,5-a]pyrimidinium iodide 20 recorded in DMSO-d6 and CD3OD were identical. This indicates that the isotopic exchange does not proceed in this case in the CD3OD solution. Consequently, the displacement of the N-alkyl group into the triazole ring, that is, its removal from the 7-Me group, led to a decrease in the effect on potential (expected) isotopic exchange. The addition of alcoholate (CD3ONa) to the solution leads to the appearance of many new signals, possibly due to the opening of the pyrimidine ring and subsequent destruction of the molecule (Scheme 6). We studied a similar interactions of two more 1,2,4-triazolo[1,5-a]pyrimidinium iodides with solutions of deuterated sodium methoxide in deuteromethanol. In particular, the NMR spectra of 3,5,7-trimethyl-1,2,4-triazolo[1,5-a]pyrimidinium iodide [21] in CD3OD and CD3ONa/CD3OD were studied (Scheme 7). As in the case of iodide 20 in CD3OD, no selective isotopic exchange of C-alkyl groups was observed without the addition of alcoholate. However, when a small amount of CD3ONa was added to the NMR ampule, an easy, quantitative, and, most importantly, selective basic deuteroexchange of protons of both C-methyl groups of the pyrimidinium salt 22 was noted. The signals of C-methyl groups completely disappeared at room temperature. With an increase in the duration of exposure to the deuterated reagent, the signal also disappeared from one of the aromatic protons (apparently, 2-H, located in the triazole ring—in the neighborhood of the quaternized nitrogen atom). It is important to note that, as in the above example, in the spectrum of compound 23 (3,7-dimethyl-6-ethoxycarbonyl-1,2,4-triazolo[1,5-a]pyrimidine) in d4-methanol, no isotopic exchanges were observed. However, when d4-sodium methoxide is added, the proton signal of the 7-methyl group disappeared completely within a few minutes, while the signals of the remaining hydrogen atoms were preserved. Note that, as in the case of compound 21, deuterium exchange of one of the aromatic protons, presumably located in the triazole ring, occurred over time (during 10 days of monitoring) with the formation of salt 24 (Scheme 8). It should be noted that in the latter case (salt 23), we also observed in the 1H NMR spectrum a partially proceeding (significantly slower than in the case of the ester group in position 5 of compounds 10, 11) transesterification reaction. Thus, on a number of examples—methyl derivatives of 1,2,4-triazolo[1,5-a]pyrimidinium iodides—it was confirmed that alkylation of the nitrogen atom of the triazole ring does not lead to isotopic exchange of protons of the C-methyl group located in the pyrimidine ring. Such H/D exchange requires the addition of an alcoholate (CD3ONa) to the medium. In the examples of pyrazolo[1,5-a]pyrimidinium iodides, where the nitrogen atom in the pyrimidine part of the molecule is alkylated, the H/D exchange of C-methyl groups in the pyrimidine ring is very easily realized already in a CD3OD solution without the addition of CD3ONa. The schemes of the deuterium exchange reaction is associated with the attack of the methylate ion at the most electrophilic position in the molecule, which leads to the elimination of a proton. The resulting carbanion is stabilized by the addition of a proton (or, when the reaction is carried out in a solution of deuterated methanol, a deuterium atom). The H/D isotopic exchange of the protons of methyl groups in all the above examples proceeds according to the mechanism of nucleophilic substitution. However, the nucleophilic substitution in bases (i.e., not salts) and alkyl iodides (i.e., azolopyrimidinium salts) occurs via different pathways and has different driving forces. In the case of the bases of 1, 2, 5, 7, 10 and 11 compounds, in a solution of CD3ONa in CD3OD, under the action of a methoxide ion, the proton of the methyl group of the pyrimidine ring is removed and replaced by a deuterium atom from the solvent molecule at the same position (Scheme 9). As a result, a stepwise exchange of all hydrogen atoms of the methyl group 7-CH3, and then in the acetyl group, by deuterium atoms is realized. In the case of 4-alkyl-substituted pyrazolo[1,5-a]pyrimidinium salts, a different driving force determines the beginning of the isotope exchange. Due to the positive charge on the nitrogen atom, the mobility of hydrogen atoms of the 7-methyl group of the pyrimidine ring increases and, as a result, already in CD3OD—without the addition of alcoholate—H/D exchange becomes possible (Scheme 10). It should be noted that the positive charge on the nitrogen atom of the pyrimidine ring, while promoting an increase in the mobility of hydrogen atoms in the 7-methyl group, does not affect the possibility of detachment of hydrogen atoms in the acetyl group. It remains unaffected by the electronic effects of p-conjugation in the pyrimidine ring. This explains the absence of H/D exchange in the acetyl group in Azolo[1,5-a]pyrimidinium 4-alkyl derivatives in CD3OD solution. When alcoholate is added to the reactor, azolopyrimidine is converted into its neutral form, due to the formation of NaI. The shift in the electron cloud towards the N4 atom makes the 7-position of the pyrimidine ring a nucleophilic attack target. This can lead to the opening of the pyrimidine ring and its destruction (Scheme 10). Note that an ambiguous transformation of the molecule after the addition of an alcoholate was noted earlier. The process of deuterium exchange of protons of the methyl groups of the pyrimidine ring can be explained by the relatively high CH acidity of these protons. This also correlates the shifts in the signals of these protons in a relatively weak field. ## 3.1. General Experimental Details 1H-, 13C-NMR and NOESY spectra were recorded via Varian Mercury-300 VX spectrometer (Varian, Baden, Switzerland) (1H-NMR 300 MHz, 13C-NMR 75 MHz) in a CD3OD at temperatures of 253, 258 and 298 K. Elemental analysis was performed via Eurovector EA 3000 instrument. Melting points were measured on instruments for determining the melting point of organic substances SMP 11 (STUART) and SMP 30 (STUART, Wickford, UK). The purity and identity of the substances were confirmed on a high-performance preparative liquid chromatograph SENMIPREPARATIV HPLC (HPLC Knauer AZURA PREP + Analitical UV Detector),Germany), as well as TLC on Silufol (UV-254). The synthesis of non-deuterated compounds 1, 2, 5, 10, 11, 16 and 17 was carried out according to the previously described procedures [48,49]. 5-Amino-1H-pyrazole-4-carbohydrazide used for the synthesis of 3-pyrazolyl derivative of pyrazolopyrimidine 7 was purchased from Aurora Fine Chemicals LLC, San Diego, CA, USA. CD3OD was purchased from Sigma- Aldrich, St. Louis, MO, USA. All reagents purchased commercially were used without purification. ## 3.2.1. Synthesis of 6-acetyl-7-methyl-3-[1-(4-acetyl-5-methyl-1H-pyrazole-1-carbonyl)]pyrazolo[1,5-a]pyrimidine 7 A mixture of 5-amino-1H-pyrazole-4-carbohydrazide (130 mg, 1.2 mmol) and ethoxymethylideneacetylacetone (400 mg, 2.4 mmol) in 5 mL of absolute ethanol was refluxed for 4 h with a calcium chloride tube. After solvent evaporation, the resulting precipitate was filtered, washed with diethyl ether, recrystallized from hexane and dried to give 6-acetyl-7-methyl-3-[1-(4-acetyl-5-methyl-1H-pyrazole-1-carbonyl)]pyrazolo[1,5-a]pyrimidine 7 as an orange solid in $70\%$ yield. 1H NMR (300 MHz, DMSO/CCl4 1:3, δ, ppm): 2.48 (s, 3 H), 2.76 (s, 3 H), 2.93 (s, 3 H), 3.14 (s, 3 H), 8.12 (s, 1 H), 8.96 (s, 1 H), 9.28 (s, 1 H). 13C NMR (75 MHz, DMSO/CCl4 1:3, δ, ppm): 12.4, 14.52, 28.82, 29.56, 103.68, 120.08, 121.8, 142.27, 146, 149.01, 149.8, 150.07, 152.88, 159.68, 191.86, 195.43. Calculated, %: C 59.07, H 4.65, N 21.53. C16H15N5O3. Found, %: C 59.03, H 4.70, N 21.50; mp: 217–218 ℃. ## 3.2.2. General Procedure for the Preparation of Deutero-Substituted Azolo[1,5-a]pyrimidines 3, 4, 6, 9, 14, 15 A solution of several mg of compounds 1, 2, 5, 7, 10, 11 in CD3OD was prepared in an NMR ampoule and 1H NMR spectra were recorded. Next, 2 drops of a pre-prepared solution of CD3ONa in CD3OD were added to the ampoule and the dynamics of the proton deuterium exchange in the ampoule was monitored by registering changes in the 1H NMR spectra (Table 4). ## 4. Conclusions We have developed an efficient protocol for the synthesis of deuterium-labeled pyrazolo[1,5-a]pyrimidines and 1,2,4-triazolo[1,5-a]pyrimidines. It is important that the method is regioselective and leads to the introduction of deuterium atoms into the methyl group of the pyrimidine fragment of the molecule. The reaction is technically easy to implement and it can be used for labeling for biological research and studying the mechanisms of chemical reactions. It can be assumed that the method will be extended to introduce a tritium label into pharmaceuticals for use in medicine. ## Figures, Schemes and Tables **Figure 1:** *Examples of drugs containing the pyrazolo[1,5-a]pyrimidine backbone.* **Figure 2:** *Drug Austedo (deutetrabenazine).* **Scheme 1:** *H/D exchange in 6-acetyl-2,7-dimethylpyrazolo[1,5-a]- (1) and 6-acetyl-7-methyl-2-phenylpyrazolo[1,5-a]pyrimidine (2).* **Figure 3:** *NOESY spectrum of 6-acetyl-2,7-dimethylpyrazolo[1,5-a]pyrimidine (1).* **Figure 4:** **Mass spectra* of substance 1 and deuterated product 3, respectively.* **Scheme 2:** *H/D exchange in 6-acetyl-7-methyl-1,2,4-triazolo[1,5-a]pyrimidine (5).* **Figure 5:** *Diagram of the decrease in the concentration of hydrogen atoms in 6-acetyl-7-methyl-1,2,4-triazolo[1,5-a]pyrimidine (5) molecule for 7-CH3 and COCH3 groups in CD3ONa solution in CD3OD at −10 °C in a time period of 0–110 min.* **Figure 6:** *NOESY spectrum of 6-acetyl-7-methyl-1,2,4-triazolo[1,5-a]pyrimidine (5).* **Figure 7:** *Diagram of the decrease in the concentration of hydrogen atoms in 6-acetyl-2,7-dimethylpyrazolo[1,5-a]pyrimidine (1) molecule for 7-CH3 and COCH3 groups in CD3ONa solution in CD3OD at −15 °C in a time period of 0–12 min.* **Scheme 3:** *H/D exchange in 3-pyrazolyl derivative of pyrazolopyrimidine 7.* **Figure 8:** *NOESY spectrum of 6-acetyl-7-methyl-3-[1-(4-acetyl-5-methyl-1H-pyrazole-1-carbonyl)]pyrazolo[1,5-a]pyrimidine (7).* **Figure 9:** *1H NMR spectra of 2,7-dimethyl-5-ethoxycarbonylpyrazolo[1,5-a]pyrimidine (10) recorded in CD3OD at temperatures of +30 °C.* **Scheme 4:** *H/D exchange in 2-substituted 7-methyl-5-ethoxycarbonylpyrazolo[1,5-a]pyrimidine (10, 11).* **Figure 10:** *Diagram of the decrease in the concentration of hydrogen atoms in 2,7-dimethyl-5-ethoxycarbonylpyrazolo[1,5-a]pyrimidine (10) molecule for 7-CH3 group in CD3ONa solution in CD3OD at −10 °C in a time period of 0–75 min.* **Scheme 5:** *H/D exchange in 6-acetyl-2,4,7-trimethylpyrazolo[1,5-a]pyrimidinium (16) and 6-acetyl-2,7-dimethyl-4-ethylpyrazolo[1,5-a]pyrimidinium (17) iodides.* **Scheme 6:** *Expected H/D exchange in 6-acetyl-3,7-dimethyl-1,2,4-triazolo[1,5-a]pyrimidinium iodide (20).* **Scheme 7:** *H/D exchange in 3,5,7-trimethyl-1,2,4-triazolo[1,5-a]pyrimidinium iodide (21).* **Scheme 8:** *H/D exchange in 3,7-dimethyl-6-ethoxycarbonyl-1,2,4-triazolo[1,5-a]pyrimidinium iodide (23).* **Scheme 9:** *The proposed mechanism of H/D nucleophilic exchange in the bases (1, 2, 5, 7, 10 and 11) on the example of compound 1.* **Scheme 10:** *The proposed mechanism of H/D nucleophilic exchange in the salts.* TABLE_PLACEHOLDER:Table 1 TABLE_PLACEHOLDER:Table 2 TABLE_PLACEHOLDER:Table 3 TABLE_PLACEHOLDER:Table 4 ## References 1. 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--- title: Multi-Omics Analysis of Lung Tissue Demonstrates Changes to Lipid Metabolism during Allergic Sensitization in Mice authors: - Kedir N. Turi - Cole R. Michel - Jonathan Manke - Katrina A. Doenges - Nichole Reisdorph - Alison K. Bauer journal: Metabolites year: 2023 pmcid: PMC10054742 doi: 10.3390/metabo13030406 license: CC BY 4.0 --- # Multi-Omics Analysis of Lung Tissue Demonstrates Changes to Lipid Metabolism during Allergic Sensitization in Mice ## Abstract Allergy and asthma pathogenesis are associated with the dysregulation of metabolic pathways. To understand the effects of allergen sensitization on metabolic pathways, we conducted a multi-omics study using BALB/cJ mice sensitized to house dust mite (HDM) extract or saline. Lung tissue was used to perform untargeted metabolomics and transcriptomics while both lung tissue and plasma were used for targeted lipidomics. Following statistical comparisons, an integrated pathway analysis was conducted. Histopathological changes demonstrated an allergic response in HDM-sensitized mice. Untargeted metabolomics showed 391 lung tissue compounds were significantly different between HDM and control mice (adjusted $p \leq 0.05$); with most compounds mapping to glycerophospholipid and sphingolipid pathways. Several lung oxylipins, including 14-HDHA, 8-HETE, 15-HETE, 6-keto-PGF1α, and PGE2 were significantly elevated in HDM-sensitized mice ($p \leq 0.05$). *Global* gene expression analysis showed upregulated calcium channel, G protein–signaling, and mTORC1 signaling pathways. Genes related to oxylipin metabolism such as Cox, Cyp450s, and cPla2 trended upwards. Joint analysis of metabolomics and transcriptomics supported a role for glycerophospholipid and sphingolipid metabolism following HDM sensitization. Collectively, our multi-omics results linked decreased glycerophospholipid and sphingolipid compounds and increased oxylipins with allergic sensitization; concurrent upregulation of associated gene pathways supports a role for bioactive lipids in the pathogenesis of allergy and asthma. ## 1. Introduction Asthma is characterized by airway hyper-responsiveness, mucus hypersecretion, infiltration of the airway by eosinophils and type 2 (T2) immune response, and airway remodeling [1,2]. Evidence suggests that cytokine imbalance and metabolic perturbance are responsible for the inflammation and tissue damage resulting from asthma [3]. In addition to increased inflammation, both systemically and locally in the lung, this perturbance results in increased oxidative stress, decreased antioxidants, and increased inflammatory cytokine markers [4,5,6]. However, our understanding of allergic asthma etiology and biological mechanisms is incomplete. This is partly due to the invasive nature of lung sampling techniques, which is a major impediment in developing prophylaxis and treatment for asthma. Experimental animal models were developed to mimic the clinical symptoms and pathological sequalae of asthma to overcome the challenges with studying relevant human tissue. The mouse model of house dust mite (HDM)-induced allergic airways disease mimics many of the features of human asthma symptoms, including airway hyperreactivity and airway inflammation, and is increasingly used to elucidate asthma/allergic airways pathology and to evaluate new therapeutic agents [7]. However, allergic airways/asthma etiology and biological mechanisms in this experimental model were not well characterized. The application of high throughput ‘omics’ approaches to both human studies and animal models has shown great potential in identifying pathological mechanisms and biomarkers of asthma. For example, metabolomics measures a variety of small molecules that are part of a biological system and have potential to capture the cellular response to past and present exposures relevant to asthma etiology [8,9,10]. Since lung tissue provides an integrated, multi-cellular platform, a metabolomic investigation utilizing lung tissues may better illustrate the etiology of allergic airways/asthma and will have a significant translational value compared to those performed in isolated cells or in vitro systems [11]. Metabolomic analysis of bronchoalveolar lavage fluid (BALF) [12,13] and lung tissue [14] in sensitized mice and BALF and sputum of patients with allergic asthma [15,16] have uncovered a panel of potential allergic airway-related metabolic biomarkers and pathways. However, most of these studies did not take a multiplatform and systems approach and, hence, may have missed important relationships. To date, various ‘omics’ approaches increasingly implicated lipids as biomarkers for the pathogenesis and severity of asthma symptoms [17,18,19,20]. Specifically, excessive oxidative stress and its endogenous and exogenous reactive oxygen and nitrogen species, decreased activities of antioxidants, and increased production of bioactive lipids that are synthesized from arachidonic acid (AA) are all associated with airway inflammation and, consequently, with allergic asthma and its severity [21,22,23,24]. Conversely, the roles of endogenous bioactive oxylipins derived from eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) as counter-regulators of inflammation and activators of resolution is still being established [25,26,27]. These bioactive lipids, termed oxylipins, are rapidly metabolized and are challenging to detect through untargeted metabolomics analysis. However, targeted analysis of these molecules using tandem liquid chromatography mass spectrometry (LC/MS/MS) was used extensively in the analysis of these important lipid molecules [17,28,29]. Furthermore, since genetics plays a major role in regulation of the metabolome [30] and asthma etiology, integrating metabolomics with gene expression data enhances the potential to unravel relevant pathways in diseases with gene-X-environmental etiological components such as asthma and allergic airways [31,32]. Overlaying molecular pathways based on metabolomics and gene expression data help to extract more insightful and comprehensive snapshots of biological systems and molecular processes in the etiology of asthma. Therefore, the aim of this study is to understand the upstream molecular processes underlying allergic asthma etiology in HDM-induced allergic mice using a multi-omics approach that comprises untargeted metabolomics, targeted analysis of oxylipins, and transcriptomics of lung tissue. This integrated analysis of metabolomics, lipidomics, and gene expression data provides additional insight into novel links between metabolic, immune, and neuronal signaling pathways triggered by HDM sensitization which can be investigated for possible intervention targets in future studies. ## 2.1. Animals Six-week-old male BALB/cJ (BALB) mice were obtained from Jackson Laboratories (Bar Harbor, ME). This strain was chosen because it is Th2-dominant and commonly used in lung allergic airway models due to their classic allergic responses, including increased Th2-immune responses, eosinophilia, and airway hyperresponsiveness [33,34]. The mouse numbers used for each endpoint were based on animal requirements for significance in previous studies [35,36] as well as a power analysis. All mice were maintained on an ovalbumin (OVA)-free Teklad diet (Envigo). Mice were acclimated for one week prior to sensitization. Studies were conducted under a protocol (#01031) approved by the Institutional Animal Care and Use Committee at University of Colorado Anschutz Medical Campus (Aurora, CO). ## 2.2. HDM Sensitization Mice were sensitized to sterile filtered 25 µg HDM extract (HDM, GREER Labs; in 35 µL saline) or saline through internasal (i.n.) administration for 5 days/week for week 1 and then challenged with 25 µg HDM (35 µL saline) or 35 µL saline for 3 days/week for weeks 2–4 of the experiment (Figure 1). All mice used in this study were treated at the same time and were euthanized 24 h following the final dose of HDM in week 4. The HDM sensitization dose, frequency, and duration was based on a recently published 4-week HDM-induced allergic airways inflammation mouse model [37]. ## 2.3. Differential Cells Counts and Histology Blood was collected via cardiac puncture and, following processing using EDTA tubes (Thermo Fisher Scientific, Waltham, MA 02451, USA), plasma was snap frozen. Bronchoalveolar lavage fluid (BALF) was collected with Hanks balanced salt solution (HBSS), described previously [38,39], using $$n = 5$$ mice per group. Cell differentials and total protein (reflective of lung hyperpermeability) was performed on BALF, as performed in Cho [39] and Bauer [36]. Following lung perfusion with sterile saline, these lungs were also inflation fixed ($$n = 5$$) with $10\%$ neutral buffered formalin for 24 h, followed by processing by the University of Colorado Cancer Center (UCCC) Pathology Shared Resource. Hematoxylin and eosin (H&E), periodic acid–Schiff (PAS), and trichrome stained slides were performed for each of these mouse lungs ($$n = 5$$). In another group of mice ($$n = 4$$), non-lavaged and non-perfused lung lobes (with no lymph nodes) were divided for untargeted metabolomics, targeted lipidomics, and RNA transcriptomics assays. ## 2.4. Untargeted Metabolomics: Lung samples ($$n = 4$$ for control and $$n = 4$$ for HDM) for untargeted metabolomics analysis were prepared as previously described [40,41,42]. Briefly, lungs were homogenized using a bead homogenizer with methanol and small molecules were extracted from 100 µL lung tissue homogenate using methyl tert-butyl ether (MTBE). Aqueous and lipid fractions were analyzed separately by liquid chromatography mass spectrometry (LC/MS) on a quadrupole time-of-flight (6545 QTOF, Agilent Technologies, Santa Clara, CA 95051, USA) mass spectrometer using published methods [13,43], except that 10 µL of the lipid fraction samples were injected on the instrument. All samples were prepared in a single batch and, therefore, no batch-to-batch quality control (QC) sample was used to control for sample preparation variance. However, all experimental lung samples were spiked with 29 labeled authentic standards and an aliquot of each sample was pooled post sample preparation to make a pooled QC sample to control for LCMS instrument variance [13,43]. Following analysis of QC data to ensure reproducibility (see Text S1 for details on quality control), metabolomics spectral data were extracted and recursively filtered, aligned, and binned using Agilent Profinder ver 10.0 SP1 and Mass Profiler Professional Ver. 15.1 (MPP, Agilent Technologies, Santa Clara, CA 95051, USA) [42]. Compounds found in at least one blank were removed. Remaining compounds were limited to those found in $75\%$ of samples in at least one group (HDM or control). Aqueous samples were additionally limited to compounds eluting before 11.5 min since compounds eluting past this time had poor signal to noise ratios. Normalization was conducted using adjustment to total signal for all compounds not found in blanks. Compounds were annotated by searching a custom in-house database comprised of data from authentic standards and public databases consisting of compounds from METLIN, Lipid Maps, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Human Metabolome Database (HMDB), using accurate mass and isotope ratios. These compounds were designated Metabolomics Standards Initiative (MSI) level three [13]. Compounds matching in retention time and mass to compounds in the in-house database were designated MSI level one. ## 2.5. Quantitative Targeted Analysis of Oxylipins (Lipidomics) Liquid chromatography tandem mass spectrometry (LC/MS/MS) and isotope dilution was used to quantitate 87 pro-inflammatory and pro-resolving lipids and isoprostanes in plasma and lung using a single, validated assay [44,45]. Briefly, samples were extracted with methanol followed by solid phase extraction to enrich for oxylipins. Internal standards, comprised of labeled analogs corresponding to 12 molecules of various lipid subclasses, were added prior to extraction. Samples were analyzed using a triple quadrupole mass spectrometer (QQQ 6490, Agilent Technologies, Santa Clara, CA 95051, USA) as previously described [44,45,46]. ## 2.6. Global Gene Expression The RNA preparation and sequencing was carried out at the UCCC Genomics Core. mRNA was isolated from mice lung tissue using TRI-Reagent (Sigma-Aldrich, St. Louis, MO 68178, USA) followed by Zymo-Seq Ribo Free Total RNA Library Kit for the library preparation. cRNA (1.5 μg) was used for whole-genome gene expression direct hybridization assay with mouse WG-6 v2.0 Expression Beadchip (Illumina, San Diego, CA 92122, USA), following the manufacturer’s instructions. The average reads/bases quality for all the samples in the lane was at least $88\%$ ≥ Q30. The filtered reads distribution for all the samples in the lane ranged from approximately 11 M to 18 M clusters (22 M to 36 M paired end reads). Sequence data quality was evaluated using fastqcr, an R wrapper for freely available quality control software (FastQC) [47,48]. The software suites of Rsubread [49] and R package were used for mRNA read mapping, with the reference mice genome (GRCm38 primary assembly genome) and the feature counts function to quantify read counts. ## 2.7. Statistical Analysis Compounds from untargeted metabolomics were assigned class hierarchy if they had a KEGG compound number provided and were annotated by compound class, subclass 1, subclass 2, subclass 3, and subclass 4; this provided several options to analyze and visualize data [50]. Changes in compounds between HDM and control mice were evaluated by multiple t-testing using a false discovery rate (FDR) of $5\%$ and fold change for compounds were generated [50]. The number of significantly changed compounds between HDM-sensitized and control mice were counted based on the KEGG class annotation and visualized with bar plots. Similarly, compound abundance was aggregated by KEGG subclasses and compared between HDM-sensitized mice and control and visualized with boxplots [50]. Enrichment and pathway analyses were conducted for significantly different compounds. Metabolic reaction pathways were predicted to identify active and suppressed metabolic conversion based on upregulated and downregulated lipid compounds using Lipid Map’s BioPAN online software suite [51]. Metabolic network, network diffusion, and network topology and clustering analysis were conducted using combination of FELLA (R package) [52] and Cytoscape software suite [53]. Changes in oxylipins (from targeted lipidomics analysis) between HDM and control mice were evaluated by multiple t-testing using a false discovery rate (FDR) of $5\%$. Changes in BALF cells and protein were determined using t-tests (Graphpad Prism 9) on log transformed data, with $p \leq 0.05$ considered significant. Gene expression read count data were converted into log2 counts using the rlog function in DESeq2 and plotted to assess data quality [54]. The read count data was filtered for zero counts before differential expression analysis was conducted. *Differential* gene expression (log2 fold changes [log2FC]) was conducted using negative binomial generalized linear equation in DESeq2, which accounted for library size and group mean and variance internally [54]. The estimated log2FC were shrunk to aid visualization and ranking of genes and p-valued corrected for inflation and biases using bacon package [55]. Enrichment and pathway analysis were conducted for significantly different genes using BioMart suite retrieving GO and KEGG molecular and functional knowledge databases [56]. Joint metabolomics and gene expression data pathway analysis were conducted using KEGG molecular knowledge databases to understand the potential interactions and involvement between the compounds and genes that were significantly changed between HDM-sensitized and control mice in the biological process and molecular functions. All statistical analyses were performed using R software version 4.1.1 (https://www.r-project.org accessed on 25 August 2021). ## 3.1. Inflammatory Cells and Histopathology Changes in HDM-Sensitized Mice BALF inflammatory cell analysis demonstrated that significant increases in macrophages, PMNs, and eosinophils ($p \leq 0.05$) were observed in HDM-sensitized mice compared to control (Figure 2a). Lymphocytes and epithelial cells appeared to be elevated compared to control, but these increases were not significant, at $p \leq 0.08$ and $p \leq 0.1720$, respectively. Total protein was also significantly elevated in HDM-sensitized mice compared to control ($p \leq 0.0232$) (Figure 2b). These results demonstrate that an inflammatory response to HDM allergic sensitization occurred. The analysis of histopathological changes in lung by H&E staining showed the typical pathological features of allergic airways and asthma in HDM-sensitized mice compared to control (Figure 2c) including inflammatory cell infiltration, specifically peribronchial inflammation (Figure 2d,e, red arrow, inset). Increased collagen deposition was also observed in the HDM-exposed mice using trichome staining (Figure 2f) and some goblet cell hyperplasia was seen in the HDM-sensitized mice compared to controls (Figure 2g). Collectively, this model had numerous similarities to human asthma and was a valuable model to use for our additional studies below. ## 3.2. Differentially Regulated Compouds (Untargeted Metabolomics) in HDM-Sensitized Mice Following untargeted metabolomics analysis of lung tissue, 1316 compounds were determined to be present in at least $75\%$ of sample per group. Of these, 391 compounds were significantly different between the HDM and control mice (adjusted $p \leq 0.05$). Most of these compounds were not annotated and, therefore, were not pursued in downstream analysis and interpretations such as pathway enrichment analysis. The five most significantly upregulated compounds included 7-8-dihydro-L-biopterin, palmitoyl ethanolamide, a phosphatidylglycerol (PG [16:$\frac{0}{0}$:0]), sphinganine, and butyryl-L-carnitine (Table S1). The five most significantly downregulated compounds were Fagaramide, s-(5′-adenosyl)-l-homocysteine, adenine, PC(20:$\frac{4}{18}$:0), and PC(20:$\frac{3}{16}$:0) (Table S1). Note that these annotations were MSI level three and were hence considered putative. Changes were visualized using volcano plots for lipids (Figure 3a) and non-lipid compounds (Figure 3b). Figure 3c shows number of significantly up- and downregulated compounds in each KEGG subclass. Most of the upregulated compounds were in diacyglycerolphosphoserines, fatty acyls (including fatty acyl carnitines and primary amides), and glycerolphosphocholines (monoacylglycerolphosphocholines and diacylglycerolphosphocholines) pathways. Note that the diacylglycerophospholipids are generally referred to as glycerophospholipids while the monoacylated forms are referred to as lyso-glycerophospholipids; however, the KEGG nomenclature was used in the current study to allow for multi-omics analysis. Enrichment analysis demonstrated that the upregulated KEGG pathways were significantly (p-value < 0.05) enriched in glycerophospholipid metabolism, purine metabolism, and one carbon pool by folate pathways before FDR adjustment; however, none were significant after FDR adjustment (see Figure S1 for list of pathways and Figure S2 for list of predicted enzymes). The majority of downregulated compounds were in glycerophospholipid (including diacyglycerolphosphocholines, monocyglycerolphosphocholines, diacylglycerophosphoethanolamines, and 1-Z-alkenyl,2-acyglycerolphosphocholines, as shown in Table S1), and phosphosphingolipids (including ceramide phosphoethanolamines and ceramide phosphocholines [shingomyelins]) (Figure 3c). At least one compound was changed in the following pathways: glycerophosphoinositols, flavonoids, purines, and eicosanoids (only PGD2 was significant) pathways (Figure 3c). Enrichment analysis demonstrated that the upregulated KEGG pathways were significantly (p-value < 0.05) enriched in sphingolipid metabolism, glycerophospholipid metabolism, and taurine and hypotaurine metabolism pathways before FDR adjustment. However, only sphingolipid metabolism pathway was significant after FDR adjustment (see Figure S1 for list of pathways and Figure S2 for list of predicted enzymes). Pathways such as glycerophosphatidylcholines, phosphatidylserines, sphingoid bases, and purines contained a mix of up- and downregulated individual compounds; the results from above were based on the direction of the majority of the compounds. Moreover, expansion of compounds’ knowledge-based network (network diffusion) by including KEGG metabolic pathways and GO terms indicates that the dysregulated compounds were associated with inflammatory pathways (see Supplemental Text S1 and Figure S3 for detail of results). In addition, since most of the significantly altered compounds were lipids, we conducted an analysis of predicted reaction pathway for differentially abundant lipid compounds to identify most active lipid conversions in our experiment. The reaction prediction was conducted in Lipid Map’s BioPAN [51] software suite. The reaction pathway prediction showed that the most active conversion pathways were from phosphotidylcholines and phosphotidylethanolamines to phosphotidylserines and from sphingomyelins (n-acyl-sphing-4-enine-1-phosphocholine) to ceramides (n-acyl-sphing-4-enine) (Figure S4). ## 3.3. Differentially Regulated Oxylipins (Targeted Lipidomics) in HDM-Sensitized Mice A targeted quantitation of 87 oxylipins was conducted in plasma and lung tissue using mass spectrometry. Twenty-one plasma and twenty-eight lung lipid mediators had values above the detection limit for $80\%$ of the samples. In plasma, 12,13-epoxyoctadecenoic acid (12,13-EpOME; $$p \leq 0.003$$) and its downstream metabolites 9,10-dihydroxy-octadecenoic acid (9,10-DiHOME; $$p \leq 0.01$$), 12,13-dihydroxy-octadecenoic acid (12,13-DiHOME; $$p \leq 0.02$$), 9-hydroxy-octadecadienoic acid (9-HODE; $$p \leq 0.03$$), and 13-hydroxy-octadecadienoic acid (13-HODE; $$p \leq 0.05$$) were significantly higher in the HDM group compared to control, but only 12,13-EpOME was significant (adjusted $$p \leq 0.07$$) after adjusting for multiple-testing using FDR at $10\%$. In addition, analysis of lung tissue oxylipins showed that 11-hydroxydocosahexaenoic acid (11-HDoHE, $$p \leq 0.002$$), 12,13-dihydroxy-octadecenic acid (12,13-DiHOME, $$p \leq 0.05$$), 13-hydroxyoctadecatrienoic acid (13-(S)-HOTrE; $$p \leq 0.02$$), 14-hydroxy-docosahexaenoic Acid (14-HDHA, $$p \leq 0.002$$), 8-hydroxyeicosatetraenoic Acid (8-HETE, $$p \leq 0.002$$), 15-hydroxyeicosatetraenoic Acid (15-HETE, $$p \leq 0.02$$), (19,20-DiHDPA, $$p \leq 0.01$$), 6-keto-prostaglandin F1α (6-keto-PGF1α; $$p \leq 0.04$$), prostaglandin E2 (PGE2; $$p \leq 0.004$$) were significantly elevated in the HDM-sensitized group; but none were significant after adjusting for multiple testing (Figure 4; see Figures S5 and S6 for additional lipids identified in plasma and lung samples, respectively). ## 3.4. Differentially Expressed Genes (Global Gene Expression) in HDM-Sensitized Mice The global gene expression analysis of lung tissue showed that several genes (143 genes) were differentially expressed after adjusting for multiple testing at adjusted p-value of 0.05 and fold change cutoff value of 1.5, where the majority (88 genes) of the genes were upregulated (Figure 5 and Table S2). The top five upregulated genes included Col24a, Nlrp4g, Samd4b, Med29, and Ganab. Additional immune response genes that were upregulated in the HDM-sensitized group included Chil4, Chil6, Cxcr6, Macir, and Clec2g, and metabolism related upregulated genes included Atp10d and Ivd. Although not statistically significant, cytochrome c oxidase (Cox)-10, cytochrome P450 (Cyp450)-2E1, Cyp450-2j3, and cytosolic phospholipase A2 (cPla2)-g4, and elongation of very long chain fatty acids protein 4 (Elov4) were among many lipid metabolism regulation genes that were upregulated with log2 foldchange >2. The top five downregulated genes included Ces2a, Sptbn4, Hsd17b1, Nrxn2, and Gpr137c. Additional immune response genes that were downregulated in the HDM-sensitized mice included Btnl4, Lifr, Atm, and Zcchc9, and additional metabolism genes that were downregulated in the HDM-sensitized mice included Mtm1, Ggta, Akt2, Repin1, Rabgap1l, Pask, and Csad. The supportive literature for the functions of these genes are summarized in Table S3. To summarize the biological and molecular context of significantly expressed genes (multiple testing adjusted p-value < 0.05), we conducted enrichment analyses using the GO knowledge database. The GO biological process enrichment analysis showed that the following were the most enriched biological processes pathways for significantly upregulated genes in the HDM-sensitized mice compared to control: regulation of cardiac muscle (cell contraction) by regulation of the release and transportation of sequestered calcium ion, metal ion transport, collagen fibril organization, and calcium-mediated signaling. Regulation of vesicle fusion, central nervous system neuron axonogenesis, regulation of glycogen biosynthetic process, regulation of torc1 signaling, and regulation of B-cell proliferation were the five most enriched biological processes for downregulated genes in HDM-sensitized mice compared to control (Table 1). Similarly, the GO molecular function enrichment analysis of significantly expressed genes showed that voltage-gated calcium channel activity involved in muscle cell action potential, benzodiazepine receptor binder, solute and sodium bicarbonate symporter activity, oncostatin M receptor activity, leukemia inhibitory factor receptor activity, and g protein-coupled serotonin receptor binding were the five most enriched pathways for upregulated genes. Testosterone dehydrogenase [nad] activity, phosphatidylinositol-3,5-bisphospate 3-phosphatase activity, neuroligin family protein binding, ccr5 chemokine receptor binding, and annealing activity were the five most downregulated molecular functions in downregulated genes in HDM compared to control mice (Table 2). ## 3.5. Joint Pathways of Differentially Regulated Metabolic Compounds and Differentially Expressed Genes in HDM-Sensitized Mice A joint KEGG pathways enrichment analysis was conducted for significantly changed compounds and genes between HDM-sensitized and control mice to understand the comprehensive metabolic pathway dysregulation that we hypothesized as occurring with allergic responses to HDM. Accordingly, glycerophospholipid and sphingolipid metabolism were the most jointly enriched KEGG molecular pathways (Figure S7) affected by HDM sensitization. In addition, joint enrichment of insulin secretion, cholinergic synapse, adrenergic signaling in cardiomyocytes, choline metabolism, calcium signaling, and apelin signaling pathways was seen. However, only glycerophospholipid metabolism and sphingolipid metabolism were significant after FDR adjustment. Genes that were involved in regulation of lipid phosphorylation, including Mtm1, Ggta, and Mtmr4, were downregulated. ## 4. Discussion This study aimed to better understand the effects of allergen sensitization on metabolic and immune signaling pathways by comparing small molecule and gene expression differences between HDM-sensitized and control mice using a multi-omics approach. Overall, our findings confirmed previous results by our group [13] and others that demonstrated the dysregulation of purine, glycerophospholipid, and sphingolipid metabolism, as well as the AA and LA oxidation products 9-HODE and 12,13-EpOME (and its downstream metabolites) in allergen-sensitized mice. Furthermore, the current study demonstrated that additional signaling pathways, such as cardiolipin and insulin secretion pathways, were dysregulated in allergen-sensitized mice. Our results from untargeted metabolomics indicated that the majority of dysregulated compounds were glycerophospholipids, similar to previous reports [12,57]. Compounds within the class of phosphosphingolipids and certain sub-classes of glycerophospholipids, including glycerophosphatidylcholines, glycerophosphatidylethanolamines, and glycerophosphatidylinositols were downregulated, whereas diacyglycerolphosphoserines and glycerophosphate were upregulated. These compounds are all part of the highly interconnected glycerophospholipid pathway, whereby glycerophosphate (1,2-diacyl-sn-glycerol-3-phosphate) acts as a precursor to the glycerophospholipids through the intermediates phosphatidic acid, sn-1,2-diacylglycerol, and/or CDP-diacylglycerol. Similarly, the diacylglycerophospholipids are metabolized to corresponding monoacylated forms and can also be used to generate phosphatidic acid. It is possible that glycerophosphatidylcholines, glycerophosphatidylethanolamines, and glycerophosphatidylinositols were depleted to meet cellular demands during inflammation. For example, the prediction model based on our data shows that, in HDM-sensitized mice, phosphatidylcholines and phosphatidylethanolamines were actively converting to phosphatidylserines, whereas sphingomyelins were actively converting to ceramides. Under normal physiological conditions, significant amounts of phosphatidylserines turn over to form phosphatidylethanolamines [58]; however, the conversion may be reversed in disease-like conditions, such as allergic airways. The importance of phospholipids in asthma pathogenesis were previously described [59]. For example, phosphatidylcholines were decreased in asthmatic lungs [12,57] and children with risk allelles in the 17q12-21 genetic region have decreased sphingolipid synthesis [60]. This is consistent with our finding that glycerophosphatidylcholine levels were decreased in sensitized mouse lung. Similarly, decreased levels of glycerophosphatidylethanolamines and glycerophosphatidylinositols and increased diacyglycerolphosphoserines in plasma samples among asthmatic patients were previously observed [61]. Although not directly measured in the current study, the observed downregulation of glycerophosphatidylcholines in lung following allergic sensitization may be interpreted to reflect metabolism of EPA or DHA via cPLA2 to more pro-resolving and/or anti-inflammatory oxylipins. In addition, glycerophosphotidylcholines have roles in anti-inflammatory mechanisms including suppression of TNF production in macrophages and interference with pro-inflammatory cytokines secreted by phagocytes [62,63,64]. Finally, the precursor of diacyglycerolphosphoserines, phosphatidylserine, may play an important role in T2 immune response induction and airway hyperreactivity [65]. Thus, by extension, upregulated diacyglycerolphosphoserines in HDM-sensitized mice in our study is consistent with allergic asthma pathogenesis. As previously mentioned, membrane glycerophospholipids such as glycerophosphoserine contain fatty acids such as AA, LA, EPA, and DHA, which are precursors of bioactive lipid mediators such as oxylipins and endocannabinoids [66,67,68,69]. While the untargeted metabolomics analysis of lung tissue showed that most glycerophospholipids were decreased in HDM-sensitized mice, the targeted analysis of oxylipins in the same tissue led to an increase in these bioactive lipids in HDM-sensitized mice. In addition, we observed upregulated but statistically insignificant genes related to the release and metabolism of membrane fatty acids to bioactive lipids such as Cox, Cyp450s, and cPla2 as well as calcium binding regulator genes. Thus, based on the observed depletion of glycerophospholipids and increased oxylipins, along with the upregulation of related genes, we speculate that allergic sensitization results in a conversion of membrane lipids to oxylipins. In support of this, we observed increases in AA-derived 8-HETE, 15-HETE, PGE2, and 6-keto-α-prostaglandin F1α (6keto-α-PF1α), which are known for both pro-inflammatory and anti-inflammatory properties often depending on receptor and tissue type (see Figure 6 for illustration). For example, PGE2 was shown to increase mast cell degranulation and IL-6 production, IL-8-induced neutrophil recruitment, vasodilation, among others [70]. 6-keto-α-prostaglandin F1α is a less potent and stable derivative of prostacyclin I2 (PGI2) known to serve as antiplatelet aggregation though the upregulation of cAMP activities [71,72] and immune regulators [73]. Increased LA oxidation products such as 9-HODE and 12,13-EpOME (and its downstream metabolites 9,10-DiHOME and 12,13-DiHOME) were also observed in HDM-sensitized mice, which is consistent with their known pro-inflammatory roles. For example, 9-HODE plays a role in inflammation by activating the G protein coupled receptor 132 (G2A), inhibiting the peroxisome proliferator-activated receptor γ (PPARγ), and increasing production of inflammatory cytokines such as IL-6, IL-8, and GM-CSF [74]. Similarly, 12,13-EpOME (and its downstream metabolites) increased inflammation by activating NF-κB and AP-1 transcription factors and inhibiting PPARγ [75,76,77]. Generally, increased LA oxidation products associate with features of severe airway obstruction, lung remodeling, increase in epithelial stress related to pro-inflammatory cytokines and airway neutrophilia in mice [78]. A potential future intervention study could inhibit LA oxidation to determine if the inflammatory response to allergic challenges and symptoms of asthma improve. Alpha linoleic acid (αLA) and DHA-derived oxylipins known for their pro-resolving characteristics were also increased in sensitized mice. For example, 13-(S)-HOTrE, which is derived from αLA, exhibited anti-inflammation properties through inhibition of NF-κB and NLRP3 and through activation of PPARγ [79,80]. Likewise, DHA-derived 19,20-DiHDPA was shown to modulate leukocyte recruitment and infiltration via reduced ICAM-1 and E-selectin expression in endothelial cells [81,82]. The increase in these oxylipins during HDM sensitization suggests a counterbalance exists between pro-inflammatory and pro-resolving oxylipins. Moreover, lipids are also known to modulate the activity of voltage-gated ion channels including calcium channel and G protein–signaling mechanisms [83,84]. As previously mentioned, phospholipases such as cPLA2 hydrolyze glycerophospholipids by binding to membrane G-protein-coupled receptors and releasing free fatty acids, such as AA and LA, from the membrane [85,86]. Our pathway analysis of differentially expressed genes confirmed the involvement of ion channels and bioactive lipids signaling pathways during HDM sensitization. We observed the upregulation of pathways such as release and transportation of sequestered calcium ion release, sequestration and transportation, metal ion transport, collagen fibril organization, and calcium mediated signaling in sensitized mice. The increase in Ca2+ in cytoplasm is associated with asthma pathology including activation of respiratory smooth muscle, mast cells, vagal reflex stimulation, secretion of the airway submucous glands, and chemotaxis of eosinophils [87,88]. Based on combined results from gene expression and metabolomics data, we speculate that one effect of Ca2+ on asthma pathology may be through modulation of lipid signaling pathways. This study used multi-omics to comprehensively illustrate molecular pathways involved during allergic sensitization in an animal model; however, it did have several limitations. First, the experiment was only conducted in male mice, which limited our ability to explore sex differences. Second, the lung tissue sample had to be rationed for histology, untargeted metabolomics, targeted lipidomics, and global gene expression data generation from different mice; thus, the metabolomics and gene expression data were not generated from the same animal. Third, the lung lobes for the omics studies were not perfused and, therefore, may have contained blood. While this could have impacted the responses observed, the filtering of compounds during data processing and the application of MTC during data analysis minimized the potential for artifacts related to blood contamination. In addition, previous studies utilized non-perfused tissues for molecular and omics research since immune cells infiltrate the lung via the blood and may contribute to the inflammatory response observed. Finally, the majority of our metabolomics data were annotated to an MSI level three and may have included mis-annotations, which can affect downstream pathway analysis. ## 5. Conclusions The metabolomics data demonstrated downregulation of glycerophosphatidylcholines, glycerophosphatidylethanolamines, phosphosphingolipids, and glycerophosphoinositols, whereas several diacyglycerolphosphoserines and glycerophosphate were upregulated in HDM-sensitized mice. A focused analysis of oxylipins from lung tissue and plasma showed consistent results with previous studies linking decreased glycerophospholipid and sphingolipid compounds with increased bronchoreactivity and increased 12,13-EpOME (and its downstream compounds) and prostaglandins with allergic sensitization. The global gene expression analysis added another layer by linking differential changes in bioactive lipids to up- and downregulated signaling pathways such as calcium ion channels and G protein–signaling. For example, calcium channels and G protein–signaling modulate cPLA2 for the release of membrane lipids, which are substrates for downstream bioactive lipids. In summary, our study, using multi-omic analyses of mouse lung tissue during HDM sensitization, provided additional insight into molecular cascades during allergic sensitization including supporting known roles for AA metabolism. ## References 1. 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--- title: BMAL1 Promotes Valvular Interstitial Cells’ Osteogenic Differentiation through NF-κ B/AKT/MAPK Pathway authors: - Yefan Jiang - Song Wang - Wenfeng Lin - Jiaxi Gu - Geng Li - Yongfeng Shao journal: Journal of Cardiovascular Development and Disease year: 2023 pmcid: PMC10054744 doi: 10.3390/jcdd10030110 license: CC BY 4.0 --- # BMAL1 Promotes Valvular Interstitial Cells’ Osteogenic Differentiation through NF-κ B/AKT/MAPK Pathway ## Abstract Objectives: Calcific aortic valve disease (CAVD) is most common in the aging population and is without effective medical treatments. Brain and muscle ARNT-like 1 (BMAL1) is related to calcification. It has unique tissue-specific characteristics and plays different roles in different tissues’ calcification processes. The purpose of the present study is to explore the role of BMAL1 in CAVD. Methods: The protein levels of BMAL1 in normal and calcified human aortic valves and valvular interstitial cells (VICs) isolated from normal and calcified human aortic valves were checked. HVICs were cultured in osteogenic medium as an in vitro model, and BMAL1 expression and location were detected. TGF-β and RhoA/ROCK inhibitors and RhoA-siRNA were applied to detect the mechanism underlying the source of BMAL1 during HVICs’ osteogenic differentiation. ChIP was applied to check whether BMAL1 could directly interact with the runx2 primer CPG region, and the expression of key proteins involved in the TNF signaling pathway and NF-κ B pathway was tested after silencing BMAL1. Results: *In this* study, we found that BMAL1 expression was elevated in calcified human aortic valves and VICs isolated from calcified human aortic valves. Osteogenic medium could promote BMAL1 expression in HVICs and the knockdown of BMAL1 induced the inhibition of HVICs’ osteogenic differentiation. Furthermore, the osteogenic medium promoting BMAL1 expression could be blocked by TGF-β and RhoA/ROCK inhibitors and RhoA-siRNA. Meanwhile, BMAL1 could not bind with the runx2 primer CPG region directly, but knockdown of BMAL1 led to decreased levels of P-AKT, P-IκBα, P-p65 and P-JNK. Conclusions: *Osteogenic medium* could promote BMAL1 expression in HVICs through the TGF-β/RhoA/ROCK pathway. BMAL1 could not act as a transcription factor, but functioned through the NF-κ B/AKT/MAPK pathway to regulate the osteogenic differentiation of HVICs. ## 1. Introduction CAVD is the most common valvular disease, with high morbidity and mortality rates [1]. It results in aortic valve thickening, calcification and eventually, hemodynamic abnormality. Thoracotomy and interventional surgeries are the only effective treatments and no medical therapies have yet been developed [2]. VICs are the most abundant cells in aortic valves. Although valvular endothelial cells take part in the development of CAVD, great evidence has proven that VICs’ phenotype change is the main cause [3,4]. During disease initiation and progression, VICs undergo myofibroblastic and osteogenic differentiation, thereby evoking extracellular matrix remodeling, collagen deposition, nucleation loci formation and eventually, osteoblastic VIC-mediated bone formation [5]. The circadian clock genes regulate the circadian rhythm and maintain normal physiological function; their disorder may result in diseases [6,7]. These clock genes exist in both brain and peripheral tissues, known as central and peripheral clock genes [8]. The central clock genes existing in the suprachiasmatic nucleus (SCN) regulate the circadian rhythm and their disorder may lead to the disturbance of the 24 h light/darkness cycle and eventually, illness [9,10]. The peripheral clock genes can be controlled by both central clock genes and peripheral stimuli. They can regulate the local cell physiology without a disturbed circadian rhythm [11,12]. *Clock* genes can take part in the calcification process. They are not only related to physiological calcification, such as bone formation and dental development, but also pathological calcification, including vessel and tendon calcification [13,14,15,16,17]. BMAL1 acts as a core clock gene and is necessary for the circadian rhythm [18,19]; it is involved in the calcification process. Runt-related transcription factor 2 (runx2), as the key transcription factor associated with osteogenic differentiation, showed 24 h periodicity in the SCN and bone and its periodicity disappeared in BMAL1-KO mice [20]. BMAL1 participates in physiological calcification; it can affect bone formation, dental development and the osteogenesis of bone marrow stromal cells [21,22,23]. Moreover, it can also contribute to pathological calcification, such as atherosclerosis and mandibular dysplasia [24,25]. BMAL1 can serve as a transcription factor alone or combined with CLOCK to form heterodimers, which can activate the transcriptional activity of downstream genes [24,26,27]. Meanwhile, it can affect the calcification process through the BMP/Wnt/p53 signaling pathway [22,28,29]. BMAL1 shows unique tissue-specific characteristics and plays different roles in the calcification processes in different tissues [30,31]. Its role in CAVD still needs further exploration. We hypothesized that BMAL1 promoted valve calcification. The purpose of this study is to determine [1] whether BMAL1 accumulation is associated with CAVD; [2] the effect of BMAL1 on HVICs’ osteogenic differentiation; and [3] the mechanism by which BMAL1 exerts its effect. ## 2.1. BMAL1 Expression Is Increased in Calcified Human Aortic Valves To confirm our hypothesis, we analyzed the gene expression profiles of normal and calcified valves from GSE51472 and found that calcified valves displayed higher expression of BMAL1 (Figure 1A). Furthermore, we collected normal and calcified valves and immunohistochemical staining and Western blotting were applied to determine BMAL1 expression. The patients’ data are summarized in Table 1; no significant differences were observed between the two groups. Alizarin red staining, immunohistochemical staining and Western blotting showed that—compared with normal valves—with the expression of runx2 or deposition of calcium increased in calcified valves, BMAL1 expression was also increased (Figure 1B–D). These results suggested that BMAL1 might play an important role in CAVD. ## 2.2. BMAL1 Is Associated with Osteogenic Differentiation of HVICs Since HVICs undergo phenotype differentiation into osteoblast-like cells in CAVD, and the phenotype change of HVICs is the main cause of CAVD, we further investigated whether BMAL1 was associated with HVICs’ osteogenic differentiation. Firstly, we incubated HVICs with osteogenic medium for 7 days to stimulate osteogenic differentiation (OS group) and analyzed the gene expression profiles of HVICs from the control group (normal medium) and OS group by RNA-seq. In total, 221 upregulated genes and 143 downregulated genes were detected (Figure 2A). KEGG analysis showed that the circadian rhythm and entrainment were the top two pathways (Figure 2B). Among the typical circadian-rhythm- and entrainment-related genes, nine genes displayed a change greater than two-fold with $p \leq 0.05$, and BMAL1 was one of them (Figure 2C). Secondly, we incubated HVICs with osteogenic medium for 3 days (OS group) and checked the protein expression of BMAL1. The protein level of BMAL1 was higher in the OS group (Figure 3A,B). Thirdly, we identified the protein expression of HVICs isolated from normal and calcified valves and found that BMAL1 expression was upregulated in HVICs isolated from calcified valves (Figure 3C,D). Fourthly, to check whether runx2 expression showed circadian rhythms synchronizing with BMAL1 expression, we detected the mRNA expression of runx2 from 2:00 A.M. to 22:00 P.M. every 4 h, and the result demonstrated that runx2 expression showed circadian rhythms synchronized with BMAL1 expression (Figure 3E). To confirm whether BMAL1 was the critical point in the osteogenic differentiation of HVICs, we silenced BMAL1 in HVICs and checked the protein expression of runx2 and alp activity. We found that, after silencing BMAL1, the protein level of runx2 and alp activity decreased (Figure 3F–H). Thus, BMAL1 is associated with the osteogenic differentiation of HVICs and is the key point in this process. ## 2.3. Osteogenic Medium Promotes BMAL1 Expression through TGF-β/RhoA/ROCK Pathway A previous study reported that the RhoA/ROCK pathway could transduce signals provided by extracellular stiffness into cells and regulate the activity of the core circadian clock complex [32]. We hypothesized that RhoA/ROCK was also involved in the osteogenic medium promoting BMAL1 expression. We incubated HVICs in normal and osteogenic medium, and Western blotting showed that RhoA expression was increased in osteogenic medium (Figure 4A,B). Further, RhoA/ROCK inhibitor Y-27632 (10 μM) from Selleck and RhoA-siRNA was added separately. Western blotting showed that after the RhoA/ROCK inhibitor and RhoA-siRNA were added, BMAL1 expression was reduced (Figure 4C–F). As Figure 2A shows, the TGF-β signaling pathway was one of the top 20 pathways of KEGG enrichment. Moreover, the RhoA/ROCK pathway is also included in the TGF-β signaling pathway (Figure 4G). We considered whether this signaling pathway was involved in the osteogenic medium promoting BMAL1 expression. TGF-β inhibitor SB525334 (10 μM) from Selleck was added and Western blotting showed that the protein level of BMAL1 was lower after its addition (Figure 4H,I). Moreover, RhoA expression was also decreased (Figure 4H,I). Therefore, TGF-β/RhoA/ROCK was the key signaling pathway in the osteogenic medium promoting BMAL1 expression. ## 2.4. BMAL1 Cannot Act as a Transcription Factor in Regulating Osteogenic Differentiation of HVICs Considering that BMAL1 can serve as a transcription factor alone or combined with CLOCK to form heterodimers that can activate the transcriptional activity of downstream genes, we needed to determine whether BMAL1 could act as a transcription factor here [24,26,27]. HVICs were incubated in normal and osteogenic medium as the control and OS group separately. Firstly, we checked whether osteogenic medium could facilitate the movement of BMAL1 into the nucleus via immunofluorescence staining. The results showed that BMAL1 existed in both the cytoplasm and nucleus and BMAL1 expression was increased in the cytoplasm in the OS group compared with the control group (Figure 5A). Secondly, we checked the protein level of BMAL1 in the cytoplasm and nucleus. Western blotting showed that more BMAL1 existed in the cytoplasm when HVICs were incubated with osteogenic medium, and no significant difference existed in the protein expression of BMAL1 in the nucleus between the control and OS group (Figure 5B–E). Thirdly, we used the JASPAR database to predict the possible binding sites of BMAL1 on the runx2 promoter CPG region. Four possible binding sites were detected (Figure 5F). Lastly, we determined whether BMAL1 could bind with runx2 promoters through ChIP. Although four possible binding sites were detected, BMAL1 could not bind with runx2 promoters directly (Figure 5G). Taken together, these results suggested that BMAL1 could not act as a transcription factor in regulating the osteogenic differentiation of HVICs. ## 2.5. BMAL1 Promotes HVIC Osteogenic Differentiation through NF-κ B/AKT/MAPK Pathway Following the silencing of BMAL1 in HVICs, substantial differences in gene expression were observed versus the control group. KEGG pathway enrichment analysis was applied and the TNF signaling pathway and NF-κ B pathway were among the top 20 pathways in KEGG enrichment (Figure 6A). Further, the protein levels of phosphorylated AKT, IκBα, p65 and JNK were checked. Western blotting showed that the protein levels of P-AKT, P-IκBα, P-p65 and P-JNK were decreased after BMAL1 was silenced (Figure 6B,C). These results provide an indicator that BMAL1 may promote HVICs’ osteogenic differentiation through the NF-κ B/AKT/MAPK pathway. ## 3. Discussion CAVD is a disease threatening many people’s health, and the osteogenic differentiation of HVICs is the main cause. In this study, we found that BMAL1 was associated with CAVD. Compared with normal valves, BMAL1 expression was elevated in calcified valves. Additionally, BMAL1 can enhance HVICs’ osteogenic differentiation. Osteogenic medium could promote BMAL1 expression in HVICs through the TGF-β/RhoA/ROCK pathway, and knockdown of BMAL1 resulted in a reduced protein level of runx2. Moreover, the NF-κ B/AKT/MAPK pathway was involved in the signaling mechanism for the osteogenic differentiation of HVICs that was induced by BMAL1. These data offer novel insights into the pathogenesis of CAVD. The circadian clock genes were first discovered in 1994 [18]. In vertebrates, clock genes can mediate circadian rhythms through a transcription-translation-based autoregulatory feedback loop [33]. Circadian rhythms have been implicated in various physiological processes [6]. Disturbed circadian rhythms could lead to diseases such as cancer [34]. Previous studies have reported that circadian rhythms may be associated with calcification. The incidence of osteoporosis and fracture is higher among shift workers and a short duration of sleep increased the relative risk of coronary artery disease [9,35]. Animal models confirmed that atherosclerosis and vascular calcification were aggravated in mice with disturbed circadian rhythms [21,36]. In our study, we found that the mRNA level of runx2 in HVICs showed 24 h periodicity, which offers an indication that CAVD development may be associated with circadian rhythms and disordered day and night rhythms might result in the progression of CAVD. Of course, further investigation is still needed. BMAL1 is one of the clock genes and is related to tumors, metabolic diseases, aging, etc. [ 18,37,38]. BMAL1−/− mice lost circadian rhythmicity and displayed decreased activity, body weight and longevity [31]. Moreover, BMAL1−/− mice also had pathological changes related to calcification, such as tendon calcification and a low bone mass phenotype [19,31]. In our work, we did not study the role of BMAL1 in SCN but in aortic valves and circadian rhythms, which might not be disturbed. Previous studies have confirmed that BMAL1 in peripheral tissues might participate in the calcification process. Mao et al. found that downregulating BMAL1 in bone marrow stromal cells played an inhibitory role in osteogenic differentiation [30]. Liu et al. showed that knockdown of BMAL1 in OCCM-30 cells (an immortalized murine cementoblast cell line) resulted in the downregulation of osteogenic markers and reduced formation of mineralized nodules [39]. Our study presented a similar result. The protein level of BMAL1 was increased in calcified valves. HVICs in osteogenic medium displayed the upregulation of BMAL1 and osteogenic markers. After silencing BMAL1, the osteogenic differentiation of HVICs was inhibited. These results proved that BMAL1 is a key point during HVICs’ osteogenic differentiation. In SCN, BMAL1 acts as a central clock gene and is regulated by the light/dark cycle, food intake and activity [40]. However, in HVICs, it serves as a peripheral clock gene. Although peripheral clock genes can be regulated by central clock genes, they are also regulated by the cellular microenvironment [41]. For example, Williams et al. reported that clock genes in epithelial and stromal cells can be regulated by their mechano-matrix environment [42]. In our study, RNA-seq of HVICs in control and osteogenic medium showed that the circadian rhythm and entrainment were the first 2 pathways among the top 20 pathways of KEGG enrichment, which supports our hypothesis that HVICs can sense the osteogenic medium and adapt to it. The fact that the protein level of BMAL1 was also increased in HVICs in osteogenic medium supports our hypothesis further. Yang et al. reported that the RhoA/ROCK pathway transduced signals provided by extracellular stiffness into cells and regulated the activity of the circadian clock complex [32]. We hypothesized that the RhoA/ROCK pathway was also involved in the osteogenic medium promoting BMAL1 expression in HVICs. To verify our hypothesis, a RhoA/ROCK inhibitor and RhoA-siRNA were applied and the osteogenic medium promoting BMAL1 expression was inhibited. In total, 3 signaling pathways were among the top 20 pathways of KEGG enrichment; only the TGF-β signaling pathway contained the RhoA/ROCK pathway. To check the function of the TGF-β pathway here, we added the TGF-β inhibitor and the osteogenic medium promoting BMAL1 expression was also inhibited. These data confirmed that the osteogenic medium could promote HVICs’ osteogenic differentiation through the TGF-β/RhoA/ROCK signaling pathway. BMAL1 can serve as a transcription factor alone or combined with CLOCK to form heterodimers, which can activate the transcriptional activity of downstream genes [24,26,27]. It is a basic helix-loop-helix PAS domain transcription factor that exerts its function by binding to the E-box elements of CACGTG-type (or CACGTT-type-like) in the promoters of its downstream target genes. Zhou et al. showed that BMAL1 could bind directly to the Opg promoter and upregulate its expression [43]. Min et al. reported that BMAL1 was a direct regulator of insulin-mediated osteoblast differentiation by increasing the promoter activity of BMP2 in MC3T3-E1 cells [44]. In our study, JASPAR database analysis showed four potential BMAL1 binding sites on the runx2 promoter CPG region. However, ChIP showed that BMAL1 could not bind with runx2 promoters directly. Moreover, immunofluorescence and Western blotting showed that more BMAL1 existed in the cytoplasm only when HVICs were treated with osteogenic medium. These data confirmed that BMAL1 could not act as a transcription factor in regulating runx2 expression. RNA-seq of HVICs treated with and without BMAL1-siRNA showed that the TNF signaling pathway and NF-κ B pathway were among the top 20 pathways of KEGG enrichment, and Western blotting confirmed that the protein levels of P-AKT, P-IκBα, P-p65 and P-JNK were decreased after BMAL1 was knocked down. We concluded that BMAL1 promoted HVICs’ osteogenic differentiation through the NF-κ B/AKT/MAPK pathway. ## 4.1. Patient Selection and Specimen Acquisition The protocol of this study was approved by the Ethical Committee of Jiangsu Province Hospital, affiliated to Nanjing Medical College, China, and conducted in accordance with the ethical standards stated in the Declaration of Helsinki. Informed consent was obtained from all patients before surgery. Calcified aortic valves were obtained from 50 patients with CAVD who underwent aortic valve replacement. Control normal aortic valves were collected from 50 age-matched patients who underwent heart transplant or Bentall procedures (acute aortic dissection). ## 4.2. Cell Culture and Treatment HVICs were obtained from normal and calcified valves using collagenase I digestion, as described previously [4]. Interstitial cells were cultured in Dulbecco’s modified *Eagle medium* containing $1\%$ penicillin G and streptomycin and $10\%$ fetal bovine serum at 37 °C and $5\%$ CO2. The cells from passages 3 to 5 were used for the following experiments and incubated in osteogenic medium to stimulate osteogenic differentiation, as previously described [45]. Here, osteogenic medium contained $1\%$ fetal bovine serum, 50 mg/mL ascorbic acid, 100 nmol/L dexamethasone and 10 mmol/L β-glycerophosphoric acid. ## 4.3. Immunohistochemistry Aortic valves were harvested, rinsed with cold phosphate-buffered saline, fixed in $4\%$ paraformaldehyde and embedded in paraffin. Immunohistochemical staining was performed, as previously described, with the following antibodies: BMAL1 (Proteintech, 1:200), runx2 (Proteintech, 1:200) [4]. ## 4.4. Immunofluorescence Staining HVICs were fixed with $4\%$ paraformaldehyde for 10–20 min, and subsequently permeabilized with $0.5\%$ Triton-X-100 for 10 min. Then, the cells were treated with BMAL1 (Proteintech, 1:200) overnight at 4 °C. Primary antibodies were removed and fluorescent-conjugated secondary antibody (Proteintech, 1:5000) was added. Images were taken with a fluorescence microscope (Leica). ## 4.5. Western Blotting Protein expression was demonstrated by Western blotting, following instructions described previously [4]. Moreover, cell cytoplasm and nucleus proteins were separated using kits from Beyotime. The following antibody dilutions were used: BMAL1 (Proteintech, 1:500), runx2 (CST, 1:1000), alkaline phosphatase (ALP) (R&D, 1:500), gapdh (Proteintech, 1:1000), Lamin B1 (Proteintech, 1:1000), phospho-JNK MAPK (cst, 1:1000), phospho-NF-kB (cst, 1:500), phospho-AKT (cst, 1:1000), phospho-IκBα (cst, 1:500) and phospho-p65 (cst, 1:1000). ## 4.6. Real-Time Polymerase Chain Reaction RNA Analysis RNA of cells was isolated as previously described [4]. Real-time reverse transcription polymerase chain reaction (RT-PCR) assays were carried out using the One Step qRT-PCR Probe Kit from Vazyme. Primers were as follows: BMAL1 (F: 5′-TGCCCTCTGGAGAAGGTGG-3′; R: 5′-GGAGGCGTACTCGTGATGTT-3′); runx2 (F: 5′-TCGCCTCACAAACAACCACA-3′; R: 5′-GCTTGCAGCCTTAAATGACTCT-3′); and gapdh (F: 5′-CATGTTCGTCATGGGTGTGAACCA; R: 5′-AGTGATGGCATGGACTGTGGTCAT-3′). Results were normalized to Gapdh and the delta/delta CT calculation method was used to analyze the data. ## 4.7. Chromatin Immunoprecipitation (ChIP) ChIP assays were conducted using the Chromatin Immunoprecipitation Kit (Millipore), following the manufacturer’s protocol. Briefly, cells were crosslinked and lysed. DNA fragments less than 500 bp were prepared by sonication in ChIP dilution buffer. Proteins were immunoprecipitated in ChIP dilution buffer using BMAL1 antibodies (1:250) and then incubated overnight at 4 °C. Crosslinking was reversed at 65 °C in elution buffer (50 mmol/L Tris–HCl, 10 mmol/L EDTA and $1\%$ SDS, pH 8.0) for 5 h, after which DNA was isolated. PCR was performed using primers specific to the BMAL1 hypersensitive site on the runx2 promoters. The primer sequences used are shown in Table S1. Furthermore, agarose gel electrophoresis was applied. ## 4.8. Silencing BMAL1 or RhoA To knock down BMAL1 or RhoA, cells ($80\%$ confluence) in 6-well plates were incubated with a small interfering RNA (siRNA) (50 nmol/L), using Lipofectamine 3000 (Invitrogen) and Opti-Men (Life Technologies), according to the manufacturer’s instructions. Meanwhile, control cells were treated with scrambled siRNA. The medium was changed 12 h after transfection; 48 h later, the cells were harvested for protein expression analysis. The sequence of BMAL1 siRNA is TCACCAAGATGACATAGGA, and the sequence of RhoA siRNA is AGAACTATGTGGCAGATAT. ## 4.9. Detection of mRNA Profiles RNA-sequencing (RNA-seq) quantification was utilized to investigate changes in cell mRNA profiles among different treatments performed. Isolated RNA was sequenced by BGI Co., Ltd. and LC-Bio Technology Co., Ltd. Sequencing results were further analyzed in order to identify differentially expressed genes (DEGs) and perform Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis using the R language. ## 4.10. Alizarin Red Staining Alizarin red staining for cell calcium deposits was performed as described previously [4]. For tissues, deparaffinized sections were incubated with alizarin red solution for 5–10 min, and excess dye was removed by washing with distilled water. ## 4.11. Alkaline Phosphatase (ALP) Activity ALP activity in the cell lysates was assayed using a colorimetric assay kit (Beyotime) by measuring the p-nitrophenol release in absorbance at 405 nm. Results are presented as relative ALP activity normalized to that of the control cells. ## 4.12. Statistical Analysis Continuous data were expressed as mean ± standard deviation. The differences between 2 groups were assessed by Student’s t-test. 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--- title: Baseline Plasma Osteopontin Protein Elevation Predicts Adverse Outcomes in Hospitalized COVID-19 Patients authors: - Stelvio Tonello - Davide D’Onghia - Daria Apostolo - Erica Matino - Martina Costanzo - Giuseppe Francesco Casciaro - Alessandro Croce - Eleonora Rizzi - Erika Zecca - Anita Rebecca Pedrinelli - Veronica Vassia - Paolo Ravanini - Maria Grazia Crobu - Manuela Rizzi - Raffaella Landi - Luigi Mario Castello - Rosalba Minisini - Gian Carlo Avanzi - Mario Pirisi - Daniele Lilleri - Mattia Bellan - Donato Colangelo - Pier Paolo Sainaghi journal: Viruses year: 2023 pmcid: PMC10054745 doi: 10.3390/v15030630 license: CC BY 4.0 --- # Baseline Plasma Osteopontin Protein Elevation Predicts Adverse Outcomes in Hospitalized COVID-19 Patients ## Abstract More than three years have passed since the first case, and COVID-19 is still a health concern, with several open issues such as the lack of reliable predictors of a patient’s outcome. Osteopontin (OPN) is involved in inflammatory response to infection and in thrombosis driven by chronic inflammation, thus being a potential biomarker for COVID-19. The aim of the study was to evaluate OPN for predicting negative (death or need of ICU admission) or positive (discharge and/or clinical resolution within the first 14 days of hospitalization) outcome. We enrolled 133 hospitalized, moderate-to-severe COVID-19 patients in a prospective observational study between January and May 2021. Circulating OPN levels were measured by ELISA at admission and at day 7. The results showed a significant correlation between higher plasma concentrations of OPN at hospital admission and a worsening clinical condition. At multivariate analysis, after correction for demographic (age and gender) and variables of disease severity (NEWS2 and PiO2/FiO2), OPN measured at baseline predicted an adverse prognosis with an odds ratio of 1.01 (C.I. 1.0–1.01). At ROC curve analysis, baseline OPN levels higher than 437 ng/mL predicted a severe disease evolution with $53\%$ sensitivity and $83\%$ specificity (area under the curve 0.649, $$p \leq 0.011$$, likelihood ratio of 1.76, ($95\%$ confidence interval (CI): 1.35–2.28)). Our data show that OPN levels determined at the admission to hospital wards might represent a promising biomarker for early stratification of patients’ COVID-19 severity. Taken together, these results highlight the involvement of OPN in COVID-19 evolution, especially in dysregulated immune response conditions, and the possible use of OPN measurements as a prognostic tool in COVID-19. ## 1. Introduction The glyco-phosphoprotein osteopontin (OPN) is a constitutive part of the extracellular matrix of different tissues such as bone, kidney, and epithelial cells and is involved in several functions such as wound healing, bone turnover, tumorigenesis, and ischemia and, in the soluble form, is a regulator of inflammatory response [1,2]. OPN receptors are integrins and CD44 variants that promote adhesion, migration, and survival in different cell types [3]. This cytokine is encoded by a gene in a cluster of “SIBLING” family proteins (Small Integrin Binding Ligand N-linked Glycoprotein) located on chromosome 4 (4q13) [1,3]. Highly conserved sequence motifs, together with post- translational modifications, contribute to the multifunctional nature of OPN [4]. Although OPN is classified as a pro-inflammatory cytokine [5], it has also shown a role in inflammation, including in COVID-19 [6]. OPN’s role in innate immunity is demonstrated by its protective function in infectious diseases [7]. In fact, it was shown to contribute to the mucosal defense against viral pathogens [8]. Low concentrations of OPN are usually detected in healthy subjects, while high OPN plasma levels have been associated with chronic inflammation states and in the pathogenesis of autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis, and cancer [9,10,11,12]. In particular, OPN is involved in the inflammatory response during the infection of pathogens such as bacteria and viruses by recruiting neutrophils and macrophages at site of infection, activating T cells, and triggering the cytokine response [2,13,14]. SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a positive single-stranded RNA virus responsible for the COVID-19 pandemic [15] responsible for more than 6 million deaths worldwide [16]. SARS-CoV-2 infection can lead to a variety of clinical manifestations ranging from an asymptomatic or mild flu-like syndrome to severe cases with interstitial pneumonia with respiratory failure, requiring assisted ventilation, that may evolve into multi-organ failure and eventually death; it is often difficult to predict at hospital admission [7,17,18,19]. In most severe cases, in fact, SARS-CoV-2 infection determines an acute, uncontrolled inflammatory reaction (cytokine storm) in the lungs [20]. In this context, some authors have highlighted the role of matrix metalloproteinases (MMPs) such as MMP-8 and MMP-2 in upregulating the immune response and the activation of inflammation mediators including OPN. Moreover, high MMPs levels in plasma have been associated with the damage of lung parenchyma [21]. Additionally, it has been shown that there is a loss of interferon (IFN) production after SARS-CoV-2 infection at the pulmonary level. Consequently, there is a rapid activation of pathogenic Th1 cells that secrete pro-inflammatory cytokines such as interleukins (IL-1β, IL-6, IL-8, and IL-12), interferon-γ-inducible protein 10 (IP-10), monocyte chemoattractant protein 1 (MCP-1), and interferon-γ (IFN-γ) [3,7]. In this inflammatory contest, there are complex activities mediated by multiple cells and factors that influence the immune system and epithelia activities. The rationale of our study was to assess of OPN involvement in this framework since it is known to play either a physiologic or pathophysiologic role [1,2,3,8]. The present study evaluates the role of circulating OPN levels as a potential biomarker of COVID-19 severity and as a prognostic tool for clinical practice. ## 2.1. Patients We conducted a prospective observational study that included 133 COVID-19 hospitalized patients in COVID-19 wards (including sub-intensive units) of the “AOU *Maggiore della* Carità” in Novara. These patients were enrolled between January and May 2021. We included in the study only patients that gave a signed informed consent. The inclusion criteria were age > 18 years, assessment of SARS-CoV-2 positivity by antigenic test or RT- PCR, with disease symptoms that did not exceed 12 days. The exclusion criteria were advanced oncological disease, advanced renal failure (stage V), and clinical conditions suggesting irreversibility or that led to immediate ICU admission. After signing the informed consent, patients underwent venous blood sampling upon entry and after 7, 14, and 21 days when possible. Patients were treated, unless contraindicated, following the standard COVID-19 care protocol imposed by the “AOU *Maggiore della* Carità” (oxygen mask, glucocorticosteroids, and low-molecular-weight heparin (LMWH)). These patients are part of a larger multicentric observational study cohort called the BIAS study (Baseline *Immunity status* effect on SARS-CoV-2 presentation and evolution: comparison between immuno-competent and immunocompromised patient study). The study protocol was approved on 14 January 2021 by the local Ethical Committee (CE $\frac{7}{21}$) and was conducted in strict accordance with the Declaration of Helsinki. ## 2.1.1. SARS-CoV-2 Variants In the period from 26 March 2021 to 30 June 2021, the Microbiology and Virology Laboratory of the “AOU *Maggiore della* Carità” in Novara carried out 236 analyses for the detection of SARS-CoV-2 variants by using a multiplex RT-PCR Real-Time assay for the simultaneous detection and identification of the presence of mutations in the S gene of the SARS-CoV-2 virus RNA, which are responsible for the Alpha variants of the virus (B.1.1.7 lineage) and the Beta (B.1.351 lineage), and Gamma (P 1 lineage) variants of the virus (Seegene MuDT™, Seegene Inc., Arrow Diagnostics, Italy). Data revealed a prevalence of Alpha V1 variant characterized by the presence of S N501I gene mutation and $\frac{69}{70}$ deletion (141 of 236 cases) and a low presence of Beta V2 and Gamma V3 variants (48 of 236 cases) characterized by the presence of S N501I gene mutation and E484K deletion. The trend of the prevalence of the variants in the first semester of 2021 in *Italy is* shown in Figure 1. In 47 cases, it was not possible to determine the variant. No cases of Omicron were reported in our cohort and in general in Italy in the first 6 months of 2021. These results were in accordance with the overall incidence in Italy in that period. Furthermore, this is in accordance with WHO data that demonstrated that Omicron appeared in Italy starting from December 2021. Although we had no complete variant characterization for all the patients included in this study, we assumed a similar proportion incidence of variants. ## 2.1.2. Circulating OPN Levels Determination Plasma OPN was measured by enzyme-linked immunosorbent assay (ELISA) using a kit commercially available (R&D Systems DuoSet Elisa DY6488, McKinley, MN, USA). A Victor X4 microplate reader (Perkin Elmer, Waltham, MA, USA) was used to measure the absorbance values. A calibration curve in a range of 0–1000 pg/mL range was used for sample amount determination, as suggested by the manufacturer. ## 2.1.3. Endpoint Definition The correlation between OPN plasma levels at admission and at day 7 of hospitalization and the disease progression represented the endpoint. The progression was defined as unfavorable (death or admission in ICU) or recovery (National Early Warning Score 2 (NEWS2) ≤ 2 for at least 24 h in the first 2 weeks or discharge). ## 2.1.4. Blood Sample Blood samples were obtained in EDTA vacutainer at two time points, namely at hospital admission (baseline, t0) and at day 7 (t7), and immediately processed. Samples were stored at −80 °C. ## 2.1.5. Routine Laboratory Evaluation Blood samples from each patient were analyzed in clinical practice to obtain a complete cell count; a routine biochemistry panel including creatinine, alanine aminotransferase (ALT), and aspartate aminotransferase (AST); and an inflammatory panel composed of coagulation/fibrinolysis (D-dimer), ferritin, and C-reactive protein (CRP). ## 2.1.6. Data Collection We stored in a web-based encrypted database (REDCap platform) patients’ laboratory parameters, clinical parameters, demographics, and therapeutic schedule. We reviewed medical records for each patient and collected relevant clinical data from hospital admission (t0, baseline) to study exit (either positive or negative diagnosis, up to a maximum of 28 days). ## 2.1.7. Statistical Analyses Clinical and laboratory data were obtained from REDCap database and correlated with OPN levels to evaluate if there was a statistically significant correlation toward the required endpoint. The continuous variables were expressed as medians and interquartile range (IQR) to describe central tendency and dispersion. The frequencies (percentages) were used to describe the categorical variables. Mann–Whitney U-test was used to perform the statistical analyses for continuous variables. The multivariable regression models were built with the statistically significant values, as identified by univariate analysis. We built receiver operator characteristics curves (ROC) for the parameters of interest to determine the prognostic cut-off. The statistically significant threshold was set at $p \leq 0.05$ (two-tailed). Graphs were created using GraphPad Prism 9.4.0 (GraphPad Software, La Jolla, CA, USA). Statistical analyses were performed with MedCalc® Statistical Software version 20.014 (MedCalc Software Ltd., Ostend, Belgium) and Statistica for Windows release 12 (TIBCO Soft-ware Inc, Palo Alto, CA, USA. ## 3. Results During the Italian third pandemic wave, from January to May 2021, 133 patients admitted to non-ICU wards of “*Maggiore della* Carità” University Hospital (Novara, Italy) for moderate or severe COVID-19 were enrolled and followed-up prospectively. Table 1 and Figure 2 summarize detailed demographic and hospital admission (baseline, t0) clinical conditions of the patient cohort included in this study. Overall, $74.4\%$ of the enrolled patients at hospital admission day showed moderate respiratory failure (100 ≤ PiO2/FiO2 < 200), while $6.8\%$ had a severe clinical presentation (PiO2/FiO2 < 100). Some patients were already receiving COVID-19-related treatment before hospital admission. Main treatments included corticosteroids ($53.4\%$), azithromycin ($35.3\%$), and heparin ($30.8\%$). The median baseline NEWS2 confirmed the severity of clinical presentations with a score of 5, IQR 4–6 [15]. In this 133-patient cohort, 29 patients ($21.8\%$) had an outcome that was negative since there was ICU admission or death, while 87 patients ($64.44\%$) reached a National Early Warning Score 2 (NEWS2) ≤ 2 for at least 24 h in the first 2 weeks or discharge. Interestingly, OPN levels at hospitalization day correlated with clinical evolution of the patients, as shown in Table 2. In fact, patients with significantly higher OPN levels were associated with negative progression of the disease. Furthermore, our data showed that patients with lower OPN plasma concentration at hospitalization day had faster clinical recovery ((NEWS2) ≤ 2 for at least 24 h in the first 2 weeks or discharge) although this difference was not statistically significant, as shown in Table 3. Moreover, the correlation between OPN levels and clinical output lost its significance at day 7 from hospitalization, as described in Table 2 and Table 3. Multivariate analysis demonstrated the prognostic role of OPN towards a negative end point and disease severity parameters at admission, such as NEWS2 and PiO2/FiO2, was retained after the correction for demographic variables such as gender and age, as shown in Table 4. Moreover, we analyzed any possible correlation between OPN levels at baseline (t0) and other laboratory parameters related to clinical severity or inflammation status. Table 5 shows the significant correlation with C-reactive protein (CRP), IP10, and MCP-1. We built an ROC curve for baseline plasma OPN to predict the adverse prognosis based on the results obtained from the correlation analyses. For the ROC analyses, sensitivity, defined as “positivity in disease”, refers to the proportion of subjects who have the target condition and are considered true positives, while specificity is defined as “negativity in health” and refers to the proportion of subjects without the target condition that are true negatives. In our simulation, we defined one target condition: the severe disease evolution. Figure 3 shows that OPN levels higher than 437 ng/mL are predictive of a negative disease evolution (area under the curve (AUC) = 0.649, $83\%$ sensitivity, $53\%$ specificity), with a likelihood ratio of 1.76 ($95\%$ confidence interval (CI): 1.35–2.28). ## 4. Discussion In this prospective observational study, we evaluated the plasma concentration of OPN in a cohort of 133 hospitalized COVID-19 patients at the “AOU *Maggiore della* Carità” in Novara (Italy), enrolled between January and May 2021. The Microbiology and Virology Laboratory of the hospital “AOU *Maggiore della* Carità” in Novara routinely performed variant analyses in infected patients. During the period considered in our study, from January 2021 to May 2021, clinical data showed that the prevalent variant in our patients was Alpha (B.1.1.7 lineage), characterized by the presence of the S N501I gene mutation and the $\frac{69}{70}$ deletion. During the months in which patients were enrolled, other variants were also found, including the Beta V2 (B.1.351 lineage) and Gamma V3 (P 1 lineage), characterized by the presence of the S N501I gene mutation and the E484K deletion. In the last months in which we enrolled patients, the variant that infected most patients were Delta. No Omicron variant was detected during this period, in accordance with national survey that reported that Omicron appeared in Italy in December 2021. In our cohort, the variant characterization was determined for most patients, and although for some patients, it was not available since at the time of recruitment the patients could be admitted with an antigenic test, it reflected the overall incidence in this period. The virulence and the experimental data here described are thus related to the EU1, Alpha, and Gamma but not Omicron variant. In fact, the Alpha variant appeared in December 2020 and in early February 2021 accounted for approximately $25\%$ of cases and reached its peak in mid-April, accounting for more than $90\%$ of cases. The Beta variant was reported in few patients. In Italy and in our region, the Gamma variant appeared at the beginning of January and peaked at in the first week of May, with around $15\%$ of cases. The Delta variant appeared in Italy in March but with very few cases (less than $3\%$) and increased considerably at the beginning of June, peaking between July and November 2021. *In* general, in the beginning of January 2021, in Italy, we $62\%$ of cases were EU1 and $18\%$ Alpha and in mid-March, $77\%$ were Alpha, $10\%$ EU1, and $4\%$ were of the Gamma variant. At the end of June, $39\%$ were Alpha, $10\%$ Gamma, and $45\%$ Delta variant. We observed that baseline plasma OPN levels in these patients directly correlated with clinical status, and higher OPN levels were demonstrated in patients with adverse prognosis and disease progression with respect to all other patients. The principal pathogenetic mechanism associated with disease severity and death in COVID-19 patients is an excessive inflammatory response to SARS-CoV-2 infection, which is associated with vascular damages [22,23,24,25]. In this context, OPN might have a pivotal role since it is known to be involved in thrombosis pathophysiology driven by chronic inflammation [26,27]. Indeed, the activation of the innate immunity is responsible for severe hyperinflammatory status, and high levels of OPN correlate to a hyper activation of the immune system that might result in cytokine storm [28,29,30]. In COVID-19, there is a lung-damaging process that involves multiple factors and direct or undirect activation of hyper inflammation due to specific actors such as, for example, MMPs [21]. Since alveolar impairment in this disease is due to vessel injury and local diffuse thrombotic damage [31], high circulating levels of OPN might be associated with the initiation or progression of these events, along with a beneficial early-response mechanism to limit viral infection damages [32]. Noticeably, we also demonstrated a significant correlation between OPN and high levels of C-reactive protein, MCP1, and IP10. These proteins are known to be involved in initiation and progression of infectious diseases, and their transient early surge significantly correlates with SARS-CoV-2 viral load in mild patients [33,34,35]. In particular, IP-10 is secreted in response to interferon-gamma (IFNγ) by different cell types including monocytes, endothelial cells, and fibroblasts [36], and it evokes a range of inflammatory responses, acting as a chemotactic agent for dendritic cells, NK cells, monocytes/macrophages, and T cells [37]. Accumulating evidences indicate for IP-10 an association with the severity of the disease, making it a useful biomarker for predicting COVID-19 progression [38,39]. Moreover, our group previously demonstrated that IP-10 measured at hospital admission in a cohort of SARS-CoV-2-positive patients positively correlated with disease severity and adverse prognosis and inversely with faster recovery [40]. Furthermore, OPN is involved in stimulation of smooth muscle proliferation of arterioles after endothelial damage, which are events well documented in acute COVID-19 physiopathology [41,42] but that may be also associated with the development of a fibrotic phenotype, so OPN could represent a potential predictor factor of pulmonary fibrosis that may occur in post-COVID syndrome [17,18,19,25,43,44]. Further investigations are needed to confirm this hypothesis. from a pathophysiologic point of view, it is not surprising that, according to our report, high OPN concentration in patients with severe prognosis is associated with the increased inflammatory status responsible for the irreversible or hardly reversible respiratory failure. Our data confirm and expand in a larger and more homogeneous cohort of patients the observation reported by other authors [45,46]. Hayek and colleagues demonstrated that elevated circulating levels of OPN in 341 patients treated for COVID-19 in four tertiary care centers in four Western countries directly reflect disease severity and represent an independent risk factor for a more severe clinical course [47]. We described that plasma OPN levels measured at hospital admission above a cut-off of 437 ng/mL predict with good accuracy a worse prognosis. All these finding, taken as a whole, indicate that OPN might contribute to accurate early diagnosis and prognosis for pauci-symptomatic patients that access COVID-19 hospital wards. The plasma level assessment of this protein has the potentiality to be integrated in a panel of known biomarkers that have been described so far for a reliable risk stratification of the patients [40,48,49,50,51]. It is noteworthy that none of the biomarkers described so far in the literature are specific for this disease, thus indicating that integration would be the optimal approach. This study has several limitations since it focuses on patients hospitalized for COVID-19 with moderate or severe symptoms. Thus, it is not possible to extend our results directly to patients with mild symptoms or even to asymptomatic patients. Furthermore, the single-center nature of this study and a multi-center prospective endorsement of the results obtained is mandatory before recommending the measurement of OPN in clinical practice. Despite these limitations, OPN assessment may enrich the diagnostic tools to help stratify COVID-19 patients’ severity at admission to hospital wards and to plan more specific therapies at the very early stage of the disease. ## 5. Conclusions This study is a prospective observational cohort that evidenced the possibility of using the plasma OPN concentration at hospital admission to predict which patients might undergo a more severe COVID-19 evolution. 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--- title: Unveiling Chemical, Antioxidant and Antibacterial Properties of Fagonia indica Grown in the Hail Mountains, Saudi Arabia authors: - Abdel Moneim E. Sulieman - Eida Alanaizy - Naimah A. Alanaizy - Emad M. Abdallah - Hajo Idriss - Zakaria A. Salih - Nasir A. Ibrahim - Nahid Abdelraheem Ali - Salwa E. Ibrahim - Bothaina S. Abd El Hakeem journal: Plants year: 2023 pmcid: PMC10054747 doi: 10.3390/plants12061354 license: CC BY 4.0 --- # Unveiling Chemical, Antioxidant and Antibacterial Properties of Fagonia indica Grown in the Hail Mountains, Saudi Arabia ## Abstract The Aja and Salma mountains in the Hail region are home to a variety of indigenous wild plants, some of which are used in Bedouin folk medicine to treat various ailments. The purpose of the current study was to unveil the chemical, antioxidant and antibacterial properties of *Fagonia indica* (Showeka) grown widely in these mountains, as data on the biological activities of this plant in this remote area are scarce. XRF spectrometry indicated the presence of some essential elements, which were in the order of Ca > S > K > AL > CL > Si > P > Fe > Mg > Na > Ti > Sr > Zn > Mn. Qualitative chemical screening revealed the presence of saponins, terpenes, flavonoids, tannins, phenols and cardiac glycosides in the methanolic extract ($80\%$ v/v). GC–MS showed the presence of 2-chloropropanoic acid $18.5\%$, tetrahydro-2-methylfuran $20.1\%$, tridecanoic acid 12-methyl-, methyl ester $2.2\%$, hexadecanoic acid, methyl ester $8.6\%$, methyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl) propionate $13.4\%$, methyl linoleate $7.0\%$, petroselinic acid methyl ester $15\%$, erucylamide $6.7\%$ and diosgenin $8.5\%$. Total phenols, total tannins, flavonoids, DPPH, reducing power, -carotene and ABTS IC50 (mg/mL) scavenging activity were used to measure the antioxidant capabilities of Fagonia indica, which exhibited prominent antioxidant properties at low concentrations when compared to ascorbic acid, butylate hydroxytoluene and beta-carotene. The antibacterial investigation revealed significant inhibitory effects against *Bacillus subtilis* MTCC121 and *Pseudomona aeruginosa* MTCC 741 with inhibition zones of 15.00 ± 1.5 and 12.0 ± 1.0 mm, respectively. The MIC (minimum inhibitory concentration) and MBC (minimum bactericidal concentration) ranged between 125 to 500 μg/mL. The MBC/MIC ratio indicated possible bactericidal efficacy against *Bacillus subtilis* and bacteriostatic activity against Pseudomona aeruginosa. The study also showed that this plant has anti-biofilm formation activity. ## 1. Introduction Medicinal plants have been used as drugs since ancient times. The interest in medicinal plants has resurged in recent decades due to tremendous scientific reports that showed their remarkable in vitro efficacy as antimicrobial agents [1], antiviral agents [2], antioxidants [3], anticancer agents [4], and many more bioactive properties. In the current century, with the development of medical research, the severity of illness has also risen. For the treatment of complex disorders, new medications are being created, but these medications also come with a variety of side effects, ranging in severity from mild to severe. According to the World Health Organization (WHO), multidrug-resistant tuberculosis and Gram-negative bacteria have become a global health-threatening issue, and the WHO has called on member states to make greater efforts into researching and developing new antibiotics to control this dilemma [5]. The use of herbs for their therapeutic benefits is known as herbal medicine, sometimes known as herbalism or botanical medicine [6]. Numerous studies have shown that certain plants contain various compounds, such as peptides, aldehydes, alkaloids, phenols, saponins, polysaccharides, terpenoids, steroids, flavonoids and tannins, which may have critical restorative effects against bacteria, fungi, or viruses [7,8,9,10]. Herbal plants produce and contain a variety of chemical substances that have an impact on humans. Many higher plants have been used as anti-infection remedies [11]. On the other hand, it seems that natural remedies are more potent than their synthetic counterparts, and have minimal side effects (Nisar et al., 2018). Oxidative stress is a good example for this claim. Oxidative stress is a state in which oxidative powers are stronger than antioxidant systems because the balance between them has been upset [12]. Plants produce a large amount of antioxidants, such as phenolic compounds, flavonoids, polyphenolics, and tannins, that stop the damage that reactive oxygen species can do to cells; therefore, medicinal plants have a lot of antioxidants that are beneficial for health maintenance [13]. The Arabian *Peninsula is* desert-dominated and biodiversity-poor. However, the Kingdom of Saudi Arabia (KSA) boasts a diverse flora, including many edible and medicinal plants and many types of trees, herbs, and shrubs, although scientists have not yet shown significant interest in its potential therapeutic compounds [14]. The Kingdom of Saudi Arabia’s natural plant life inhabits a considerable portion of the Hail area, which is also home to many animals and plants. Numerous plant species from various families and orders have been found in the Hail area. Native plants in Hail were frequently used for multiple purposes, such as food, herbal medicine and grazing animals’ nutrition. The Aja and Salma Mountains (Figure 1) and Jabal Rumman are only a few of the mountains that make up the Hail region’s diverse topographical environment. In addition, there are several valleys, including Wadi Al-Adi’a and Al-Hamima, and several reefs, including Sha’ab Al-Sahba and Shu’ib Shatib. In addition, the area is home to plains, dunes, streams and several small pools of water that emerge after rain [15,16]. Fagonia spp. is a desert plant widely spread throughout the Middle east, North Africa, the Horn of Africa, Iran, and India. It is a woody tree or shrub that can grow to a height of two, three, and occasionally five meters. The plant is grayish-green in color, and its branches are basal. A white cork husk covers the stem, and when the husk is scraped, a viscous milky liquid leaks out. Taxonomically, *Fagonia is* a member of the Zygophyllaceae family, which includes over 22 genera and more than 250 types. Regarding the morphology, *Fagonia indica* is considered one of the most important members of the genus Fagonia. It is a tiny, spiky bush that grows to a height of 60 cm and a width of about 100 cm [17,18]. It has been used as a medicinal plant in folk medicine in Pakistan, India, and the Far East, and it is rumored to have unique therapeutic benefits and tremendous goodness. It has a wide range of traditional applications, including for diarrhea, crises, urinary secretions, and liver issues. Additionally, they may have less effectiveness as a powerful antibacterial agent against various hazardous microorganisms, due to neck abscesses. Research has demonstrated that the plant affects blood pressure, the neurological system, cancer, and liver disorders [19,20]. The effectiveness of these mixes against bacteria needs to be better understood, and scant information is available on the antibacterial characteristics, as well as on the chemical and antioxidant characteristics of the plant under study from this remote area. To the best of our knowledge, there are no data on the biological activities of *Fagonia indica* grown in the Hail Mountains, Saudi Arabia. Therefore, the current study aimed to investigate the chemical composition of Fagonia indica, and to determine its possible antibacterial and antioxidant activities using different standardized methodologies. ## 2.1. Phytochemical Screening of Fagonia indica Most people concur that plants’ medicinal properties are due to their bioactive phytochemical components [21]. Thus, investigations on plant components can provide scientific justification for the traditional uses of these plants. The results of the phytochemical analysis revealed the presence of cardiac glycosides, saponins, terpenes, flavonoids, tannins, and phenols in the methanol extract ($80\%$ v/v) from *Fagonia indica* (Table 1). Phytochemical compounds are secondary metabolites generated by plants for specific activities essential to the plant’s survival in its environment, as well as its for capability to withstand biotic and abiotic stresses. These substances have direct or indirect multi-functional effects on eukaryotic cells, prokaryotic cells and viruses, but have no function in plant growth or development [22]. As an example, inflammation is hypothesized to be reduced by polyphenols and flavonoids by inhibiting the production of pro-inflammatory chemicals [23]. Additionally, the polyphenols are antimicrobial. Since many pathogenic microorganisms have developed the ability to survive current treatments at clinically significant concentrations, their eradication may benefit from antibacterial action [24]. ## 2.2. GC–MS Analysis of Fagonia indica Gas chromatography coupled with mass spectroscopy is a crucial tool for analyzing chemical substances. The mass spectrum supplies qualitative data about a substance’s chemical constituents. The GC–MS chromatogram of the methanol extract of *Fagonia indica* is shown in (Figure 2). The peak retention time, peak area percentage, height percentage and mass spectral fragmentation features of the chromatograms were compared with those of recognized compounds in the library of the National Institute of Standards and Technology (NIST) [25]. From the GS–MS chromatogram, nine peaks were identified. As presented in Table 2 and Figure 3 are the chemical compounds and their percentages in methanolic extract of Fagonia indica. The detected phytochemicals were 2-chloropropanoic acid $18.5\%$, tetrahydro-2-methylfuran $20.1\%$, tridecanoic acid, 12-methyl-, methyl ester, $2.2\%$, hexadecanoic acid, methyl ester $8.6\%$, methyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl) propionate $13.4\%$, methyl linoleate $7.0\%$, petroselinic acid methyl ester $15\%$, erucylamide $6.7\%$ and diosgenin $8.5\%$. According to the findings, tetrahydro-2-methylfuran accounted the highest percentage of phytochemicals ($20.1\%$), whereas tridecanoic acid, 12-methyl-, methyl ester accounted the lowest percentage ($2.2\%$) of the chemicals, as depicted in Figure 2. The compounds identified were primarily plant fatty acids (2-chloropropanoic acid, tridecanoic acid, 12-methyl-, methyl ester, hexadecanoic acid, methyl ester, methyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl) propionate, methyl linoleate, petroselinic acid methyl ester and erucylamide), carbohydrates (tetrahydro-2-methylfuran) and sterols (diosgenin). It has been documented the literature that *Fagonia indica* contains a number of phytochemicals, including flavonoids, alkaloids, terpenoids, saponins, tannins, sterols, anthraquinones and coumarin. However, phytochemicals, such as flavonoids, alkaloids, terpenoids, tannins, coumarin and anthraquinones, were not detected in the current study. Meanwhile, the presence of alcohols, fatty acids, heterocyclics and esters have been reported in methanolic extracts of this plant [26]. On the other hand, a GC–MS analysis of many non-polar and polar plant extracts demonstrated the existence of flavonoids, terpenoids, alkaloids, tannins and sterols [27,28]. It is well documented the majority of sterol compounds have anti-cancer, anti-inflammatory, immunomodulatory, and even antiviral properties [29]. Although their therapeutic effects have not been established, carbohydrates may enhance the efficacy of other physiologically important substances. Furthermore, carbohydrates have also been employed to create polysaccharide immunomodulatory effects, which have potential uses in vaccines and in medicine. As a result, the combined active ingredients found in each plant may have greater therapeutic efficacy than a single isolated molecule [29]. Numerous biological processes involving fatty acids, such as their anti-inflammatory characteristics, help organisms defend themselves [30]. According to the findings of a number of studies, *Fagonia indica* can both aid in the prevention of bacterial and fungal diseases, and speed up the body’s recovery from their effects [31]. ## 2.3. Energy Dispersive X-ray Fluorescence Analysis The energy dispersive X-ray fluorescence spectrometer is a non-destructive detector that has the ability to detect a wide range of elements, from Na to Am. The elemental analysis of the *Fagonia indica* plant resulted in the detection of 14 elements. Table 3 presents the concentrations of K, Ca, Ti, S, Ni, Mn, Fe, AL, Cl, Si, Na, Sr, Zn and Mg detected in a *Fagonia indica* sample. From the table, it can be noticed that the elemental concentrations were in the order of Ca > S > K > Al > Cl > Si > P > Fe > Mg > Na > Ti > Sr > Zn > Mn. The accumulated metal ions had both direct and indirect effects on bacteria. By integrating into bacterial proteins, the dissolved ions had an indirect impact on bacteria by rendering those proteins inactive or dysfunctional. It is believed that when metals dissolve, active radicals are created that directly harm bacteria, causing the cell wall to burst and leading to death [32]. Furthermore, using energy dispersive X-ray fluorescence examination, Table 3 demonstrates that no heavy metals such as Pb and Cd were found. In recent years, the presence of some heavy metals such as Cd, Co, Cr and Cu, due to the accumulation of residues and pollutants in agricultural soil and in cultivated medicinal plants, has become an issue of interest and research, as medicinal plants are freely sold in open-air markets without chemical or biological analysis [33,34]. ## 2.4. Antioxidant Activities Free radicals are a byproduct of the body’s usual metabolic activity in biological systems. By scavenging free radicals, antioxidants defend us against several ailments [35]. Total phenols, total tannins, flavonoids, DPPH, reducing power, beta-carotene, and ABTS IC50 (mg/mL) scavenging activity were used to measure the antioxidant capabilities of *Fagonia indica* in comparison to unveiled standard molecules (Table 4). The acquired results show promising antioxidant properties at low concentrations when compared to ascorbic acid (AA), butylate hydroxytoluene (BHT) and beta-carotene, as compared with the results of [35,36]. Total phenols, total tannins, flavonoids, DPPH, reducing power, -carotene and ABTS IC50 (mg/mL) scavenging activity were used to measure the antioxidant capabilities of *Fagonia indica* in comparison to well-known standard molecules (Table 3). Comparing the obtained values to those for ascorbic acid (AA), butylate hydroxytoluene (BHT) and β-carotene, the data show potential antioxidant benefits at low doses. Fagonia indica contained the following amounts of total phenols, total tannins and total flavonoids: 3.72 ± 0.05 mg GAE/g, 24.14 ± 0.65 mg TAE/g and 136.05 ± 0.45 mg QE/g, respectively. The addition of an antioxidant can drastically reduce the stability of the free radical DPPH. In this research, it was investigated at what sample concentrations the DPPH radical scavenging activity was $50\%$ inhibited (IC50). The methanol extract of *Fagonia indica* had an average IC50 value of 00.06 ± 3.53 (mg/mL), which suggests significant antioxidant activity. The presence of an antioxidant can quickly reduce the stability of the free radical DPPH, and it absorbs (UV-Vis) strongly and visibly at 517 nm. The methanol solutions’ decreased ability to absorb the DPPH radical at 517 nm indicates increased antioxidant activity. In this experiment, the sample concentrations that resulted in a $50\%$ inhibition (IC50) of the DPPH radical scavenging activity were found. DPPH-scavenging action and efficiency of the extraction solvents was compared in this research using the IC50 value of the DPPH scavenging activity. A lower IC50 value indicated more antioxidant activity. The results of this study revealed that the plant contains tannins, flavonoids and total phenolic content. The different extracts can bleach stable ABTS and O2 free radicals; researchers can assess their capacity for free radical scavenging. The extracts’ capacities to neutralize O2 and ABTS radicals were significantly lower than those of the standards. Polyphenols (such as phenolic acids, tannins, coumarins, anthraquinones and flavonoids) with redox properties—enabling them to function as reducing agents, singlet oxygen quenchers, hydrogen donors, and have the potential to chelate metal ions—make up the majority of the antioxidants isolated from higher plants. Through the use of the reagent Folin–Ciocalteu phenol, the total polyphenol content of *Fagonia indica* was determined to be 3.72 ± 0.05 mg gallic acid equivalent dry weight of plant per gram. ## 2.5. Antibacterial Activity Results of the antibacterial activity of *Fagonia indica* methanol extract are shown in (Table 5). The plant extract successfully suppressed the studied microorganisms, which represented Gram-negative bacteria (*Pseudomonas aeruginosa* MTCC741) and Gram-positive bacteria (*Bacillus subtilis* MTCC121), at different concentrations (1, 2, and 3 mg/disc); the last concentration (3 mg/disc) was significant compared to the reference drug (ampicillin 10 μg/disc) at p ≤ 0.05. At 3 mg/disc of the methanol extract of Fagonia indica, *Bacillus subtilis* recorded 15.00 ± 1.5 mm and *Pseudomonas aeruginosa* recorded 12.0 ± 1.0 mm inhibition zones. The Gram-positive bacteria exhibited the highest zone of inhibition. This may be explained by the fact that, in contrast to Gram-positive bacteria, the lipopolysaccharide layer and periplasmic zone around Gram-negative bacteria shield the cell membrane from the damaging effects of the plant extract [37]. The MIC and MBC values confirmed the findings of the disc diffusion test (Table 6). Bacillus subtilis was found to be the most susceptible bacterium (MIC = 125 μg/mL, MBC = 250 μg/mL), while *Pseudomonas aeruginosa* was found to be the least susceptible (MIC = 250 μg/mL, MBC = 500 μg/mL). To understand the mechanism of the antibacterial activity, the MBC/MIC ratio was calculated, and it was found to be 4 for *Bacillus subtilis* and 16 for Pseudomonas aeruginosa. *In* general, for any tested extract, if MBC/MIC is less than or equal to 4, it is considered bactericidal, and if it is higher than 4, it is considered bacteriostatic [38]. Our study is in agreement with some previous studies; worldwide, it was cited that *Fagoina indica* collected from the Cholistan desert in India showed substantial antibacterial activity against *Escherichia coli* [39]. Fagoina indica grown in the desert near Dubai, United Arab Emirates, exhibited good antimicrobial activity against a group of Gram-positive and Gram-negative bacteria, and also showed anti-Candida activity at a concentration of 200 mg/mL [40]. In fact, the first stage in creating new chemotherapeutic medications from plants, which are a substantial source of potentially beneficial compounds, is to assess the in vitro antimicrobial activity. Many researchers have examined plants’ antibacterial and antifungal properties [41,42]. Some of these discoveries have aided in identifying the underlying reason for specific behaviors, leading to the development of drugs that may be used to treat them and enhance people’s well-being. Plants with potential antibacterial effects should be evaluated against a suitable microbiological model to establish the activity and identify its associated features. The alcoholic and aqueous extracts of numerous plants and herbs effectively suppress food pathogens and spoilage bacteria with various potencies. Few reports exist regarding the effectiveness of the *Fagonia indica* plants’ antibacterial compounds against harmful pathogens. Only a few substances—many of which have antimicrobial effects—can be regarded as therapeutic, because mammalian cells are more sensitive to chemical inhibition than microbial cells. In the current study, we investigated the antibacterial activity of *Fagonia indica* methanolic extract against the pathogenic bacteria B. subtilis and P. aeruginiosa. It was revealed from earlier research that *Fagonia cretica* methanol extract showed high antibacterial activity [43,44]. The antibacterial activity of the *Fagonia indica* extract may be explained by the presence of several bioactive components, such as saponins, flavonoids and alkaloids, found in the methanolic extract as well as in the aqueous extract of *Fagonia indica* (Table 1 and Table 2). These results were in agreement with those of Anil et al. [ 27], who suggested that the diverse antibacterial activity of the plant extract is explained by the presence of several bioactive components, such as saponins, flavonoids and alkaloids. Previous research found that the alcoholic extract of many plants such as Piper stylosum, Epipremnum sp., Tetracera indica, Zingiber sp., Tectaria crenata, Goniothalamus sp., Homalomena propinque, Smilax sp., Elephantopus scaber, Mapania patiolale, Melastoma sp., Phullagathis rotundifolia, *Stemona tuberosa* and *Thotea grandifolia* could inhibit the growth of *Bacilus subtilis* [45]. The results of the anti-biofilm formation of *Fagonia indica* against B. subtilis and P. aeruginosa are shown in Table 7. This plant exhibited noticeable anti-biofilm formation activity. The extract of *Fagonia indica* had an MIC value of 125 mg/mL and an MBC value of 500 mg/mL, according to the preliminary antibacterial investigation. The inhibition of biofilm by these extracts ranged from 40.19 to $20.60\%$ for B. subtilis, and from 33.69 to $17.78\%$ for P. aeruginosa. Different levels of anti-biofilm activity against the examined bacteria were present in the plant species of this study. However, we contend that *Fagonia indica* is a strong contender, and more research is required to identify the antimicrobial substances for the control of multidrug-resistant pathogenic bacteria and their modes of action. Biofilms are multi-species bacterial communities with intricate structures that lead to antibiotic resistance and potentially fatal illnesses, resulting in significant financial loss; new methods are required. As a result of their therapeutic and antibacterial properties, medicinal herbs are being studied as potential replacements [46]. There are currently no “anti-biofilm drugs” that have been approved for use in people, even though microbial biofilms have been linked for two to three decades to antibiotic resistance and persistent microbial infections. To treat infectious disorders linked to biofilms, it is imperative to create new “anti-biofilm” drugs. Numerous studies indicate that blocking molecules involved in quorum sensing or biofilm-specific transcription may prevent the growth of biofilms. The idea of focusing on other important microbial biofilm components, notably the extracellular matrix components, has received very little attention [47,48]. Verma et al. [ 49] reported that two small molecule inhibitors (lovastatin and simvastatin), discovered by virtual screening and pharmaceutical repurposing, completely inhibited biofilm. These inhibitors target the significant proteinaceous portion of B. subtilis. Another result of these putative inhibitors was the breakdown of already-formed biofilms, which suggested that innovative anti-biofilm therapy strategies against biofilm-forming chronic microbial diseases could be developed using a similar method that uses FDA-approved medications to target ECM-associated proteins. P. aeruginosa is a widespread opportunistic infection that has been connected to severe morbidity and mortality in some groups. Environments containing soil, water and hosts, such as plants, animals and people, are ideal for it to flourish [50]. It is generally present in high amounts in everyday meals, particularly vegetables. Additionally, it is present in trace amounts in drinking water. Its adaptable energy metabolism would be the reason for its universality. P. aeruginosa develops biofilms to colonize various surfaces, just like other bacterial species that are common in the environment (including food packaging, water taps and medical devices). As a result of this, the cells resist both host defenses mediated by macrophages, neutrophils and antibacterial agents, including antibacterial cleansers, disinfectants and therapeutically relevant antibiotics. Several studies have successfully employed plant extracts to manage P. aeruginosa in the recent past. To the best of our knowledge, this is the first study on the antibacterial characteristics of *Fagonia indica* grown in mountains in the Hail region, Saudi Arabia. ## 3.1. Sample Collection Fagonia indica (Showeka) is grown in the Hail region, situated in the northern middle part of Saudi Arabia 25 290 N and 38 420 E. (Figure 4). It occupies 118,322 square kilometers, or $6\%$ of the total land of Saudi Arabia. Fogonia indica (Showeka) samples were taken from Aja Mountain (27° 259,040 N, 41° 259,330 E) during the period between March to May, 2021. ## 3.2. Chemicals All of the chemicals (methanol, ethanol, chloroform) used were of analytical grade. The chemicals and indicators were utilized as received, without any purification, and were obtained from Merck (Merck KgaA, Darmstadt, Germany). Folin–Ciocalteu’s phenol reagent, aluminium chloride hexahydrate, quercetin, H2SO4, standard vitamin E and DPPH (2,2-Diphenyl-1-picrylhydrazyl) reagents were from Sigma-Aldrich (St. Louis, MI, USA). ## 3.3. Preparation of Plant Extract Fresh samples of *Fagonia indica* areal parts (whole plant) were gathered and identified by the Department of Biology, College of Science, University of Hail, Saudi Arabia (Figure 5). The obtained *Fagonia indica* was dried in a shad for up to a week. Then, whole plant material was ground using a mechanical grinder (Electric Grinder, OMCG2145, Olsenmark, New York, NY, USA) to obtain a smaller particle size that was preferable for solvent extraction efficiency. In total, 100 g of the plant’s powder was macerated in 1000 mL of $80\%$ methanol for up to three days at room temperature (about 35–37 °C), with frequent shaking. The methanol was evaporated, and the extract was concentrated using a rotary vacuum evaporator (8 kw 50 L, Henan Lanphan Industry Co., Ltd, Zhengzhou, China). Furthermore, the unfiltered extracts were injected into the GC–MS after being dissolved in hexane and microfiltered. ## 3.4. Gas Chromatography–Mass Spectrometry (GC–MS) Analysis The GC–MS investigation used a Perkin Elmer Clarus 600 GC System equipped with an Rtx 5MS capillary column (30 m 0.25 mm i.d. 0.25 m film thickness; maximum temperature, 350 °C) and coupled to a Perkin Elmer Clarus 600C MS. As the carrier gas, a steady flow of 1.0 mL/min of ultra-high-purity helium ($99.9999\%$) was employed. The ion source, transfer line and injector temperatures were 280 °C, 270 °C and 270 °C, respectively. The gas had an ionization energy of 70 eV. The electron multiplier (EM) voltage was derived from auto tune. All data were collected using full-scan mass spectra between 40 and 550 amu [29,51]. ## 3.5. GC–MS Analysis Conditions The split ratio of the 1 L injected sample was 10:1. The oven’s temperature program was set to hold at 280 °C for 25 min, at a rate of 80 °C per minute from 60 °C. The entire performance lasted 53.5 min. Conditions for the GC–MS analysis of the leaf oil: the GC–MS apparatus, as previously noted, detected fatty acid methyl ester (FAME) molecules. The flow of helium gas was 0.7 mL/min. The temperatures of the ion source, transfer line and injector were 250 °C, 250 °C and 220 °C, respectively. Initially set at 50 °C (held for 8 min), the oven temperature was raised to 250 °C at a pace of 40 °C per minute. By gathering full-scan mass spectra throughout the scan range of 35–500 amu, all data were obtained. Through comparison of the collected spectra with mass spectral libraries, the unidentified chemicals were found [52]. The determination of the calibration and minimum detection limits for the system was based on the manufacturing conditions, and the corresponding equation is available elsewhere [53]. ## 3.6. Phytochemical Profile The extracts were tested for the determination of major phytochemical compounds using qualitative methods described elsewhere [54,55], as follows: Detection of saponins: The methanol plant extract (0.5 g), which was mixed in a test tube, was tested for the presence of saponins if persistent foaming was seen after warming. Detection of terpenes: To detect the presence of terpenes (terpenoids), a dried extract weighing 50 mg was soaked in 5 mL of ethanol and mixed with 2 mL of chloroform. The resulting mixture was slightly warmed and then cooled. To the cooled mixture, 3 mL of concentrated H2SO4 was gradually added along the sides of the test tubes. A brownish-red precipitate was formed at the interface, which confirmed the presence of terpenes. Detection of flavonoids: To determine the presence of flavonoids, a dried extract weighing 0.30 g was extracted with 30 mL of distilled water for 2 h, and filtered using Whatman filter paper number 42 (125 mm). Next, 10 mL of the aqueous filtrate of the extract was mixed with 5 mL of 1.0 M dilute ammonia solution, followed by the addition of 5 mL of concentrated tetraoxosulphate (VI) acid. The appearance of a yellow coloration that disappeared upon standing indicated the presence of flavonoids. Detection of phenols: To identify the presence of phenols, the ferric chloride test was conducted. Specifically, a 10 mL extract solution was mixed with a few drops of ferric chloride solution. The formation of a bluish-black coloration was an indication of the presence of phenols. Detection of tannins: To perform the tannin test, 1 mL of the extract was combined with water and subjected to heating on a water bath. After filtration, the resulting filtrate was subjected to the addition of ferric chloride. The development of a dark green hue was indicative of the existence of tannins. Detection of alkaloids: To identify the presence of alkaloids, two techniques are commonly used. The first is the Dragendorff’s test, which involves the addition of 2 mL of MeOH and 2 mL of $1\%$ HCl to 5 mg of the extracts along the side of the test tube, followed by the addition of 500 μL of Dragendorff’s reagent to the mixture. A positive test is indicated by the formation of an orange or orange reddish-brown precipitate. The second method is the Mayer’s test, in which a drop or two of Mayer’s reagent is added to 1 mg/mL of the extract. The presence of alkaloids is confirmed by the formation of a white or creamy precipitate. Detection of cardiac glycosides: To detect the presence of cardiac glycosides in a 2.5 mg extract, a solution comprising 1 mL of glacial acetic acid and a few droplets of $5\%$ ferric chloride was introduced. Subsequently, 0.5 mL of concentrated sulfuric acid was added along the side of the test tube. A positive result, indicative of the presence of cardiac glycosides, was determined by the formation of a green or blue hue. ## 3.7. Energy Dispersive X-ray Fluorescence Measurements The electrical conductivity (EC) of the plant sample was measured at 20 °C with the aid of a conductivity meter [56]. An EDXRF (energy dispersive X-ray fluorescence) from Thermo Fisher Scientific (Waltham, MA, USA) was used to determine the concentrations of elements of the plant sample. The instrument was equipped with a state-of-the-art silicon drift detector (SDD) that eliminates spectral interference while offering a rapid response. The active area of 30 mm2 allows for a wide hard angle for efficient X-ray capture. The high flux rhodium anode tube was designed to enable direct X-ray tube excitation or custom excitation via different filters, enhancing elemental sensitivity. The calibration and minimum detection limits were determined following the conditions under which it was manufactured, and the equation can be found elsewhere [57]. ## 3.8. Determination of Total Phenolic Content (TPC) According to the procedure of Kumar et al. [ 58], using the Folin–Ciocalteu reagent, the total phenolic content (TPC) of different extracts was measured. The samples were analyzed at a concentration of 1 mg/mL. The extract was diluted ten-fold with deionized water before being put in a test tube with 0.75 mL of Folin–Ciocalteu reagent and stirred. The mixture was allowed to stand at 25 °C for 5 min. Following the addition of 0.75 mL of a saturated sodium carbonate solution, the liquid was gently mixed. Using a UV-Vis spectrophotometer, the absorbance at 725 nm was measured after 90 min at 25 °C. Gallic acid was used to develop a calibration curve. Gallic acid equivalents (GAE) in mg/mg of vegetable extract (mg of gallic acid/mg dry weight) were used to quantify the total phenolic content. ## 3.9. Determination of Total Flavonoid Content (TFC) The extracts’ total flavonoids concentration (TFC) was determined with minor modifications [59]. A volume of 1.5 mL (1 mg/mL) of the extract was mixed with an equal amount of $2\%$ AlCl3–6H2O. After 10 min of incubation, the mixture was vigorously agitated, and the absorbance at 367 nm was measured. Using a quercetin calibration line, units of milligrams of quercetin per gram of dry weight (mg Q.E./mg) were used to quantify the total flavonoid content. There were three tests performed on every sample. ## 3.10. Determination of Total Tannin Content (TTC) The tannins were quantified with a colorimetric method using a modified vanillin test [60]. A volume of 1.5 mL of concentrated H2SO4 and 3 mL of a $4\%$ methanolic vanillin solution were added to 50 mL of the extract (1 mg/mL). After allowing the mixture to stand for 15 min, the absorbance at 500 nm was calculated using methanol or water as a reference. The TTC was expressed as mg catechin/g of dry weight, or mg C.E./mg. Each sample underwent three replicate analyses. ## 3.11. DPPH Radical Scavenging The DPPH radical scavenging method was utilized to evaluate the free radical scavenging activity of the extracts, with the standard as vitamin E [61]. The various extracts (stock solutions 20 mg/mL and 1 mg/mL) and the standard were pipetted into separate test tubes (stock solutions). In a volume of 0.5 mL, an equal volume of DPPH methanolic solution was added to each sample and the standard. Before being allowed to stand for 30 min at a temperature of 25 °C in the dark, the mixture was vigorously stirred. The absorbance of the resultant solution at 520 nm was measured with a spectrophotometer. Each measurement was made three times. In total, 0.5 mL of the DPPH solution and 0.5 mL of the methanol were combined as a control. Pure methanol was assumed to be the blank. To calculate the percentage (PI %) of free radical DPPH inhibition, the following equation was used: PI % = 100 × (A of Control − A of Sample)/A of Control [1] where A of Control and A of Sample are the absorbances of the control solution and of a test sample or standard, in order. ## 3.12. ABTS Radical Scavenging Activity Assay 2,2′-azino-bis (3-ethylbenzthiazoline-6-sulphonic acid), commonly known as the ABTS cation scavenging activity test, was used to conduct the antiradical assay [61]. The ABTS radical mono-cation was formed by reacting a 7 mM ABTS solution with 2.45 mM K2S2O8. The combination was allowed to stand at room temperature and in the dark for 15 h. For the organic extracts, the samples were dissolved in methanol, and for the aqueous extract, the samples were dissolved in distilled water. The tocopherol (vitamin E) standard and various extract concentrations were examined, with the benchmark serving as a yardstick. By mixing 800 mL of diluted ABTS+ with 200 mL of each standard and sample, the anti-oxidant activity was determined. The absorbance was measured spectrophotometrically at 734 nm after thirty minutes. Each measurement was performed thrice. The antioxidant capacity of the test samples and the standard was represented as a percentage (%) of inhibition. The proportion of ABTS+ scavenging was computed using the following equation: PI % = 100 × (A of Control − A of Sample)/A of Control [2] where A of Control and A of Sample are the absorbances of the control and of the test sample or a standard, respectively. ## 3.13. β-Carotene/Linoleic Acid Method The extracts’ capacity to stop -carotene from bleaching was evaluated using a method previously published by [62]. Linoleic acid produces a free radical when it is heated with the compound of β-carotene and linoleic acid. Two milliliters of the β-carotene solution (1.5 mg -carotene/2.5 mL chloroform) were added to twenty milliliters of linoleic acid and two hundred milliliters of Tween-20. The chloroform was evaporated at 40 °C in a vacuum with a revolving evaporator. The dried material was mixed with 50 mL of distilled water to make a β-carotene-linoleic acid emulsion. By adding 0.800 mL of the emulsion to 0.200 mL of extracts at varied concentrations (stock solution 20 mg/mL), we examined each extract’s capacity to bleach -carotene and observed the results. The absorbance at 470 nm was measured before and after the combinations were incubated for 120 min at 50 °C in a water bath. Each test was conducted three times. The antioxidant activity of extracts was calculated using the following formula: [3]PI % is calculated as: 1−A0−At/Ac0−Act×100 where A0 and Ac0 are the test sample’s, standard’s, or control’s absorbance values recorded at zero time, respectively, and At and Act are the corresponding absorbance values measured after incubation for 120 min, respectively. ## 3.14. Bacterial Strains As a test bacterium, samples of the crude extract of the *Fagonia indica* plant were tested for their ability to inhibit the growth of *Bacillus subtilis* (MTCC121) and *Pseudomonas aeruginosa* (MTCC741). Both strains of bacteria were received from the Microbial Type Culture Collection (MTCC), Chandigarh, India, and then cultivated on Muller–Hinton agar. A single colony of bacteria was transferred to fresh media and left to rise overnight at 37 °C to form bacterial cultures. Using the sterile saline solution, the culture’s turbidity was adjusted to match the 0.5 McFarland standard (106 CFU/mL). ## 3.15. Agar Disc-Diffusion Method The disc-diffusion test was used to evaluate Fagonia indica’s antibacterial activity. Bacillus subtilis MTCC121 and *Pseudomonas aeruginosa* MTCC741 suspensions of the studied microorganisms were made, adjusted to McFarland turbidity to obtain about 106 CFU/mL, and then swapped over to sterile plates containing 20 mL of Mueller–Hinton agar. Individual sterile filter discs, 5 mm in diameter (Whatman No. 1), were put into previously infected agar plates under aseptic conditions after being saturated with 1, 2 and 3 mg/disc of the methanolic extract. At room temperature, the plates were incubated for 24 h. Discs impregnated solely with $80\%$ methanol were used as a negative control. Ampicillin, at 10 μg/disc and as a positive control disc, served as the standard drug. The mean value was calculated from three individual repetitions [63]. ## 3.16. Determination of Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) The minimum inhibitory concentration (MIC) of *Fagonia indica* methanolic extract of was estimated using a microdilution method on 96-well microplates [64]. In a nutshell, decreasing concentrations of the extract (500 to 31.25 μg/mL) were produced in $5\%$ DMSO for each microplate row using the serial two-fold dilution method. Following that, the microplates were incubated with 20 μL of bacterial suspensions adjusted to 0.5 McFarland and 160 μL of Mueller–Hinton broth for 24 h at 37 °C. The bacterial growth was then tested by incubating 40 μL of 2, 3, 5-triphenyltetrazolium chloride (TTC) (at a concentration of 0.2 g/mL for 30 min at 37 °C. The TTC identifies the wells with bacterial growth by staining the bacterial cells with a red dye. Microplate wells with the least amount of extract and no discernible bacterial growth were taken as the MIC. The minimum bactericidal concentration (MBC) of the *Fagonia indica* methanol extract against the examined bacteria was carried out following the diffusion test described in the literature [65], with minor modifications. The Mueller–Hinton agar plates were loaded with 50 μL of each of the tubes from the MIC test that exhibited no apparent growth with B. subtilis and P. aeruginosa, and these plates were subsequently incubated for up to 24 h at 35–37 °C. The growth of bacteria on the plates was checked after the incubation time. The lowest concentration that did not allow even a single bacterial colony to grow on the Mueller–Hinton agar plate was defined as the MBC value. The MBC/MIC ratio was also calculated. ## 3.17. Anti-Biofilm Assays The biofilms of each bacterial strain were produced on 96-well microtiter plates with MHB, $1\%$ glucose and cells (108 cells/mL) for 24 h at 37 °C [66]. Planktonic cells were delicately removed after incubation, and the wells underwent three N-saline washes. Following that, 200 mL of crude extract (Sub-MIC) was added to the wells, which were then incubated for 24 h at 37 °C. At 0 and 24 h, the absorbance at 492 nm was measured. The positive control used was chloramphenicol. All of the assays were run in triplicate. With the aid of M.H.B. medium containing distinct bacterial strains, biofilm formation was inhibited. The amount of biofilm inhibition was calculated as follows:OD (control) − OD (test)/OD (control) × 100[4] ## 3.18. Statistical Analysis The data were analyzed using the SPSS application for Windows, version 20 (SPSS Inc., Chicago, IL, USA). Based on Duncan’s multiple-range test, a one-way ANOVA was used to determine the difference between the groups. The information was displayed as means and S.D., and statistics were judged to be significant at p ≥ 0.05. ## 4. Conclusions The findings of this study on the phenolic content, antioxidant properties and antibacterial capabilities of the methanolic extract of *Fagonia indica* validated the plant’s folkloric use as medicine by Bedouin in the Hail region, and established a framework for further research into its potential as a functional food. Future research on the connection between structure and bioactivity will require purifying and separating the extract’s numerous components. Based on conventional knowledge, responsible phytoconstituents and targeted compounds were isolated and identified. 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--- title: 'Spiroleiferthione A and Oleiferthione A: Two Unusual Isothiocyanate-Derived Thioketone Alkaloids from Moringa oleifera Lam. Seeds' authors: - Yueping Jiang - Rong Liu - Ling Huang - Qi Huang - Min Liu - Shao Liu - Jing Li journal: Pharmaceuticals year: 2023 pmcid: PMC10054748 doi: 10.3390/ph16030452 license: CC BY 4.0 --- # Spiroleiferthione A and Oleiferthione A: Two Unusual Isothiocyanate-Derived Thioketone Alkaloids from Moringa oleifera Lam. Seeds ## Abstract Spiroleiferthione A [1], with a 2-thiohydantoin a heterocyclic spiro skeleton, and oleiferthione A [2], an imidazole-2-thione derivative, were isolated from the aqueous extract of *Moringa oleifera* Lam. seeds. The unprecedented structures of 1 and 2 were elucidated by extensive spectroscopic data, X-ray diffraction, and gauge-independent atomic orbital (GIAO) NMR calculation, as well as electronic circular dichroism (ECD) calculation. The structures of 1 and 2 were determined to be (5R,7R,8S)-8-hydroxy-3-(4′-hydroxybenzyl)-7-methyl-2-thioxo-6-oxa-1, 3-diazaspiro [4.4] nonan-4-one, and 1-(4′-hydroxybenzyl)-4,5-dimethyl-1,3-dihydro-2H-imidazole-2-thione, respectively. Biosynthetic pathways for 1 and 2 have been proposed. Compounds 1 and 2 are considered to have originated from isothiocyanate and then undergone a series of oxidation and cyclization reactions to form 1 and 2. Compounds 1 and 2 demonstrated weak inhibition rates of NO production, 42.81 ± $1.56\%$ and 33.53 ± $2.34\%$, respectively, at a concentration of 50 μM. Additionally, Spiroleiferthione A demonstrated moderate inhibitory activity against high glucose-induced human renal mesangial cell proliferation in a dosage-dependent manner. A wider range of biological activities, and the diabetic nephropathy protective activity of Compound 1 in vivo and its mechanism of action, need further investigation after the sufficient enrichment of Compound 1 or total synthesis. ## 1. Introduction Thiohydantoins, imidazole-2-thione derivatives, and isosteric analogues of hydantoin exhibit numerous biological activities, such as anticancer, anti-inflammatory, immunoregulatory, and antimicrobial properties [1]. To date, no more than 50 naturally occurring thiohydantoin derivatives have been reported in the literature [2,3,4,5,6,7,8,9,10]. They have mainly been discovered in plants of the Brassicaceae (syn. Cruciferae) family, such as *Lepidium meyenii* Walp., *Armoracia rusticana* P.G. Gaertn, and *Pugionium cornutum* (L.) Gaertn [2,3,4,5,6,7,8,9,10]. Only two imidazole-2-thione derivatives derived from ergothioneine have been isolated from a plant extract, although all previously reported ergothioneine-derived natural products are from fungal and animal sources [11]. These derivatives possess biological activities such as antioxidant, hepatoprotective, and epithelial–mesenchymal transition inhibition [12,13,14]. Moringa oleifera Lam. ( Moringaceae), a perennial plant of the Moringaceae family, is widely distributed in Africa and South Asia and is consumed as a folk medicine for the treatment of diabetes, paralysis, helminthiasis, sores, and skin infections, or as food [15,16,17]. M. oleifera seeds are an important part of M. oleifera and are rich in bioactive compounds and functional ingredients, which makes them a rich source of nutrition with potent therapeutic properties. Pharmacological studies have shown that the extracts of M. oleifera seeds, or compounds that were isolated from M. oleifera seeds, have a variety of pharmacological activities, namely anti-inflammatory [15,16,18], antiproliferation [15,16,18], hepatoprotective [16,18,19], antiatherosclerotic [16,18,20], antinociceptive [16,18], antidiabetic [18,19,20], antiperoxidative [15,16,18,20], neurodegenerative [18], and cardioprotective properties [15,16,18,20]. Moreover, various chemical constituents have been isolated from the extracts of M. oleifera seeds, such as glucosinolates [15,18], flavonoids [15,16,18], carbamates [18], steroids [15,16,18], fatty acids [16,18], phenolics [15,16,18], and polysaccharides [16]. However, the investigation of bioactive compounds and their bioactivities is still inadequate. In order to enrich the structural diversity and in-depth development of M. oleifera seeds, it is necessary to continuously determine the active ingredients in M. oleifera seeds, especially the sulfur-containing compounds. In our previous studies, the extracts and pyrrole-2-carbaldehydes from the seeds of M. oleifera showed strong diabetic-nephropathy-protective and potential neuroprotective activities [21,22]. In order to enrich the scope of active compounds for further pharmacological research, the chemical composition of M. oleifera seeds was further investigated, with the identification and isolation of two novel thioketone compounds: Spiroleiferthione A [1] and Oleiferthione A [2] (Figure 1). Spiroleiferthione A is a rare 2-thiohydantoin with an unprecedented heterocyclic spiro skeleton. Oleiferthione A is a novel, naturally occurring imidazole-2-thione derivative. Notably, Spiroleiferthione A demonstrated moderate inhibitory activity against high glucose-induced human renal mesangial cell (HRMC) proliferation in a dosage-dependent manner. Herein, details of the isolation, structural elucidation, proposed biosynthesis, and bioactivity of the two compounds are described. ## 2.1. Structural Elucidation Spiroleiferthione A [1] was obtained as a yellowish, amorphous powder with [α]D25+187 (ⅽ 0.03, MeOH). Its molecular formula, C14H16N2SO4, established by HRESIMS as m/z 309.0908 [M + H]+, combined with NMR spectral data (Table 1), indicates eight degrees of unsaturation. Its IR spectrum shows absorption bands for hydroxy (3415 cm−1) and aromatic (1645 and 1563 cm−1) functionalities. The 1H NMR spectrum of 1 has peaks indicating an aromatic ring AA′BB′ system [δH 7.04 (2H, d, $J = 8.4$ Hz, H-2′, 6′) and δH 6.62 (2H, d, $J = 8.4$ Hz, H-3′, 5′)], one nitrogen-bearing methylene [δH 4.72 (1H, d, $J = 15.0$ Hz, H-7′a) and 4.61(1H, d, $J = 15.0$ Hz, H-1′b)], one saturated methylene [δH 2.41 (1H, dd, $J = 6.0$, 13.2 Hz, H-9a) and 1.95 (1H, dd, $J = 7.2$, 13.2 Hz, H-9b)], two nonequivalent methines [δH 3.85 (1H, dq, $J = 6.0$, 6.0 Hz, H-7) and 3.83 (1H, ddd, $J = 7.2$, 6.0, 6.0 Hz, H-8)], and one methyl [δH 1.09 (3H, d, $J = 6.0$ Hz, H3-10)]. The 13C NMR and DEPT spectra display signals corresponding to the above proton-bearing units include two additional quaternary carbonyls assigned as carboxylic (δC 172.9, C-4), and thiourea carbonyl (δC 182.6, C-2) groups [3,8,9], and three quaternary carbon resonances that were assigned as two aromatic carbons, including an oxygen-bearing carbon (δC 126.9 and 157.3, respectively) and one nitrogen/oxygen-bearing carbon (δC 90.7) (Table 1). These spectroscopic data, and those of the reported thiohydantoin derivatives (Lee et al., 2019; Peng et al., 2021; Yu et al., 2017) indicate that 1 is a thiohydantoin derivative, as confirmed by 2D NMR data analysis (Figure 2). The HSQC and 1H–1H COSY spectra of 1 provide the unambiguous assignment of proton and carbon signals in the NMR spectra. In the HMBC spectrum of 1, correlations from H-2′/6′ to C-1′, C-4′, and C-3′/5′; from H-3′/5′ to C-1′, C-4′, and C-2′/6′; and from H2-7′ to C-2, C-4, C-2′/6′, and C-1′ in combination with the chemical shift of H2-7′, demonstrate that C-7′ of the 1,4-disubstituted benzyl group is connected to the N-3 atom of the thiohydantoin ring (ring A, Figure 1). Additionally, the thiohydantoin ring (Ring A) is connected to Ring B via C-5, supported by the HMBC correlations of H2-9/C-4, C-5, C-7, C-8; H-8/ C-5, C-7, C-9, C-10; H-7/C-5, C-8, C-9, C-10; and H3-10/C-7, C-8, in combination with the chemical shift of C-5 (90.7). Hence, the planar structure of 1 was determined to be 8-hydroxy-3-(4′-hydroxybenzyl)-7-methyl-2-thioxo-6-oxa-1, 3-diazaspiro [4.4] nonan-4-one. The relative configurations of C-7 and C-8 in 1 were determined by the ROESY correlation observed between H-8 and H3-10, which suggested that H-8 and CH3-10 were on the same side. However, determining the stereochemistry of C-5 was a challenge due to the unprecedented carbon skeleton and the absence of NOEs. To solve this, the 13C NMR chemical shifts for the two possible isomers, namely, 1a [(5R,7R,8S)1] and 1b [(5S,7R,8S) −1], were calculated at the ωB97x-D/6-31G*/B3LYP-D3(BJ)/TZVP level [23]. Isomer 1a yielded a better linear correlation coefficient (R2) value (0.9993 vs. 0.9986) (Figure S1), a lower mean absolute error (MAE, 1.01 vs. 1.57), and a lower root mean square (RMS, 1.29 vs. 1.82) than those of Isomer 1b, suggesting the 5R,7R,8S relative configuration of 1 (Figure 3). Further supporting this conclusion, the experimental and calculated chemical shifts were statistically analyzed using the sorted training set (STS) protocol [23], indicating a striking predominance ($99.99\%$ probability) of the (5R,7R,8S) −1 isomer (Figure 3). ECD calculations were carried out to define the absolute configuration of 1. As shown in Figure 4, the calculated ECD curve matched well with the experimental data, enabling a confident assignment of the absolute configuration of (5R,7R,8S) −1. Oleiferthione A [2], a yellowish, amorphous powder, has the molecular formula C12H14N2OS with seven degrees of unsaturation, as indicated by HRESIMS m/z 235.0906 [M + H]+ (calcd for C12H15N2OS, 235.0905). In the 1H NMR spectrum, typical resonance values were observed for two singlet methyls [δH 2.04 (3H, s) and 1.93 (3H, s)], a 1,4-disubstituted benzene ring with four aromatic protons [δH 7.09 (2H, d, $J = 8.5$ Hz) and 6.71 (2H, d, $J = 8.5$ Hz)], and one nitrogen-bearing methylene [δH 5.19 (2H, s)] (Table 2). A p-hydroxyphenyl group [δC 128.8 (C-1′), 129.6 (C-2′, 6′), 116.3 (C-3′, 5′), and 158.1 (C-4′)], two methyls [δC 8.8 (C-6) and 9.1 (C-7)], one nitrogen-bearing aliphatic methylene (δC 48.3, C-7′), one nitrogen-bearing olefin [δC 123.6 (C-4) and 121.5 (C-5)], and one thiourea carbonyl, or one sulfhydryl substituted olefinic carbon (δC 159.3, C-2), were identified from the 13C NMR, DEPT, and HSQC data (Table 1 and Table 2, Figure S5). These data account for the seven degrees of unsaturation, a pentacyclic ring system satisfying one of these. From the 2D NMR data, the 1H–1H COSY correlations of H-2′/H-3′ and H-5′/H-6′ indicated the 1,4-disubstituted benzene ring (Figure 1). The key HMBC correlations from CH3-6 to C-4 and C-5; from CH3-7 to C-4 and C-5; from H2-7′ to C-2, C-4, C-1′, C-2 ′, and C-6′; from H-2′/H-6′ to C-3′/C-5′, C-4′, and C-1′; and from H-3′/H-5′ to C-2′/C-6′, C-1′, and C-4′, in combination with the chemical shift of C-7′, demonstrate that C-7′, in the 1,4-disubstituted benzyl group, is connected to the N-3 atom of the 4,5-dimethyl-1H-2-thioimidazole or 4,5-dimethyl-1H-imidazole-2-thiol ring. Fortunately, after many attempts, a small crystal of 2 was generated in methanol through the solvent evaporation method. Single-crystal X-ray crystallography using Mo–Kα radiation confirmed the 4,5-dimethyl-1H-2-thioimidazole ring in 2 (CCDC: 2168388, Figure 5). Accordingly, the structure of 2, oleiferthione A, was elucidated as 1-(4′-hydroxybenzyl)-4, 5-dimethyl-1, and 3-dihydro-2H-imidazole-2-thione. ## 2.2. Proposed Biosynthetic Pathway of 1 and 2 Biosynthetic pathways for 1 and 2 are proposed in Scheme 1. The typical isothiocyanate derived from phenylalanine was considered to be the starting unit [24]. The initial head-to-tail cyclization of isothiocyanate (A) with methyl alanine would produce B with the removal of a methoxy moiety [25]. The oxidation of B would yield key intermediate C. SAM-dependent methyltransferase would catalyze the conversion of C into E, which would dehydrate to afford 2. The oxidation of key intermediate C would give D. Finally, the cyclization of D with methyl lactate would produce 1 in a transformation similar to that producing B. ## 2.3. Biological Activity Evaluation of 1 and 2 In bioassay experiments, Compounds 1 and 2 were evaluated for their antimicrobial activity and their inhibitory activities against lipopolysaccharide (LPS)-activated nitric oxide (NO) production in RAW 264.7 cells and high glucose-induced human renal mesangial cell (HRMC) proliferation. Compounds 1 and 2 displayed no antimicrobial activity against four bacteria, including Escherichia coli, *Staphylococcus aureus* subsp. Aureus, *Salmonella enterica* subsp. Enterica, and *Pseudomonas aeruginosa* at a concentration of 100 μM. In the antimicrobial assay, the positive control group (Ceftazidime) displayed inhibition rates of 99.853 ± $0.129\%$ and 100.04 ± $0.069\%$ against E. coli and P. aeruginosa, respectively. Penicillin G sodium salt displayed inhibition rates of 100.232 ± $0.201\%$ and 99.942 ± $0.084\%$ against S. aureus and S. enterica, respectively. Compounds 1 and 2 showed a weak inhibition of NO production with 42.81 ± $1.56\%$ and 33.53 ± $2.34\%$, respectively, at a concentration of 50 μM. The positive control (L-NG-monomethylarginine) demonstrated an inhibition of NO production with 59.31 ± $2.19\%$. However, as shown in Figure 6, Compound 1 showed the moderate inhibition of high glucose-induced HRMC proliferation in a dosage-dependent manner. This result suggests that Compound 1 can potentially exert protective effects against the progression of diabetic nephropathy. ## 3. Discussion To date, no more than 50 naturally occurring thiohydantoin derivatives have been reported in the literature [2,3,4,5,6,7,8,9,10]. Spiroleiferthione A is a rare 2-thiohydantoin with an unprecedented heterocyclic spiro skeleton that differs from these reported thiohydantoin derivatives. Thus far, only two imidazole-2-thione derivatives derived from ergothioneine have been isolated from a plant extract, although all previously reported ergothioneine-derived natural products are from fungal and animal sources [11]. Oleiferthione A is a novel naturally occurring imidazole-2-thione derivative, which is the third identified plant origin of imidazole-2-thione derivatives. Spiroleiferthione A showed moderate inhibitory activity against high glucose-induced human renal mesangial cell proliferation in a dosage-dependent manner. However, on account of the limitations, the diabetic-nephropathy-protective activity of Compound 1 in vivo and its mechanism of action were not further investigated. Although it has been reported that natural imidazole-2-thione derivatives possess biological activities, such as antioxidant, hepatoprotective, and epithelial–mesenchymal transition inhibition properties [12,13,14], and natural 2-thiohydantoin derivatives showed anti-neuroinflammatory [3,4,8], antibacterial [9], anticancer [8,26], hypolipidemic [2], anticarcinogenic [2], antimutagenic [2], and antithyroidal [2] activities, a wider range of biological effects was not further evaluated due to the limitations of the two compounds. Although various bioactivities of 2-thiohydantoin derivatives have been reported, the antidiabetic nephropathy activity was investigated in this study for the first time. In order to comprehensively investigate its bioactivities and mechanisms of action, the total synthesis of 2-thiohydantoin derivatives may be an effective approach to produce sufficient yields. ## 4.1. General Experimental Procedures Optical rotations were measured using an INESA SGW-3 automatic polarimeter (Shanghai INESA Physico Optiacal Instrument, Shanghai, China). UV data were recorded using a Cary 300 spectrometer (Agilent Technologies, Santa Clara, CA, USA). CD data were measured using a JASCO J-815 CD spectrometer (JASCO, Tokyo, Japan). IR data were recorded using a Nicolet IS50 FT-IR spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). NMR spectra were obtained at 500 MHz or 600 MHz for 1H, and 125 MHz or 150 MHz for 13C on Bruker 500 MHz or 600 MHz spectrometers (Bruker, Billerica, MA, USA) in CD3OD or DMSO-d6, respectively, with the tetramethyl silane (TMS) peak used as a reference. HR-ESIMS data were measured using an Agilent Q-TOF 6545 spectrometer (Agilent Technologies). Column chromatography (CC) was performed using silica gel (200−300 mesh, Qingdao Marine Chemical, Qingdao, China), MCI gel (CHP20P) (Mitsubishi Chemical, Tokyo, Japan), and macroporous adsorbent resin (HPD-300) (Ainuo chemical technology Co., LTD, Zhengzhou, China). HPLC separation was performed using a system consisting of an Agilent 1260, an Agilent 1260 pump, and an Agilent 1260 wavelength absorbance detector with an Agilent (250 × 9.4 mm) semipreparative column packed with C18 (5 μm) (Agilent Technologies). TLC separations were carried out on precoated silica gel GF254 plates (Qingdao Marine Chemical). Spots were visualized under UV light (254 or 356 nm), or by spraying with $10\%$ H2SO4 in $90\%$ EtOH followed by heating. ## 4.2. Plant Material M. oleifera (Moringaceae) seeds were collected in September 2019 from Kunming city, Yunnan Province, China (Latitude: 24° 88′ N; Longitude:102° 88′ E). The seeds were dried at 50 °C in an oven. Plant identity was verified by Professor Shao Liu (Xiangya Hospital, Central South University, Changsha 410008, China). A voucher specimen (no. 2019001) was deposited at the Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, China. ## 4.3. Extraction and Isolation Dry ground M. oleifera seeds (10 kg) were extracted with water using ultrasonic apparatus (solvent ratio: 1:8 (g seeds: mL H2O), 3 × 1 h). The aqueous extracts were evaporated under reduced pressure and lyophilized to yield a dark brown residue (2.65 kg). The residue was dissolved in H2O (20 L), loaded on a macroporous adsorbent resin (HPD-300) column (10 × 80 cm), and successively eluted with H2O (80 L), EtOH-H2O (1:1) (80 L) and EtOH-H2O (9:1) (50 L) to yield three corresponding fractions: A, B, and C. After removing the solvent under reduced pressure, Fraction A (1.5 kg) was separated by CC over MCI gel CHP 20P (5 L), with successive elution using H2O (20 L), EtOH-H2O (1:1) (20 L), and EtOH-H2O (9:1) (20 L) to yield fractions A1−A3. Fraction A2 (104 g) was subjected to CC over RP silica gel (1 L), with successive elution using EtOH-H2O (3:7) (5L), EtOH-H2O (1:1) (5 L), and MeOH (5 L) to give fractions A2-1−A2-3. Fraction A2-2 (12 g) was subjected to CC over silica gel, with elution by a gradient of increasing MeOH concentration (0−$100\%$) in CH2Cl2 to yield fractions A2-2-1−A2-2-12 based on TLC analysis. A2-2-7 (~100 mg) was purified by RP HPLC (C18 column, 2.0 mL/min), using $23\%$ MeCN in H2O containing 1 ‰ formic acid (v/v) as the mobile phase to yield 1 (1.5 mg, tR = 36.5 min). A2-2-6 (~150 mg) was purified by RP HPLC (C18 column, 2.0 mL/min), using $20\%$ MeCN in H2O containing 1‰ formic acid (v/v) as the mobile phase for the former to yield 2 (2.0 mg, tR = 27.5 min). ## 4.4. Physicochemical Properties of Compounds 1 and 2 Spiroleiferthione A [1]: yellowish, amorphous powder; UV (MeOH) λmax 280 nm; IR (KBr) νmax 3415, 2930, 2856, 1645, 1563, 1439, 1384, 1259, 1152, 1101, 800, 649, 600, 466 cm−1; 1H NMR (CD3OD, 500 MHz and DMSO-d6, 600MHz) data, see Table 1; 13C NMR (CD3OD, 125 MHz and DMSO-d6, 150MHz) data, see Table 1; (+)-HRESIMS m/z 309.0905 [M + H]+ (calcd for C14H16N2O4S, 309.0904). Oleiferthione A [2]: yellowish, amorphous powder; UV (MeOH) λmax 270 nm; IR (KBr) νmax 3448, 2925, 2850, 1633, 1514, 1456, 1399, 1242, 1168, 1114, 787, 665, 544 cm−1; 1H NMR (CD3OD, 500 MHz) data, see Table 1; 13C NMR (CD3OD, 125MHz) data, see Table 1; (+)-HRESIMS m/z 235.0901 [M + H]+ (calcd for C12H14N2OS, 235.0900). Crystallographic and structure refinement for Compound 2: C12H14N2OS, $M = 235.02$, $a = 12.2627$[6] Å, $b = 6.2696$[3] Å, $c = 16.1773$[7] Å, α = 90°, β = 106.647°[3], γ = 90°, $V = 1191.62$[10] Å3, $T = 296.15$ K, Space Group Pn, $Z = 4$, μ(MoKα) = 0.253/mm−1, 6212 reflections collected, 3840 independent reflections (Rint = 0.0282). The final R1 value was 0.0535 (I > 2σ(I). The final wR (F2) values were 0.1217 (I > 2σ(I). The final R1 value was 0.0993 (all data). The final wR (F2) value was 0.1502 (all data). The goodness of fit value on F2 was 1.018. ## 4.5. Antimicrobial Assay The microorganisms used in antibacterial assays were obtained from the China General Microbiological Culture Collection Center (CGMCC) (*Escherichia coli* ATCC25922, *Staphylococcus aureus* subsp. Aureus ATCC29213, *Salmonella enterica* subsp. enterica ATCC14028, and *Pseudomonas aeruginosa* ATCC27853. Lysogeny broth (LB, Huankai Microbial, Guangzhou, China) culture media were used for culturing bacteria, while Mueller–Hinton broth (MHB, Huankai Microbial, Guangzhou, China) was used to determine the minimum inhibitory concentration. The inocula of bacteria was prepared from 24 h-old agar cultures and incubated to logarithmic phase. Ceftazidime (Yuanye biotechnology Co., LTD, Shanghai, China) was used as a positive reference substance. We measured the minimum inhibitory concentration (MIC) of Compounds 1 and 2 using the broth microdilution method in 96-well microtiter plates, as described in the literature [27]. The MIC was defined as the lowest concentration without any colony growth after incubating the fungus at 28 °C for 16 h. All tests were performed in triplicates. ## 4.6. Anti-Inflammatory Assay Murine RAW 264.7 cells were purchased from the Shanghai cell bank of the Chinese Academy of Sciences (Shanghai, China). These cells were incubated in RPMI1640 medium plus $10\%$ FBS, 100 U/mL penicillin, and 100 μg/mL streptomycin sulfate in a humidified incubator with $5\%$ CO2. The cells were treated with LPS (1 µL/mL) and the test compounds for 48 h. L-NMMA was used as a positive control. Accumulated nitrite in the culture supernatants, an indicator of NO synthase activity, was measured by the Griess reaction [28]. Cell viability was examined by MTS assay (Beyotime Inst. Biotech. Shanghai, China) according to the manufacturer’s instructions. The absorbance was examined at 570 nm using a Spectra Max microplate reader (Molecular Devices, LLC, Sunnyvale, CA, USA). All tests were performed in triplicates. The results were expressed as a percentage of the response of the related LPS-treated groups that were designated as $100\%$. ## 4.7. Inhibitory Assay of High Glucose-Induced HRMC Proliferation HRMCs were cultured in DMEM (Sigma, St. Louis, MO, USA) and supplemented with $10\%$ fetal bovine serum (FBS, Gibco, CA, USA) and $1\%$ double antibiotic (penicillin–streptomycin, Beyotime Biotechnology Co., Ltd., Shanghai, China) at 37 °C in a humidified environment containing $5\%$ CO2. Next, 20 μL of L-DMEM was added to the blank and control wells, and 10 μL each of L-DMEM and 250 mM glucose (0.26 g of D-(+)-glucose dissolved in 8 mL of phosphate-buffered saline (PBS) and filtered using a 0.22 μm membrane) was added to the other wells to a final glucose concentration of 30 mM, which were then incubated for 24 h [22]. Different concentrations of Compounds 1 and 2 (10, 20, and 50 μM) were added to the designated wells, and the Cell Counting Kit-8 (CCK8, Dojindo, Kyushu Island, Japan) assay was used to detect optical density after 24 h of incubation. We used L-DMEM containing only HRMCs and no intervention drugs as a control group. ## 4.8. Statistical Analysis One-way ANOVAs and LSD t-tests were used to analyze the groups of samples using SPSS 19.0. The data are expressed as the mean ± SD (standard deviation). All the data shown are representative of at least three independent experiments. $p \leq 0.05$ was considered to be statistically significant. ## 4.9. Computational Section Crest software was used to search the conformers of (5R,7R,8S)-1 and (5S, 7R, 8S)-1 on the GFNFF level of theory [29,30], following the optimization of GFN2-XTB level with a 4 kcal/mol energy window to remove high-energy conformers [31]. Optimization and frequency calculations of each conformer were performed on B3LYP-D3(BJ)/TZVP (IEFPCM, CH3OH) level of theory. DFT GIAO 13C NMR calculations were performed on the ωB97xD/6-31G * (IEFPCM, CH3OH) level, and data processing followed the reported STS protocol [23]. The calculated shielding tensors of conformers were Boltzmann averages based on the Gibbs free energy. Theoretical ECD was calculated by time-dependent density functional theory (TDDFT) at the mPW1PW$\frac{91}{6}$-311g(d) level with the IEF–PCM solvent model (MeOH). SpecDis v1.71 was used to simulate the ECD for (5R,7R,8S)-1 curve with Gaussian band shape at 0.28 eV. The calculated ECD curve of each conformer was Boltzmann-averaged based on its Gibbs free energy. All the DFT calculations were performed using the Gaussian 16 software package. ## 5. Conclusions Two isothiocyanate-derived thioketone alkaloids, Spiroleiferthione A and Oleiferthione A, were isolated from the aqueous extract of M. oleifera seeds. The novel structures of 1 and 2 were elucidated by extensive spectroscopic data, gauge-independent atomic orbital (GIAO) NMR calculation, ECD, and X-ray diffraction. Spiroleiferthione A is a rare 2-thiohydantoin with an unprecedented heterocyclic spiro skeleton. Oleiferthione A is a novel, naturally occurring imidazole-2-thione derivative. Spiroleiferthione A demonstrated moderate inhibitory activity against high glucose-induced human renal mesangial cell proliferation in a dosage-dependent manner. This study has enriched the structural diversity of M. oleifera seeds, especially the isothiocyanate-derived, sulfur-containing compounds. It provides clues for the subsequent study of thioketone derivatives and their activities. ## Figures, Scheme and Tables **Figure 1:** *Structures of Compounds 1 and 2.* **Figure 2:** *Key 2D NMR correlations of 1 and 2.* **Figure 3:** *The 13C NMR chemical shift calculation results of a pair of C-5 epimers of (5R, 7R, 8S) −1 (1a) and (5S, 7R, 8S) −1 (1b).* **Figure 4:** *Experimental and calculated ECD spectra of 1.* **Figure 5:** *ORTEP diagram of Compound 2.* **Scheme 1:** *Proposed biosynthetic pathways for 1 and 2.* **Figure 6:** *Effects of Compound 1 on the proliferation of glucose-induced HRMCs (* $p \leq 0.05$, vs. the 30 mM glucose group; *** $p \leq 0.001$, vs. the 30 mM glucose group; ## $p \leq 0.01$, vs. the control group).* TABLE_PLACEHOLDER:Table 1 TABLE_PLACEHOLDER:Table 2 ## References 1. Cho S., Kim S., Shin D.. **Recent applications of hydantoin and thiohydantoin in medicinal chemistry**. *Eur. J. Med. Chem.* (2019) **164** 517-545. 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--- title: Correlation between Morphological Characteristics of Macular Edema and Visual Acuity in Young Patients with Idiopathic Intermediate Uveitis authors: - Ludovico Iannetti - Fabio Scarinci - Ludovico Alisi - Marta Armentano - Lorenzo Sampalmieri - Maurizio La Cava - Magda Gharbiya journal: Medicina year: 2023 pmcid: PMC10054752 doi: 10.3390/medicina59030529 license: CC BY 4.0 --- # Correlation between Morphological Characteristics of Macular Edema and Visual Acuity in Young Patients with Idiopathic Intermediate Uveitis ## Abstract Background and Objectives: *Macular edema* (ME) is a common complication of intermediate uveitis (IU). It is often responsible for a decrease in visual acuity (VA). Three distinct patterns of macular edema have been described in intermediate uveitis, namely, cystoid macular edema (CME), diffuse macular edema (DME), and serous retinal detachment (SRD). The current study aims to describe the characteristics of macular edema in young patients with idiopathic intermediate uveitis and to correlate its features with VA using spectral domain optical coherence tomography (SD-OCT). Materials and Methods: A total of 27 eyes from 18 patients with idiopathic IU complicated by ME were included in this retrospective study. All patients underwent SD-OCT; data were gathered at the onset of ME. Best-corrected VA (BCVA) was correlated with the morphological features of ME. Results: BCVA was negatively correlated with Ellipsoid Zone (EZ) disruption ($$p \leq 0.00021$$), cystoid pattern ($$p \leq 0.00021$$), central subfield thickness (CST) ($p \leq 0.001$), and serous retinal detachment (0.037). Conclusions: In ME secondary to idiopathic IU, VA negatively correlates with Ellipsoid Zone disruption and increases in CST. Moreover, vision is influenced by the presence of cysts in the inner nuclear and outer nuclear layers and by the neuroepithelium detachment. ## 1. Introduction Intermediate uveitis (IU) represents the widest of four major categories of uveitis proposed by the International Uveitis Study Group (IUSG). IU predominantly affects patients under the age of 40 and affects approximately $10\%$ of the general uveitis population. It accounts for 8–$18\%$ of uveitis cases and up to $38\%$ of uveitis in the pediatric population [1,2]. Usually, the disease presents as bilateral in 70–$90\%$ of cases. No difference in gender prevalence has been observed [3]. Although the disease does not present itself as hereditary, a certain common HLA recurrence in some families, such as HLA-A*28 HLA-DRB1*15, HLA-B*51, and B*08, has been observed [4]. Moreover, Tang et al. observed that patients with HLA-DR15-related IU showed a tendency to develop the concomitant systemic findings of other related disorders, such as multiple sclerosis, optic neuritis, and narcolepsy [5]. In addition, a concomitant genetic predisposition may act in concert with an exogenous infection to determine the development of the disease. For instance, it has been suggested that HLA class II protein may act as a cofactor during the infection of B lymphocytes by the Epstein–Barr virus. The Epstein–*Barr virus* has been linked to the development of multiple sclerosis. Some authors suggest that there may be a common genetic predisposition in patients affected by multiple sclerosis and the Epstein–*Barr virus* [6]. From an etiopathogenetic point of view, several hypotheses have been made in the previous years. Gartner suggested that the remnants of the hyaloid may act as an immunogenic stimulus in pars planitis, while others suggested breakdown of the blood–retinal barrier as the first inflammatory trigger [6]. The precise etiology of IU is not known, although it is oftentimes associated with systemic conditions such as sarcoidosis, multiple sclerosis, and several infectious diseases. IU is a chronic intraocular inflammatory disorder in which the vitreous represents the major site of inflammation [7]. Usually, the patient reports floaters and a minimally decreased vision. Clinical signs are represented by a minimal involvement of the anterior chamber; posterior synechiae, if present, usually involves the inferior iris. Vitreitis is a cardinal feature of the IU and is associated with snowballs and snowbanks. Snowballs represent inflammatory aggregates that can be found in the inferior peripheral vitreous. Snowbanks are inferior exudates of the pars plana and are usually associated with a more aggressive form of the disease [3]. IU is frequently related with peripheral retinal phlebitis with a percentage ranging between 16 and $36\%$. The persistence of the phlebitis may determine the formation of cyclitic membranes and neovasis. In a small percentage of cases, a retinal detachment can develop after an acute IU, both exudative and tractional [3,8]. Macular edema (ME) is characterized by a retinal thickening in the macular zone due to blood–retinal barrier (BRB) breakdown. Extracellular fluid accumulates in the intraretinal area or in the subretinal space. Inflammatory ME may be secondary to anterior, intermediate, posterior, or diffuse uveitis and is the main condition associated with vision loss in uveitis. The main cause of macular thickening in inflammatory conditions is inflammatory ME. Moreover, other causes can determine macular thickening in ocular inflammatory conditions, such as vitreo-macular traction from inflammatory epiretinal membrane; inflammatory choroidal vascularization; an association with papillary edema; or central serous chorioretinopathy due to the chronic use of steroid therapy. Inflammatory ME is due to the breakdown of the blood–retinal barrier, which is mainly formed of tight junctions between the endothelial cells of non-fenestrated capillaries and the retinal pigment epithelial cells [9,10,11]. Several molecular factors are involved in the inner BRB breakdown, such as VEGF; pro-inflammatory cytokines such as TNF-α, IL-1, TGF-β, and angiotensin II; as well as adenosine, histamine, and glucose [12]. In IU, increased levels of IL-6 and IL-8 in the aqueous humor were detected [13]. IU is characterized by a consistent prevalence of ME. In 21–$52\%$ of cases, ME is clinically significant, representing the most common cause of decreased visual acuity (VA) [14]. Longstanding ME can lead to retinal degeneration with permanent visual loss over time [15,16]. Optical coherence tomography (OCT) represents the gold standard technique for the diagnosis of ME, since it is non-invasive, reproducible, and sensitive. It quantifies the retinal macular thickness using mapping and may show fluid accumulation either at the inner or outer plexiform layer, a non-uniform photoreceptor outer/inner segment line, the presence of hyperreflective dots in the subretinal fluid, epimacular membranes, and vitreomacular traction. OCT is an imaging technique that allows the obtainment of images of the retinal layers with high detail [17]. The first available OCT technology was Time Domain OCT (TD-OCT). Subsequently, Spectral Domain OCT (SD-OCT) took its place and represents the most common model in use today [18]. Its high sensitivity makes SD-OCT suitable for detecting and monitoring uveitic ME, as it is able to discern forms of ME that may be otherwise undetectable by less-advanced methods [19]. Moreover, OCT delivers fundamental elements to study fluid deployment and organization, as well as revealing the morphology of the vitreo–retinal interface [16,18].The currently available SD-OCT instruments ensure an excellent display of the external limiting membrane (ELM); the photoreceptor inner segment—internationally referred to as the Ellipsoid Zone (EZ) and traditionally ascribed to the junction of the inner/outer segment (OS) of the photoreceptors; the interdigitation of the photoreceptor OS and the retina pigment epithelium (RPE), or OS/RPE junction; and the RPE–choriocapillaris complex. The OS/RPE junction line is also known as the cone outer segment tip (COST) line and it consists in a fine layer interposed between the EZ and the RPE [20,21]. Three different patterns of fluid distribution in uveitic ME have been identified: cystoid macular edema (CME), diffuse macular edema (DME), and serous retinal detachment (SRD) [22,23]. VA decreases with increasing fluorescein leakage and central thickness. A correlation has been established between the central thickness measured by OCT and VA. This correlation showed significant differences depending on the OCT pattern and was strongly dependent on the presence of CME. A negative correlation between central foveal thickness and VA has also been described by other authors [22,24,25]. DME was found to be associated with poor visual recovery after treatment, mainly because of the persistence of this edema presentation even after treatment [24]. On the other hand, several studies point to a negative visual outcome in patients with uveitic CME [15]. In a previous study, our group demonstrated in a mixed group of uveitic patients that visual acuity was negatively affected by CME and disruption of the photoreceptors [16]. Lardenoye et al. demonstrated that the cystoid pattern was associated with worse VA, advanced age, and chronic inflammation. The development of blindness in IU was caused, in most cases. by CME [11]. The purpose of the present study is to describe the OCT characteristics of ME at its first presentation in young patients affected by idiopathic IU and to correlate them with VA to better understand the impact of ME on the final functional outcome. ## 2. Materials and Methods A retrospective study was carried out on patients younger than 25 years old affected by idiopathic IU complicated by ME at its first diagnosis from January 2020 to September 2022. The diagnostic suspect was first based on clinical evaluation. Exclusion criteria were patients affected by IU aged ≥ 25; IU associated with sarcoidosis, multiple sclerosis and infectious diseases, and other causes of hypovisus (e.g., amblyopia, optic nerve atrophy, retinal pathologies with macular involvement); media opacity and drug-induced ME. We considered several factors including age, sex, specific diagnosis, duration of the uveitis, and clinical characteristics. The evaluation of inflammation gravity and disease activity was conducted in accordance with the guidelines provided by the Standardization for Uveitis Nomenclature (SUN) Working Group [17]. Best-corrected visual acuity (BCVA) was assessed at first ME presentation with 5 m Snellen charts. OCT scans (linear, radial, and volumetric) were performed to determine the retinal thickness and ME characteristics with an SD-OCT Spectralis OCT system (Heidelberg Engineering, Heidelberg, Germany). OCT images of insufficient quality determined the exclusion of the patient from the study. A correlation between BCVA and the following OCT parameters of ME was performed: pattern of ME (cystoid or diffuse) (Figure 1a,b), presence or absence of SRD (Figure 1c,d), presence or absence of foveal bulge (Figure 2a), presence or absence of subfoveal bubbles (Figure 2b), integrity or disruption of COST line (Figure 2c), integrity or disruption of Ellipsoid Zone (Figure 2d), integrity or disruption of ELM, central subfield thickness (CST). We decided to include only the patients aged < 25 and ME at its first diagnosis to investigate as homogeneous a sample of young patients as possible and to avoid the potential effect of longstanding or chronic ME on its OCT morphological features and on BCVA. All patients received corticosteroid therapy administrated both topically and systemically to reduce inflammatory manifestations. In all patients, ME resolved after steroid treatment (systemic or peribulbar administration). This study followed the tenets of the Declaration of Helsinki. Informed consent was obtained from all subjects after an explanation of the nature and possible consequences of the study. In the case of minors, informed consent was obtained from the parents or legal tutors. ## Statistical Analysis The graphical analysis of population distribution for BCVA resulted in a non-normal distribution; therefore, we reported the median value. Metric variables are reported as mean (±SD). For the multivariate analysis of BCVA, cumulative link modeling (CLM in the ordinal package) was used in the “R for statistical computing” environment, version 2.15.2. [ 26,27] Graphical evaluation identified the data outliers, which were eliminated or used to establish collinearity. For the final BCVA, a logic link function with a flexible threshold was used. The full model was then evaluated by applying a stepwise procedure in both directions, automatically and manually, to select significative covariates. We reported regression coefficients and cumulative odds ratio. P-value was calculated with a wale test, and we considered significant values for $p \leq 0.005.$ ## 3. Results A total of 27 eyes from 18 patients (27 eyes) with ME associated with IU (8 males and 10 females), with a median age of 18 years (range: 13–23 years) and a mean follow-up of 46 months (range 15–37), were enrolled in the study. The median decimal BCVA was 0.8 (range: 0.55–0.95). The grade for vitreous cells and haze was 0.5+ in 5 eyes, 1+ in 13 eyes, 2+ in 9 eyes. The OCT’s morphological features in relation to the corresponding median BCVA are reported in Table 1. The SRD was observed in 13 eyes (48,$1\%$) and always associated with the two main patterns (seven with CME and six with DME). Other morphological features observed were subfoveal bubbles in 12 eyes ($44.4\%$), EZ disruption in 3 eyes ($11.1\%$), COST line disruption in 6 eyes ($22.2\%$), and ERMs in 17 eyes ($62.0\%$). Average central subfield thickness was 459 µm (±153 µm) and central perifoveal thickness was 443 µm (±153 µm). BCVA was negatively correlated with Ellipsoid Zone disruption (regression coefficient −5.6, $$p \leq 0.00021$$), cystoid pattern (regression coefficient −4.4, $$p \leq 0.00021$$), CST (regression coefficient −2.2, $p \leq 0.001$) and SRD (regression coefficient −1.9, $$p \leq 0.037$$). The significant correlations between VA and morphological characteristics are summarized in Table 2. ## 4. Discussion In patients affected by ME secondary to idiopathic IU, the assistance of SD-OCT images can be a valuable help to the clinician in the characterization of edema features. In accordance with the literature, in this study, we recognized three principal patterns of edema: CME and DME, associated or not with SRD. Previously published studies identified comparable characteristics in patients suffering from intraocular inflammation and in diabetic macular edema [23,28,29,30]. Among our patients, the most common presentation was CME ($66.6\%$) whereas DME was observed in $33.3\%$ of cases. Interestingly, both CME and DME were found to be crucial for the development of SRD. In fact, these two distributions of ME showed a similar correlation with the risk of SRD formation, in accordance with the available literature [19,22,23,30]. In the present study, the main features affecting vision during inflammatory ME in idiopathic IU are EZ disruption, cystoid pattern, CST, and SRD. On the other hand, DME, the presence or absence of a foveal bulge, subfoveal bubbles, and COST line disruption do not affect VA. These results agree with those observed in our previous study performed on ME secondary to all types of uveitis [16]. The EZ can be recognized as a hyper-reflective line below the external limiting membrane and its integrity correlates with VA preservation during the course of ME [31]. Maheshwary et al. highlighted the role of the EZ in the maintenance of a good BCVA in patients with diabetic ME. They described a reduction in VA, measured in ETDRS letters, depending on the amount of Ellipsoid Zone loss. They hypothesized that the assessment of the EZ using SD-OCT images could be a predictive factor for VA in patients with diabetic ME [20]. Oster et al. observed the same correlation in ME caused by macular pucker. These findings underline the important connection between EZ integrity and visual performance [32]. In our study, among all the features analyzed with the multivariate regression analysis, EZ disruption appears to be the most influential factor negatively affecting VA. We did not find any significant correlation between COST line status and BCVA, although recent studies showed a negative correlation between COST line disruption and visual recovery in epi-retinal membranes (ERM), and between macular hole surgery and diabetic macular edema [33,34,35,36]. On the other hand, in a previous study, we found a negative correlation between the interdigitation zone disruption and VA in patients with uveitic macular edema [37]. Roesel et al. studied the characteristics of the junction between the inner and outer segments of the photoreceptors with the aid of fundus autofluorescence (FAF) and OCT in patients with ME. They correlated the anatomical data concerning the alteration and disruption of this retinal layer with the functional data evaluated with BCVA. They concluded that an increased central FAF, the presence of cystoid changes, a disrupted EZ, and ERMs were associated with poor vision [38]. Akduman et al. evaluated the modification of macular thickness in correlation with clinical inflammatory parameters such as cells and flare. They noticed an interdependence between macular thickness and VA, and between macular thickness and inflammatory indexes. Moreover, they highlighted that macular thickness measured with OCT could be a good predictive factor for VA in uveitic patients. They also suggested that objective OCT morphological characteristics may be more strictly correlated with VA than subjective characteristics such as flare or cells [39]. The Multicenter Uveitis Steroid Treatment (MUST) Trial investigated the BCVA of 479 intermediate, posterior, and panuveitic eyes at baseline and after a 2-year follow-up. A longer duration of uveitis, AC flare, the presence of cataract, pseudophakia at baseline, the persistence of vitreous haze, and macular thickening were associated with BCVA worsening [40]. Niederer et al. reported that early CME in IU can often be treated with a good improvement in VA in more than two-thirds of cases, while its sequelae as macular atrophy and scarring are significantly associated with moderate and severe vision loss [41]. These findings are in accordance with the MUST Trial and Follow-up Study, in which participants’ eyes with incident, persistent, or relapsed uveitic ME had consistently worse BCVA than eyes with resolved ME over seven years [42]. The influence of SRD on VA is still controversial. Separation of the neurosensory retina from the RPE leads to the deprivation of nutrition and oxygen supplies to the outer retina, which causes photoreceptor apoptosis and visual loss [43,44]. Successful reattachment of the neurosensory retina is crucial for vision recovery. Disruption of the EZ has also been observed in patients with retinal detachment using OCT and a better visual recovery is usually closely correlated with an intact EZ at the fovea after retinal reattachment. Retinal reattachment permits the restoration of the blood supply to the outer retina and the regeneration of the photoreceptors and the patients’ visual acuity is recovered subsequently [45,46]. SRD is also commonly observed in other macular disorders such as central serous chorioretinopathy and diabetic macular edema [47]. In a previous paper, we reported that VA is negatively correlated with SRD [16]. However, some authors report an ambiguous role for SRD in the deterioration of VA. More specifically, they report that SRD does not worsen the visual outcome in uveitic patients with ME [22,24]. Lehpamer et al. evaluated the influence of subretinal fluid on VA, based on OCT images during the course of inflammatory ME. They reported that the progressive augmentation of macular thickness due to subretinal fluid corresponded to a decline in VA at presentation. Moreover, the authors investigated the response of SRD and ME to uveitis treatment at 3 and 6 months and obtained an improvement in BCVA relative to the reduction in fluid accumulation. The resolution of ME was more consistent in eyes without SRD, although both eyes with and without SRD achieved similar levels of VA [48]. Weldy et al. also reported that uveitic eyes with subretinal fluid at presentation show worse initial VA when compared to eyes without SRF. However, they obtained a similar VA and CST in the follow-up after treatment [49]. Tran et al. described that DME had a worse visual prognosis compared to SRD with or without associated CME in uveitic patients [50]. Given the median decimal BCVA of 0.8, our study shows a limitation by not including uveitic eyes with macular edema and worse VA. Since patients with this condition can show a worse BCVA than 0.8 [11], our results might not represent the overall spectrum of the disease and might not be generalizable to more severely affected eyes. Unlike other studies on similar subjects that reported larger samples but included different types of uveitis and a larger age spectrum, we focused our attention only on young patients affected by idiopathic intermediate uveitis [23,30,32]. The limit of the present study is the small sample of the study but this is mainly due to the choice of inclusion criteria—age (<25), type of uveitis (idiopathic intermediate), and ME (at its first diagnosis)—which were very strict to make the study sample as homogeneous as possible. ## 5. Conclusions In conclusion, this study promotes the role of SD-OCT to gain information about retinal morphology and to correlate the images obtained with the visual data in patients suffering from idiopathic IU. We described two main patterns of fluid accumulation, cystoid and diffuse, which could determine the elevation of the neuroretina. Characteristics such as Ellipsoid Zone disruption, cystoid pattern, SRD, and central retinal thickening appear to be strongly associated with poor vision. Among these, the most influential features appear to be EZ disruption and cystoid form. 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--- title: CD8+ Regulatory T Cell Deficiency in Elderly-Onset Rheumatoid Arthritis authors: - Ryu Watanabe - Keiichiro Kadoba - Atsuko Tamamoto - Koichi Murata - Kosaku Murakami - Hideo Onizawa - Takayuki Fujii - Akira Onishi - Masao Tanaka - Hiromu Ito - Akio Morinobu - Motomu Hashimoto journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10054757 doi: 10.3390/jcm12062342 license: CC BY 4.0 --- # CD8+ Regulatory T Cell Deficiency in Elderly-Onset Rheumatoid Arthritis ## Abstract Elderly-onset rheumatoid arthritis (EORA) is associated with higher disease activity and accelerated joint destruction compared with young-onset RA (YORA). However, the underlying immunological mechanism remains unclear. Regulatory T cells (Tregs) are an immunosuppressive T cell subset, and CD4+ Tregs are deficient and/or dysfunctional in RA; however, CD8+ Tregs have not been fully examined in RA. Here, we aimed to determine the role of CD8+ Tregs, particularly in EORA. A total of 40 patients (EORA, $$n = 17$$; YORA, $$n = 23$$) were cross-sectionally enrolled. Current disease activity and treatment were comparable between the two groups; however, levels of multiple cytokines, including IL-1β, TNFα, interferon (IFN)-γ, IL-2, and IL-10, were significantly increased in EORA. The number of CD4+ Tregs did not differ between the groups ($$p \leq 0.37$$), but those of CD8+ Tregs were significantly decreased in EORA ($$p \leq 0.0033$$). The number of CD8+ Tregs were inversely correlated with plasma matrix metalloprotease (MMP)-3 levels (r = −0.3331, $$p \leq 0.036$$). Our study results revealed an intrinsic deficiency of CD8+ Tregs in patients with EORA, which leaves synovitis unchecked with excessive MMP-3 release. A therapeutic approach to restore CD8+ Tregs may provide a new avenue for the treatment of EORA. ## 1. Introduction Rheumatoid arthritis (RA) is a chronic inflammatory disease that causes progressive joint destruction if not appropriately treated [1]. However, recent advances in treatment, particularly the advent of biological disease-modifying antirheumatic drugs (bDMARDs) and targeted synthetic DMARDs (tsDMARDs), have made it a feasible therapeutic goal to control joint destruction [2]. RA is prevalent among women aged in their 40s to 50s. However, with the aging of the population, the number of patients who develop RA after the age of 60 years has been increasing [3]. Compared with young-onset RA (YORA), elderly-onset RA (EORA) has a higher proportion of males, and many are seronegative for rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibody (ACPA), which causes difficulties in differentiating EORA from polymyalgia rheumatica (PMR) [4,5]. Acute phase reactants, such as C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), are often elevated due to increased IL-6 signaling, which is associated with higher disease activity and more rapid joint destruction in EORA than in YORA [6,7]. However, the immunological mechanism underlying the difference between EORA and YORA remains largely unclear. Regulatory T cells (Tregs) are a subset of CD4+ T cells that actively engage in immunological tolerance and prevent autoimmunity [8]. These cells are characterized by the expression of CD25 and the master transcription factor, Foxp3 [9]. Multiple studies have demonstrated that CD4+ Tregs are deficient and/or dysfunctional in autoimmune diseases, including RA [10,11,12], systemic lupus erythematosus (SLE) [13,14,15], giant cell arteritis (GCA) [16,17,18], PMR [19], and others. Although CD4+ Tregs are well recognized, CD8+ Tregs are still controversial in many aspects, including their phenotypes and suppressive mechanisms [20]. However, accumulating evidence indicates that CD8+ Tregs also possess immunosuppressive functions, as found in animal models of inflammatory bowel disease, graft-versus-host disease, and viral infections [21,22,23]. In addition, although the number of CD8+ Tregs are not reduced in the elderly and patients with GCA, they are dysfunctional compared with those in younger individuals [24]; however, the role of CD8+ Tregs in EORA remains unknown. Here, we aimed to determine whether plasma protein levels and the number of CD8+ and CD4+ Tregs differ between patients with EORA and YORA. We then assessed correlations between the number of CD8+ Tregs and plasma protein levels and examined the role of CD8+ Tregs in the pathophysiology of EORA. ## 2.1. Study Design and Selection of Patients All patients who fulfilled the 1987 or 2010 classification criteria for RA [25,26] at Kyoto University Hospital were registered in the KURAMA cohort database, as previously described [27,28]. Patients with a diagnosis of RA were eligible for enrollment regardless of treatment and no exclusion criteria were set. Clinical data were recorded at baseline and at every visit. Patients who visited Kyoto University Hospital between April 2020 and March 2021 and had been treated with a treat-to-target strategy [29] were cross-sectionally enrolled. We defined YORA and EORA as RA with age at onset <60 and ≥60 years, respectively [6,7]. ## 2.2. Clinical Evaluation The medical records of the enrolled patients were retrospectively reviewed, as well as clinical data, including age, sex, disease duration, medication, erythrocyte sedimentation rate (ESR), serum C-reactive protein (CRP) values, swollen joint counts, tender joint counts, and titers of RF and ACPA. Rheumatoid factor and ACPA were considered positive if titers were >15 IU/mL and >4.5 U/mL, respectively. Disease activity of RA was monitored using the Disease Activity Score (DAS)28-ESR, DAS28-CRP, simplified disease activity index (SDAI), and clinical disease activity index (CDAI). ## 2.3. Measurement of Plasma Protein Levels Plasma protein levels of IL-1β, IL-6, TNFα, interferon-γ (IFN-γ), IL-17, IL-2, IL-10, and matrix metalloproteinase (MMP)-3 were evaluated using the Luminex® Discovery Assay Human Premixed Multi-Analyte Kit (Cat No. LXSAHM-20; R&D Systems Inc., Minneapolis, MN, USA) according to the protocol provided by the manufacturer. ## 2.4. Flow Cytometry Peripheral blood mononuclear cells (PBMCs) were isolated from peripheral blood by density gradient centrifugation using BD Vacutainer® CPT (Catalog No. 362753, BD Biosciences, San Jose, CA, USA). Flow cytometric analysis was performed using a BD LSRFortessa (BD Biosciences), and data were analyzed using FlowJo software (Tree Star, Ashland, OR, USA). Methods for measuring surface and intracellular proteins have previously been described [30]. APC-conjugated anti-human CD4 antibody (Clone A161A1, Catalog No. 357408), PerCP-conjugated anti-human CD8 antibody (Clone SK1, Catalog No. 344708), and FITC-conjugated anti-human Foxp3 antibody (Clone 206D, Catalog No. 320106) were obtained from BioLegend (San Diego, CA, USA). We used eBioscienceTM Foxp3/Transcription Factor Staining Buffer Set (Catalog No. 00-5523-00, ThermoFisher Scientific Inc., Waltham, MA, USA) to stain Foxp3. We defined CD4+Foxp3+ cells as CD4+ Tregs, and CD8+Foxp3+ cells as CD8+ Tregs. ## 2.5. Statistical Analysis All statistical analyses were performed using Prism 9 (GraphPad Software Inc., La Jolla, CA, USA). The normality of all data was evaluated using Kolmogorov–Smirnov tests. Statistical significance was determined using unpaired two-tailed Student t-tests for normally distributed data, and Mann–Whitney U tests for data that were not normally distributed. Correlations were determined using Pearson or Spearman analyses based on the data distribution. Categorical variables were analysed using Fisher’s exact test. The Benjamini–Hochberg step-down procedure was applied to adjust for multiple tests and to control the false-discovery rate at 0.05 [31]. Values with $p \leq 0.05$ were considered significant. ## 2.6. Ethics Approval and Consent to Participate The study protocol was approved by the Kyoto University Ethics Committee (R0357). All participants provided written informed consent to all study procedures, which complied with the principles of the Declaration of Helsinki. ## 3.1. Clinical Characteristics of Enrolled Patients Table 1 summarizes the clinical characteristics of the 40 patients (EORA, $$n = 17$$; YORA, $$n = 23$$) included in this study. In line with previous studies [4,5], our patients with EORA were significantly older ($p \leq 0.001$), included fewer females ($$p \leq 0.023$$), and had lower positivity for RF ($$p \leq 0.003$$) and ACPA ($p \leq 0.001$) compared with patients with YORA. Current disease activity and treatment including methotrexate, prednisolone, and biologics were balanced (Table 1). None of the patients were administered with Janus kinase (JAK) inhibitors. ## 3.2. Inflammatory Milieu Persisted despite Treatment in EORA We measured the levels of plasma protein in the patients (Figure 1). Despite similar disease activity, levels of IL-1β ($$p \leq 0.028$$, Figure 1a), TNFα ($$p \leq 0.019$$, Figure 1c), MMP-3 ($$p \leq 0.00052$$, Figure 1d), IFN-γ ($$p \leq 0.028$$, Figure 1e), IL-2 ($$p \leq 0.0022$$, Figure 1g), and IL-10 ($$p \leq 0.0059$$, Figure 1h) were significantly increased in patients with EORA compared with YORA. Even after the multiple tests using the Benjamini–Hochberg procedure, the differences remained statistically significant. In contrast, IL-6 ($$p \leq 0.42$$, Figure 1b) and IL-17 ($$p \leq 0.053$$, Figure 1f) levels did not differ between the groups. These results indicated that the pathophysiology of EORA and YORA may fundamentally differ and that current therapies can suppress IL-6 and disease activity but cannot sufficiently diminish the inflammatory milieu. ## 3.3. CD8+ Tregs Are Deficient in EORA We then measured the number of CD4+ and CD8+ Tregs, as well as the proportion of the cells (CD4+ Tregs and CD8+ Tregs to CD4+ and CD8+ T cells, respectively) using flow cytometry (Figure 2 and Figure 3). The gating strategy is shown in Figure 2. The proportion of CD4+ Tregs mostly ranged from $1\%$–$5\%$ (Figure 3b), whereas that of CD8+ Tregs ranged from $0\%$–$2\%$ (Figure 3c). When we compared these cells between patients with EORA and YORA (Figure 3a), the proportions and the number of CD4+ Tregs did not differ between the groups (Figure 3b,d), whereas those of CD8+ Tregs were significantly decreased in EORA (Figure 3c,e, $$p \leq 0.019$$, $$p \leq 0.0033$$, respectively). These differences remained statistically significant after multiple tests. Although a previous study demonstrated that CD8+ Tregs were comparable between young (<30 years) and elderly (>60 years) individuals [24], our results showed that CD8+ Tregs, but not CD4+ Tregs, are decreased in EORA. ## 3.4. Number of CD8+ Tregs Are Associated with Plasma MMP-3 Levels Multiple cytokines were increased, whereas CD8+ Tregs were decreased in EORA. We then examined correlations between the abundance of CD8+ Tregs, age, RA disease activity, and plasma protein levels to determine whether the decrease in CD8+ *Tregs is* associated with the disease state of EORA (Table 2). Age (r = −0.2847, $$p \leq 0.075$$) and RA disease activity (DAS28-ESR, DAS28-CRP, SDAI, and CDAI, $$p \leq 0.61$$, $$p \leq 0.87$$, $$p \leq 0.93$$, and $$p \leq 0.89$$, respectively) were not associated with the abundance of CD8+ Tregs. Sex and seropositivity were also not associated with the number of CD8+ Tregs ($$p \leq 0.11$$, $$p \leq 0.23$$, respectively). Among plasma proteins, levels of MMP-3 were inversely correlated with the abundance of CD8+ Tregs (r = −0.3331, $$p \leq 0.036$$, Figure 4a), but not CD4+ Tregs (r = −0.07073, $$p \leq 0.66$$, Figure 4b). These results suggest that CD8+ Tregs may play a protective role in suppressing synovitis, particularly in elderly persons. ## 4. Discussion We showed that an array of inflammatory cytokines persisted in EORA despite treatment. We also found that CD8+ Tregs, but not CD4+ Tregs, were deficient in patients with EORA, and that the number of CD8+ Tregs was inversely correlated with plasma MMP-3 levels. These results suggest that patients with EORA may have an intrinsic deficiency of CD8+ Tregs, which leaves synovitis unchecked, leading to excess release of MMP-3. Thus, restoring CD8+ Tregs may offer a new avenue for treating EORA. In our study, levels of CRP, ESR, and IL-6 did not differ between patients with EORA and YORA, whereas those of IL-1β, TNFα, IFN-γ, and IL-2 were increased in EORA (Figure 1). Since synovial fibroblasts are the major producers of IL-6 [32], these results suggest that IL-6 production in synovial fibroblasts could be susceptible to treatment. In contrast, monocytes/macrophages and T cells, which are the producers of IL-1β, TNFα, and IFN-γ, may be persistently activated despite treatment in EORA. IL-2 is primarily produced by activated CD4+ T cells and functions as a major growth factor for CD4+ Tregs [33], but they were not increased in EORA. IL-10 can be secreted by not only CD4+ and CD8+ Tregs [33,34], but also Th1, Th2, B, and dendritic cells [35,36], which explains why IL-10 accumulated in EORA. These results suggest that the treatment that EORA patients were receiving failed to fundamentally correct the pathology of EORA. In our recent work, we showed that IFN-γ is associated with the treatment resistance to anti-TNF inhibitor therapy [37]. In this multi-omics analysis involving 27 bDMARD-naïve RA patients, we found that, compared to responders, IFN-γ is accumulated during anti-TNF therapy in non-responders, which attracts additional T cells into the synovial tissue via CXC motif chemokine ligand 10, forming a vicious cycle of resistance to anti-TNF inhibitors [37]. Since IFN-γ utilizes the JAK-signal transducer and activator of transcription (STAT) pathway for intracellular signaling, our findings thus provide a rationale for the use of JAK inhibitors against EORA, although prior risk stratification is required [38]. Although the number of CD8+ Tregs do not decrease, their suppressive function is not maintained with age [24]. However, the potential to induce CD8+ Tregs from PBMCs using IL-15 and low-dose anti-CD3 is impaired in elderly compared with younger individuals [39]. We found that age did not correlate with the number of CD8+ Tregs, although the abundance was distinctly lower in patients with EORA than YORA (Figure 3). The decrease in CD8+ Tregs has been reported in other autoimmune diseases, such as SLE [40] and type 1 diabetes mellitus [41]. Our study results are consistent with these studies. The suppressive activity of CD8+ *Tregs is* not mediated by IL-10 but relies on interference with the T cell receptor (TCR)-induced signaling cascade [39]. Specifically, CD8+ Tregs release exosomes containing NADPH oxidase 2 (NOX2) that interfere with the TCR-induced phosphorylation of ZAP-70 and suppress activation in neighboring CD4+ T cells [42]. Defective CD8+ Treg functions in elderly individuals and patients with GCA are attributed to the inadequate release of exosomes containing NOX2 [24]. We did not analyze the functions of CD8+ Tregs because they comprise a distinctly low proportion of T cells, particularly in EORA. Further studies are needed to determine the functional activity of CD8+ Tregs in patients with EORA. Recently, low-dose IL-2 therapy has been expected to be effective against autoimmune diseases such as SLE because it can expand CD4+ Tregs [33,43]. The anti-IL-6 inhibitor tocilizumab can also restore the number and functions of CD4+ Tregs [17,44,45]; however, these effects on CD8+ Tregs are unknown [46]. Several attempts to expand CD8+ Tregs using probiotics or by in vitro or in vivo procedures are under investigation to treat autoimmunity [20,47]. In the present study, anti-IL-6 inhibitors, including tocilizumab and sarilumab, were used in six patients with YORA ($26.1\%$) and only one with EORA ($5.9\%$) ($$p \leq 0.21$$). The use of anti-IL-6 inhibitors did not affect the number of both CD4+ and CD8+ Tregs in this study ($$p \leq 0.68$$ and $$p \leq 0.78$$, respectively, Supplementary Figure S1). In addition, abatacept, a selective inhibitor for T cell activation, was administered in three cases of both YORA and EORA ($$p \leq 1.0$$). The use of abatacept also did not have an impact on the number of both CD4+ and CD8+ Tregs ($$p \leq 0.81$$ and $$p \leq 0.29$$, respectively, Supplementary Figure S1). Therefore, the use of these biological agents may not explain CD8+ Tregs’ deficiency in EORA in this study. The number of CD8+ Tregs was inversely correlated with plasma MMP-3 levels (Figure 4), but not RA disease activity and other cytokines (Table 2). The direct evidence showing that the deficiency of CD8+ Tregs causes excessive release of MMP-3 is scarce even in the literature, thus it remains unclear why MMP-3 is specifically associated with the number of CD8+ Tregs. Whether this is just a coincidence or not requires further investigation in the future. The present study had several limitations. First, we included only 40 patients, and their clinical characteristics of EORA and YORA significantly differed (Table 1). The differences in age, sex, and seropositivity between EORA and YORA may have affected the number of CD8+ Tregs. However, the patient profiles were relatively typical of YORA or EORA and disease activity was comparable between the groups. Second, this study did not compare the results with those of healthy controls. Patients with EORA should be compared with age-matched, healthy, elderly individuals. Third, because of the cross-sectional study design, many patients had already been treated, which may have modified the results. The number of CD8+ Tregs should have been examined before and after treatment. Fourth, the definition of CD8+ Treg was not rigorous. Since the definition of the cell differs among reports [20,48], we defined CD8+Foxp3+ cells as CD8+ Tregs. Finally, as described above, the present study did not perform the functional assay of CD8+ Tregs. ## 5. Conclusions We revealed that the number of CD8+ Tregs decreased and was inversely correlated with plasma MMP-3 levels in EORA. Further studies are required to utilize these cells for EORA treatment. ## References 1. Smolen J.S., Aletaha D., McInnes I.B.. **Rheumatoid arthritis**. *Lancet* (2016) **388** 2023-2038. DOI: 10.1016/S0140-6736(16)30173-8 2. 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--- title: Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio as Predictive Factors for Mortality and Length of Hospital Stay after Cardiac Surgery authors: - Georgios Tzikos - Ioannis Alexiou - Sokratis Tsagkaropoulos - Alexandra-Eleftheria Menni - Georgios Chatziantoniou - Soultana Doutsini - Theodosios Papavramidis - Vasilios Grosomanidis - George Stavrou - Katerina Kotzampassi journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10054765 doi: 10.3390/jpm13030473 license: CC BY 4.0 --- # Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio as Predictive Factors for Mortality and Length of Hospital Stay after Cardiac Surgery ## Abstract Background: Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are widely accepted indices positively correlated with disease severity, progression, and mortality. In this study, we tested whether NLR and PLR could predict mortality and length of hospital stay (LOS) after cardiac surgery. Methods: NLR and PLR were calculated on days 0, 3, 5, and 7 postoperatively. A ROC curve was generated to assess their prognostic value; multivariate logistic analysis identified independent risk factors for 90-day mortality. Results: Analysis was performed on 179 patients’ data, 11 of whom ($6.15\%$) died within 90 days. The discriminatory performance for predicting 90-day mortality was better for NLR7 (AUC = 0.925, $95\%$ CI:0.865–0.984) with the optimal cut-off point being 7.10. NLR5 and PLR3 also exhibited a significant strong discriminative performance. Similarly, a significant discriminative performance was prominent for PLR3, NLR5, and NLR7 with respect to LOS. Moreover, NLR7 (OR: 2.143, $95\%$ CI: 1.076–4.267, $$p \leq 0.030$$) and ICU LOS (OR:1.361, $95\%$ CI: 1.045–1.774, $$p \leq 0.022$$) were significant independent risk factors for 90-day mortality. Conclusions: NLR and PLR are efficient predictive factors for 90-day mortality and LOS in cardiac surgery patients. Owing to the simplicity of determining NLR and PLR, their postoperative monitoring may offer a reliable predictor of patients’ outcomes in terms of LOS and mortality. ## 1. Introduction Complete blood count (CBC) is one of the most common examinations performed in the everyday clinical setting to provide information about red blood cells, white blood cells and their subtypes, and platelets. Furthermore, the indices derived from them such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-platelet ratio (NLP) have been found to be well correlated with disease severity, progression, and mortality [1], reflecting the immune system’s sufficiency and its ability to respond to inflammation. The cellular-mediated inflammatory response includes neutrophils, lymphocytes, monocytes, and platelets; the indices derived from them seem to be reliable biomarkers of the immunological status of the patient and, thus, predictive factors for the disease progression [2], as have been proven both in ICU trauma patients and in a variety of malignancies [3,4,5,6,7,8,9,10,11,12]. Patients undergoing anesthesia for cardiac surgery experience a systemic inflammatory response more aggravated than in other surgeries due to the additional stress of extracorporeal circulation [13,14]. A variety of hematological indices has been referred to in the literature as having different predictive powers in different clinical situations; perioperative NLR and PLR, used separately or as a pair, have been tested for the prognostication of postoperative morbidity and mortality, as well as for severe postoperative complications in cardiac surgery patients with sometimes good and sometimes ambiguous results. These indices, to some extent, reflect the extent of the inflammatory response occurring after the stress of an operation [15,16]. This study aims to assess the potential predictive value of postoperative NLR and PLR in patients undergoing cardiac surgery regarding 90-day postoperative mortality and length of hospital stay. ## 2.1. Study Design and Population This is a post hoc analysis of data collected prospectively for the primary study assessing the prognostic validity of nutritional status, body composition, phase angle, and muscle strength regarding morbidity and mortality in a cardiac surgery population from September 2018 to August 2019 [17]. All the patients scheduled for elective coronary artery bypass grafting or isolated valve replacement or repair, by means of minimally invasive extracorporeal circulation, were eligible for the primary study. The exclusion criteria were: 1. age < 18 years old, 2. clinical instability necessitating emergency surgery, 3. congenital heart abnormality, 4. aortic dissection, 5. recent (≤3 months) open heart surgery, and 6. the existence of an implantable electronic cardiovascular device. The patients were admitted one day before the surgical intervention and completed the mandatory preoperative assay. Written informed consent was obtained from all subjects; the study protocol was approved by the authors’ institutional review board and prospectively registered with ClinicalTrials.gov (NCT03644030). This work has been reported in line with the STROCSS criteria [18]. ## 2.2. Data Collection Mortality was defined as death occurring from any cause during the first 90 days after cardiac surgery. After the sample size had been recruited, general data, such as sex, age, demographics information, weight, height, behavioral history (smoking, alcohol, and drug use), preoperative diagnosis, any accompanied comorbidities, EuroSCORE II, ejection fraction (EF), MUST score for the assessment of nutritional status, postoperative records for length of ICU and hospital stay, and follow-up laboratory exams were obtained from medical records of the selected patients. After having retrieved the data from the patients’ general blood tests, the values of lymphocytes, neutrophils, and platelets preoperatively and on the 3rd, 5th, and 7th postoperative days were used for NLR and PLR calculations. The NLR ratio was defined as the absolute neutrophil count divided by the absolute lymphocyte count on a given day, and the PLR as the absolute platelet count divided by the absolute lymphocyte count. These parameters were named NLR0, NLR3, NLR5, and NLR7 as well as PLR0, PLR3, PLR5, and PLR7, for day 0 (preoperatively) and postoperative days 3, 5, and 7, respectively. ## 2.3. Statistical Analysis Statistical analysis was conducted with the Statistical Package for Social Science (SPSS), Inc. (v 25.0; Chicago, IL, USA). The normality of the data’s distribution was assessed using the Kolmogorov–Smirnov or Shapiro–Wilk test when the evaluated group included more or less than 50 patients, respectively. For continuous variables, the results were presented as mean ± standard deviation (SD) if normality was assumed, and as the median and the interquartile range (IQR) for variables with skewed distribution. Moreover, for the comparison of two independent samples’ means, an independent sample t-test was performed, while the Mann–Whitney test was used to find the differences between the medians of two independent samples. Qualitative data were presented as percentages and the chi-square test was used for nominal variables. Multivariate logistic regression was performed for identifying the potential predictive factors responsible for 90-day mortality. Thus, after the univariate logistic analysis of every possible factor had been performed, a multivariate logistic analysis was conducted, and the final model was built. During univariate regression, a factor was included in the multivariate logistic regression model when it met a statistical significance of a p value less than 0.20. The final model was built using a stepwise backward elimination method with a significance level of 0.05. In addition, a receiver operating characteristic (ROC) curve was generated to calculate the optimal cut-off point of the derived indices for 90-day mortality and length of hospital stay, which was chosen based on the accompanying Youden’s index [19,20]; sensitivity and specificity were also measured. After the optimal cut-off points for NLR and PLR had been calculated, the sample size was divided into two groups based on them, and the mortality incidence was reassessed. Any linear correlation was assessed with the help of the Pearson or Spearman correlation coefficients, when normality was or was not assumed, respectively. Finally, a post hoc power analysis was performed to estimate the power of this study [21]. ## 3. Results One hundred eighty-nine consecutive patients were eligible for this post hoc analysis. Ten were lost to follow-up and there were no available data from their records. Thus, 179 were included in the final analysis. The post hoc power analysis for the NLR7 [mortality ($20\%$) when NRL7 > 6.60 versus mortality of the whole sample ($6.15\%$)] revealed a power of $81.2\%$ with a level of significance of 0.05 (two-sided). The demographic and clinical characteristics of the participants are presented in Table 1. The diagrams of hematological parameters and the derived indices as they varied up to postoperative day 7 are shown in Figure 1. Additionally, the data from the blood analysis and the derived hematological indices are presented in Table 2. Eleven patients died within the first 90 postoperative days (rate:$6.15\%$). The time to death measured in days has a mean of 32.9 days (SD = 19.5 days) and a median of 29 days (min = 15 days, max = 85 days). Six patients died within the first month postoperatively and the other five during the second and the third month. There was no difference between survivals and non-survivals regarding the duration of extracorporeal circulation (78.2 ± 32.5 min vs. 77.2 ± 28.7 min, $$p \leq 0.921$$). There is no sign of difference, or, in other words, no predictive value of NLR0 and PLR0 for patients who finally died ($$p \leq 0.185$$ and $$p \leq 0.915$$, respectively). The mean time of patients being intubated was 1.52 ± 2.20 days (median: 1.0, min: 1.0, max: 26.0) for survivals and 10.72 ± 9.03 days (median: 12.0 days, min: 1.0, max: 25.0) for non-survivals ($p \leq 0.001$). Eight out of 11 patients who died remained intubated and under ventilatory support for more than 48 hours. Thus, we continued testing the predictive value of NLR and PLR on the 3rd, 5th, and 7th postoperative days and found that only NLR5, NLR7, and PLR3 showed significantly good performance. ## 3.1. NLR and 90-Day Mortality Our findings highlighted the NLR7 values as the most predictive factor for 90-day mortality. The probability of death was greater as the NLR value increased. As shown in Figure 2, the discriminative performance for predicting 90-day mortality was better for NLR7 (AUC = 0.925, CI $95\%$: 0.865–0.984) than for NLR5 (AUC = 0.810, CI $95\%$: 0.678–0.942). The optimal cut-off point was 6.60 for NLR7, with a sensitivity of $100.0\%$ and specificity of $78.2\%$, while for NLR5, it was 7.10, with a sensitivity of $100.0\%$ and specificity of $50.0\%$. When patients were divided according to the optimal cut-off point of 6.60 for NLR7, the mortality was found to be $20.00\%$ (11 out of 55 patients) in patients with an NLR7 value > 6.60, which was significantly higher compared to the survival of the rest of the patients ($0\%$, $p \leq 0.001$) and that the whole sample overall ($20.00\%$ vs. $6.15\%$, $$p \leq 0.002$$) as well. Similarly, after patients had been divided according to the optimal cut-off point of 7.10 for NLR5, the mortality was $10.52\%$ (10 out of 95 patients) in patients with an NLR5 value > 7.10, which was also significantly higher compared to the mortality of the patients with NLR5 value ≤ 7.10 ($1.19\%$, $$p \leq 0.011$$), but not compared to the overall survival of the sample ($10.52\%$ vs. $6.15\%$, $$p \leq 0.194$$). ## 3.2. PLR and 90 Day Mortality Regarding PLR, as opposed to NLR, the probability of death increases as the PLR value decreases. Its discriminatory performance for predicting 90-day mortality after cardiac surgery and the respective ROC curve is presented in Figure 3. More specifically, the PLR3 exhibited a significant strong discriminatory performance (AUC = 0.714, CI $95\%$: 0.581–0.847), while PLR5 and PLR7 values were not statistically significant (PLR5: AUC:0.585, $95\%$ CI: 0.371–0.798, PLR7: 0.650, $95\%$ CI: 0.414–0.887). Regarding the optimal cut-off point of PLR3, this was 126.34, with a sensitivity of $100.0\%$ and specificity of $43.7\%$. Based on these, it should be mentioned that although PLR5 and PLR7 failed to be discriminative predictors, 9 out of the 11 patients who died had not only PLR3 < 126.34 but also NLR5 > 7.10 and NLR7 > 6.60. Additionally, after splitting the patients according to the PLR3 cut-off point of 126.34, it was found that in those 99 patients having low PLR3 values, the mortality rate was significantly higher ($10.1\%$) compared to that ($1.25\%$) of the remaining 80 patients ($$p \leq 0.017$$), but not compared to the overall survival of the sample ($$p \leq 0.194$$). ## 3.3. NLR, PLR, and 90-Day Mortality For further analysis, we divided the patients into four categories based on an arbitrary point system according to the number of predictors that were met. We considered “abnormal” regarding NLR any NLR5 value > 7.10 and any NLR7 > 6.60, and for PLR, any PLR3 value < 126.34. Thus, four categories were formed: 0: when neither PLR3, NLR5, nor NLR7 were abnormal, 1: when one of PLR3, NLR5, or NLR7 was abnormal, 2: when two of them were abnormal, and 3: when all of them were abnormal. The results are presented in Table 3; it is clear that the mortality rate was $0\%$ for the 107 patients having a score of 0 or 1, $4.35\%$ for the 46 patients having a score of 2, and $34.6\%$ for the 26 patients having a score of 3 ($p \leq 0.001$). Then, a multivariate binary logistic regression analysis was performed in order to identify any potential independent risk factors for mortality. In the univariate analysis, we included, besides the factors shown in Table 4, PLR3, PLR5, and NLR7 (as scale variables), which had shown good discriminatory performance in the ROC curve analysis. In the multivariate analysis, we included gender, age, and MUST score (regardless of the fact that they have not achieved the level of significance we have set ($$p \leq 0.20$$) for making a factor eligible for inclusion in the multivariate analysis) because of their clinical significance for heart diseases. We also included EuroSCORE II, ICU length of stay, PLR3, NLR5, and NLR7, which achieved a significance level of less than 0.20. The multivariate analysis finally revealed that only NLR7 (OR: 2.143, $95\%$ CI: 1.076–4.267, $$p \leq 0.030$$) and ICU length of stay (OR:1.361, $95\%$ CI: 1.045–1.774, $$p \leq 0.022$$) were significant independent risk factors for 90-day mortality after cardiac surgery, adjusted for gender, age, and MUST score, while PLR3 and NLR5 lost their significance. The detailed results are presented in Table 4. ## 3.4. NLR, PLR, and Length of Hospital Stay Regarding the predictability of NLR and PLR for the prolongation of in-hospital length of stay (>7 days), PLR3, NLR5, and NLR7 were found to have the best-fitted discriminative performance. The respective ROC curves are presented in Figure 4. The AUC for PLR3 was 0.616 (CI $95\%$: 0.516–0.717) and the optimal cut-off point 131.44, with a sensitivity of $66.9\%$ and specificity of $55.3\%$; for NLR5, the AUC was 0.637 (CI $95\%$: 0.535–0.738) and the optimal cut-off point 7.93 with a sensitivity of $50.0\%$ and specificity of $78.4\%$; and for NLR7, the AUC was 0.638 (CI $95\%$: 0.544–0.732) and the optimal cut-off point 4.03 with a sensitivity of $60.5\%$ and specificity of $74.3\%$f. PLR3 and length of hospital stay exhibited a negative linear correlation, with a Spearman correlation coefficient of −0.255 ($$p \leq 0.001$$). Finally, when the PLR and NLR values from the 3rd, 5th, and 7th postoperative days were assessed for the potential of a linear correlation, significant strong evidence was only found between PLR3 and NLR3 (Table 5). ## 4. Discussion In a recent systematic review and meta-analysis of 12 studies with 13,262 cardiac surgery patients, Perry et al. [ 22] conclude that the perioperative NLR value is an independent predictor of short-term and long-term postoperative mortality, besides a considerable between-study statistical heterogeneity (I2 = $94.39\%$) explained by the study-level variables. In light of their findings, we decided to perform the present post hoc analysis of data collected from our group for a primary cohort survey [17], where we have shown that cardiac surgery patients are at risk of nutritional status deterioration—as assessed by means of BIA, mainly phase angle and fat-free mass—positively related to morbidity and mortality; our data regarding NLR and PLR were, thus, evaluated as predictive indices for 90-day mortality, trying to avoid the bias reported in the aforementioned meta-analysis. Among all the parameters analyzed, the NLR5 and NLR7, as well as PLR3, were found to exhibit good discriminatory performance for predicting 90-day mortality. The multivariate analysis performed thereafter showed that NLR7 and the ICU length of stay were independent risk factors for death, adjusted for age, gender, and MUST score. Prolonged ICU length of stay has also been confirmed as an independent risk factor in other studies, which reported that postoperative morbidity and mortality are increased in patients with prolonged ICU stay after cardiac surgery. Moreover, prolonged hospitalization is mainly associated with respiratory events and prolonged ventilator intubation time [23]. Thus, in our study, most of the patients who finally died had remained intubated for more than 48 hours in the ICU. At this point, it should also be noted that in the multivariate analysis model, the preoperative MUST score, which is an indicator of patients’ nutritional status, was not associated with increased mortality, because there was no difference detected in the median MUST score between the patients who died and those who survived. Furthermore, when dividing the patients according to “points” received—one point per each positive predictor NLR5, NLR7, and PLR3—most of the patients having the highest score of 3 points eventually died (9 out of 11). Moreover, PLR3, NLR5, and NLR7 also have good performance for predicting the prolongation of hospital stay of more than 7 days. It is well known that the contribution of NLR and PLR in evaluating the immune status of patients, and consequently their inflammatory response, has been studied thoroughly in the last two decades [24]. Moreover, during an overwhelming inflammatory response, lymphocytopenia and lymphocyte hypoactivity occur, due to B-cells and T-cells apoptosis, both contributing to greater mortality [25,26]. In addition to lymphocytopenia, neutrophilia and inappropriate systemic neutrophil activation and migration within the microvasculature contribute to tissue damage and multiple organ failure [27]. Furthermore, in cardiac surgery patients, besides the operational stress itself, the additional use of the stressful extracorporeal circuit triggers an unavoidable major immune response, accelerated through the contact of the blood products and the surfaces of the CPB tubes. Additionally, during anesthesia and surgery, the activation of the neuroendocrine system results in the release of cytokines and hormones, which induce systemic leukocyte alterations affecting NLR [28]. In our study, the mean cardiopulmonary bypass time was 78.0 ± 32.3 min, and although the aortic cross-clamp time was not recorded, it was estimated to be around $20\%$ less than the time needed for extracorporeal circulation. NLR and PLR have been evaluated, either separately or together, as predictive factors for mortality related to cardiovascular outcomes [29,30]. The prognostic performance of these indices has been also evaluated by others on cardiac surgery patients [31,32,33,34]. In a recent retrospective study of 1694 patients divided into two groups according to their preoperative NLR optimal cut-off point of 3.23, the authors conclude that patients having an NLR value greater than 3.23 experienced greater mortality (OR:3.36, $95\%$ CI: 1.63–6.91); other parameters such as the ICU stay were also affected [35]. The predictive value of preoperative NLR and PLR values for major adverse cardiovascular and cerebrovascular events has also been confirmed by Larmann et al. [ 36], who reported a cut-off point of >204.4 for PLR and >3.1 for NLR. However, it should be highlighted that both studies referred to the preoperative NLR and PLR values, this probably being the reason they report lower cut-off values compared to our results. In our study, we evaluated the postoperative values of NLR and PLR, which are definitely affected by the inflammatory response elicited by operational stress. Very similar are the results of Zhu et al. [ 37], who found the critical postoperative NLR value to be 7.23 when they correlated NLR with mortality after cardiac surgery. In the same manner, the optimal cut-off point for predicting mortality with NLR on postoperative day 1 was 7.28 in a recent retrospective study including 2707 cardiac surgery patients. Our post hoc analysis also reveals that the lower the PLR value, the higher the possibility of death. This could be easily explained by the fact that thrombocytopenia is a sign of both infection and inflammatory response; platelets interact with white blood cells or vascular endothelial cells directly, based on a contact-dependent mechanism, and indirectly through the secretion of inflammatory cytokines [38]. Thus, the involvement of platelets in the inflammatory process is noted both locally and systemically [39]. This recruitment of platelets in combination with their adhesion to white blood cells to enhance their effect reduces the absolute number of circulating platelets, which is then reflected in the decrease in PLR [40]. This is why we demonstrate a reversed probability—the lower the PLR, the higher the probability of death—while others, by using preoperative values, support a positive correlation [36]. It is of interest to mention that when the patients were divided according to the points received—one point per each positive predictor NLR5, NLR7, and PLR3—we found that 9 out of 11 patients who died presented with all the parameters (PLR3, NL5, and NLR7) positive, whereas when none of the indices were abnormal, all the patients survived. This finding is in accordance with a previous study, where the predictive power increased in parallel with the number of abnormal parameters measured (NLR, red cell distribution width, and mean platelet volume) [15]. Based on all the aforementioned findings, we could support the suggestion that these parameters could be highly informative for the postoperative monitoring of cardiac surgery patients, and they are easy to perform and of a very low cost; they consist of a routine, daily practice, and calculating them during the first 7 postoperative days may let the patients who are at higher risk for adverse outcomes, including mortality, to be detected, even from the 3rd postoperative day. It is commonly accepted that doctors have a perpetual desire and will to be able to predict the prognosis of their patients. However, this commitment should not let them forget that their role is to provide the best possible care to critically ill patients, regardless of whether the odds are in their favor or whether the patient’s survival would be a minor miracle. Healthcare professionals should follow the “deontological theory” and try to gain the greatest good for the patient and act for the patients’ benefit [41]. Given the above, the strategy of predicting as soon as possible which patients have a higher chance of experiencing worse morbidity or higher mortality aims at triggering the reflexes of physicians in time and alerting them to possible complications that may arise in the future. In this way, it will be possible to ensure maximum patient-centered medical care delivery with the lowest possible consumption of resources, as these are consumed on the basis of need rather than horizontally. The contribution of the NLR and PLR predictive value to personalized medicine is pivotal because these easily CBC-derived indices are useful information that could affect treatment decisions about patients. These include identifying patients at higher risk of experiencing a more stressful postoperative course after major cardiac surgery; those patients should be monitored more closely and carefully. Additionally, NLR and PLR in combination with other equally simple and available biomarkers, such as C-reactive protein, erythrocyte sedimentation rate, or even procalcitonin and pancreatic stone protein, could take a “one size fits all” treatment approach and turn it into an individualized and patient-centered approach, which would be more effective and possibly less costly. There are some limitations in this study. First, it is a post hoc analysis of retrospectively collected data for the primary work. Second, based on the variation in hematological parameters, our sample size could be considered small. However, the conducted post hoc power analysis has revealed a power of $81.2\%$; thus, the results are reliable, and safe conclusions can be drawn. Finally, regarding the mortality observed in our study, 30-day mortality (6 out of 179 patients) was $3.35\%$ and 90-day mortality (11 out of 179 patients) was $6.15\%$. Although these percentages could be considered relatively high, they are equivalent to the percentages presented in the original EuroScore II study ($4.048\%$ and $6.023\%$, respectively) [42], while in this study, we aimed to evaluate only the predictive character of the aforementioned hematological parameters and, thus, analyzing the causes of these results would be beyond the purposes of our work. ## 5. Conclusions The present post hoc analysis strengthens the suggestion that NLR and PLR values are efficient predictive factors for 90-day mortality and hospital length of stay in adult cardiac surgery patients. More specifically, NLR5, NLR7, and PLR3 seem to exhibit the best discriminatory values for predicting 90-day mortality, whereas NLR5 > 6.60, NLR7 > 7.70, and PLR < 126.34 were found to be the optimal predictive cut-off points. Additionally, an elevated postoperative NLR value (NLR7 > 6.60) and the ICU length of stay are independent risk factors for increased 90-day mortality. Additionally, more than two of these indices being positive significantly increases the possibility of death occurring. The aforementioned findings can be simply summarized with the perspective that, owing to the simplicity of determining the NLR and PLR values, monitoring them can predict the early outcome of adult patients undergoing cardiac surgery. ## References 1. 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--- title: 'Healthy Diet, Polygenic Risk Score, and Upper Gastrointestinal Cancer Risk: A Prospective Study from UK Biobank' authors: - Wenmin Liu - Tianpei Wang - Meng Zhu - Guangfu Jin journal: Nutrients year: 2023 pmcid: PMC10054787 doi: 10.3390/nu15061344 license: CC BY 4.0 --- # Healthy Diet, Polygenic Risk Score, and Upper Gastrointestinal Cancer Risk: A Prospective Study from UK Biobank ## Abstract Dietary and genetic factors are considered to be associated with UGI cancer risk. However, examinations of the effect of healthy diet on UGI cancer risk and the extent to which healthy diet modifies the impact of genetic susceptibility on UGI cancer remains limited. Associations were analyzed through Cox regression of the UK *Biobank data* ($$n = 415$$,589). Healthy diet, based on “healthy diet score,” was determined according to fruit, vegetables, grains, fish, and meat consumption. We compared adherence to healthy diet and the risk of UGI cancer. We also constructed a UGI polygenic risk score (UGI-PRS) to assess the combined effect of genetic risk and healthy diet. For the results high adherence to healthy diet reduced $24\%$ UGI cancer risk (HR high-quality diet: 0.76 (0.62–0.93), $$p \leq 0.009$$). A combined effect of high genetic risk and unhealthy diet on UGI cancer risk was observed, with HR reaching 1.60 (1.20–2.13, $$p \leq 0.001$$). Among participants with high genetic risk, the absolute five-year incidence risk of UGI cancer was significantly reduced, from $0.16\%$ to $0.10\%$, by having a healthy diet. In summary, healthy diet decreased UGI cancer risk, and individuals with high genetic risk can attenuate UGI cancer risk by adopting a healthy diet. ## 1. Introduction Upper gastrointestinal (UGI) cancer, including esophageal cancer (ESC) and gastric cancer (GC), account for 1.7 million new cancer cases and 1.3 million deaths each year worldwide [1]. Previous studies have identified several common environmental risk factors for UGI cancer, including tobacco [2] and alcohol consumption [3], obesity [4], physical activity [5], and dietary factors [6]. Dietary components have received an increasing amount of attention as a potentially modifiable factor [7,8]. It was estimated that 5.1–$5.9\%$ of cancer cases each year worldwide can be attributed directly to poor diet [9]. As recently reported by the World Cancer Research Fund International/American Institute for Cancer Research, the role of individual dietary components on UGI cancer risk remains controversial and limited [10]. Rather than individual dietary components, people consume diverse foods together, and the resulting complex combination of dietary components is likely to have interactive or synergistic effects [11]. In this context, dietary pattern analysis has been recommended as an approach because it considers the complexity of overall diet and can potentially facilitate public health interventions [12]. In recent years, cancer prevention guidelines have shifted from reductionist or nutrition-centric approaches to more holistic dietary concepts characterized by dietary patterns. Holistic dietary concepts emphasize how food as a whole can prevent chronic disease, associating nutrients, foods or food groups with health rather than studying the role played by nutrient/food interactions in health [13,14,15]. Adherence to a dietary pattern can be assessed using a priori method, which is constructed on the basis of a predefined set of criteria (generally based on guidelines) to measure diet quality in a given population [16], which would be easier to make comparisons between different studies and populations. A meta-analysis of the association of GC risk with dietary patterns indicated that Western dietary patterns (generally considered unhealthy, characterized by an increased consumption of meat, high-fat dairy products, sweets, and starchy foods) were associated with a higher GC risk, while prudent dietary patterns (generally considered healthy, characterized by higher intake of vegetables and fruits) played a protective factor [17]. A case-control study suggested that adherence to a healthy dietary pattern represented by high loadings of vegetables and fruits was associated with a lower risk of GC [18]. However, there is no large-scale prospective cohort study that systematically investigates the association between dietary patterns and UGI cancer risk. Accumulating evidence has shown that genetic factors have major roles in the development of UGI cancer [19,20]. Recent genome-wide association studies (GWAS) have identified dozens of genetic variants associated with UGI cancer risk [21,22]. The PRSs, gathering genetic contribution and effects of all UGI cancer-associated genetic variants, have been proven to effectively predict incident cases of ESC and GC [23,24]. Both dietary factors and genetic risk play an essential role in the development of the disease. A Gene-Diet Interaction Study from the UK Biobank showed that, compared with those in the lowest intraocular pressure (IOP) polygenic risk score (PRS) quartile who consumed no caffeine, those in the highest IOP PRS quartile who consumed ≥321 mg/day showed a 3.90-fold higher glaucoma prevalence [25]. Moreover, one current study suggested that genetic factors modified the association between diet and cardiovascular disease (CVD) [26]. However, previous studies have typically focused on the separate effects of dietary factors and genetic factors on UGI cancer risk. Few studies provided insight into the combined effect of dietary factors and genetic factors on UGI cancer risk. It is unclear whether there is a gene-diet combined effect or interaction in the risk of UGI cancer development, as well as the extent to which participants with a high genetic risk of UGI cancer can offset that risk by adhering to a healthy diet. In this study, we conducted dietary pattern analysis based on examining the adherence to healthy diet and investigated the association of adherence to healthy diet with UGI cancer risk using UK Biobank data. We also tested the hypothesis that dietary factors and genetic factors jointly contribute to incident UGI cancer and that adopting a healthy diet can attenuate UGI cancer risk for individuals at high genetic risk. ## 2.1. Study Design and Participants UK *Biobank is* a large, population-based prospective study with genetic and phenotypic data. Between 2006 and 2010, UK Biobank recruited over 500,000 participants from the general population who were aged 40–69 years. Participants were recruited at 22 assessment centers located throughout England, Wales, and Scotland [27]. Participants completed a touch-screen questionnaire, took physical measurements, and provided biological samples at assessment centers. The basic collection details are described elsewhere [28,29]. We excluded participants with prevalent cancer ($$n = 46$$,531), those who were missing any dietary information data ($$n = 40$$,132), and individuals who had withdrawn consent for future linkage ($$n = 157$$), leaving 415,589 participants (193,083 men and 222,506 women) included in the study. First, we examined the association between the degree of adherence to healthy diet defined by healthy diet score and UGI cancer risk. Then, we compared the combined effect and interactions of healthy diet and genetic risk categories on UGI cancer risk across genetic risk groups. Last, we compared the benefit of adherence to a healthy diet within genetic risk groups (Figure 1). ## 2.2.1. Dietary Intake Assessment The touch-screen questionnaire, self-completed at baseline, was used to collect the frequency of consumption of the following 12 food items over the previous year with FFQ: beef, lamb, pork, processed meat, oily fish, non-oily fish, fresh fruit, dried fruit, raw vegetables, cooked vegetables, cereal, and bread. We also created new data fields based on food items: [1] Red meat intake, [2] Total fish intake, [3] Total vegetables intake, [4] Total fruit intake, [5] Whole grains intake, and [6] Refined grains intake. We summed beef, lamb and pork intake to create red meat intake. We also summed oily fish and non-oily fish intake to generate total fish intake. To calculate total vegetables and fruit consumption respectively, we aggregated cooked vegetables and salad/raw vegetable intake as total vegetables intake, and fresh fruit and dried fruit as total fruit intake. We divided grains into whole grains and refined grains according to the type of bread and cereal mainly consumed. We defined wholemeal or wholegrain bread, bran cereal, oat cereal, and muesli as whole grains; white bread, brown bread, other bread, biscuit cereal, and other cereals as refined grains. We categorized the 12 food items into 7 food groups, including red meat, processed meat, total fish, total fruit, total vegetables, whole grains and refined grains. We also defined serving size for each baseline food items. For bread and cereal, data were provided for weekly consumption, which were converted into daily consumption. Detailed serving size and coding for each food item/food group are shown in Table S1. ## 2.2.2. Healthy Diet Score Estimation We adopted seven dietary factors and cut-offs according to recommendations for dietary priorities on cardiometabolic health [30], that is, increasing fruit, vegetables, whole grains, and fish consumption, and decreasing red meat, processed meat, and refined grains intake. The healthy diet score was calculated using the seven dietary components: Total fruit ≥ 4 servings/day; Total vegetables ≥ 4 servings/day; Total fish ≥ 2 servings/week; Processed meat ≤ 1 serving/week; Red meat ≤ 1.5 servings/week; Whole grains ≥ 3 servings/day; Refined grains ≤ 1.5 servings/day. Each favorable dietary factor was given one point (Table S2). The score ranged from 0 to 7; we defined score 0–1 as low-quality diet, 2–4 as intermediate-quality diet, and 5–7 as high-quality diet, according to data distribution characteristics. Next, we categorized the scores into unfavorable diet (healthy diet score < 4) and favorable diet (healthy diet score ≥ 4). ## 2.3. PRS Calculation and UGI-PRS Construction Genotyping process and single nucleotide polymorphisms (SNPs) used in the UKB research have been described elsewhere in detail [31,32]. We extracted variants with $p \leq 5$ × 10−8 and minor allele frequency (MAF) ≥0.01 from GWAS with the largest sample size in European ancestry [23,33]. For variants that were not available in the UKB genotyping data, their strong correlated SNPs (r2 > 0.8) were included in the present study. If more than one variant correlated in the same locus were reported, the SNPs with the smallest reported p-value were selected by using the linkage disequilibrium clumping procedure (at r2 < 0.2) in PLINK. We excluded SNPs with allele mismatches or MAF differences > 0.10, compared with those in the European population of 1000 Genomes, and palindromic SNPs (A/T, G/C) with an MAF ≥0.45. Finally, we estimated site-specific PRS based on 13 SNPs and 3 SNPs for ESC and GC, respectively (Table S3). No SNPs were shared or in high LD (r2 > 0.6) with each other in more than one site-specific PRS. Firstly, site-specific PRS was created following an additive model [34], generated by multiplying the genotype dosage of each risk allele by its respective effect size, summing all alleles together. Then, we built a UGI-PRS to assess UGI cancer risk by summing site-specific PRSs weighted by ESC and GC age-standardized incidence rate in the UK population [35]. Cancer site-specific PRS has been proven to effectively identify individuals with high risk of overall cancers and gastrointestinal cancer risk [36,37]. The UGI-PRS was divided into three levels of genetic risk: low (lowest quintile), moderate (quintiles 2–4), and high (top quintile). ## 2.4. Outcome Assessment The outcomes in the study were first primary incident events due to UGI cancer (ESC and GC), which is identified through the national cancer registries of England, Wales, and Scotland, coded by the 10th revision of the International Classification of Diseases (ICD-10), as (C15) and (C16) for ESC and GC, respectively. After four years of baseline recruitment (2006–2010), UGI cancer risk in participants was assessed from baseline up to the UGI cancer diagnosis, death, completion of follow-up, or loss to follow-up, whichever occurred first. The time of risk was calculated according to date the participant attended the assessment center (Data Field: 53), date of cancer diagnosis (Data Field: 40005) and the end date of follow-up. The end date of follow-up was updated to September 2018 for Scotland and to June 2021 for England and Wales. For participants who developed a UGI cancer, time at risk was the interval between the date of cancer diagnosis and the date of attending assessment. For participants without UGI cancer, time at risk was calculated by the end date of follow-up minus date of attending assessment center. ## 2.5. Statistical Analysis Cox proportional hazard models were used to investigate the associations between healthy diet and UGI cancer risk and to estimate hazards ratios (HRs) and $95\%$ confidence intervals (CIs) with the time of follow-up used as the timeline variable. The proportional hazard assumptions were checked using Schoenfeld residuals. We determined UGI cancer risk for participants among healthy diet score categories (low-quality diet, intermediate-quality diet, and high-quality diet group). We also compared the UGI cancer risk for per two-point increase in healthy diet score. Furthermore, we investigated the combined effect and interactions of dietary and genetic factors on UGI cancer risk according to healthy diet and genetic risk categories to explore the extent to which healthy diet modified the associations between genetic susceptibility and UGI cancer risk across genetic risk groups. We examined the results for potential additive and multiplicative interaction between healthy diet and genetic risk [38]. The additive interaction was evaluated using two indexes: the relative excess risk due to the interaction (RERI) and the attributable proportion due to the interaction (AP) [39]. The $95\%$ CIs of the RERI and AP were generated by drawing 5000 bootstrap samples from the estimation data set [40]. If there was no additive interaction, the CIs of the RERI and AP would include 0. In addition, we used RHR (ratio of HR) to evaluate the gene–diet multiplicative interactions by setting variable cross-product terms of the healthy diet with the genetic risk in the models. The $95\%$ CIs of RHR would contain 1 if there was no multiplicative interaction. We also calculated the absolute risk as the percentage of incident UGI cancer cases occurring in each genetic risk group to compare the benefit of adherence to a healthy diet with incident UGI cancer within genetic risk groups. The absolute risk reduction was calculated according to the given groups UGI cancer incidences difference, and then the difference in five-year event rates was extrapolated among given groups. The calculation of $95\%$ CIs for the absolute risk reduction were calculated by drawing 1000 bootstrap samples from the estimation dataset. Two models were applied in our analyses: minimally adjusted model, adjusted for age at recruitment, sex, Townsend deprivation index, assessment center (10 regions) and ethnic background; fully adjusted model, additionally adjusted for BMI (kg/m2, <25, 25–29.9, ≥30), glycosylated hemoglobin (HbA1c, mmol/mol, quintiles), smoking status (never, former, current, unknown), alcohol intake frequency (never/rare, twice or less per week, at least three times per week, unknown), education (college or university degree, no degree, unknown), multimorbidity (None, ≥1, unknown), physical activity (<600 MET minutes/week, 600–3000 MET minutes/week, >3000 MET minutes/week) [41] and family cancer history (yes, no, unknown) (Table S4). We additionally adjusted the top 10 genetic principal components of ancestry in the analysis including genetic risk. Missing data were coded as missing proxies (unknown) for categorical variables, while those for continuous variables were imputed with sex-specific median values. We performed the following sensitivity analysis to further investigate the robustness of our results: [1] excluded participants who reported that they had made a major change in their diet in the past 5 years due to illness in the past 5 years ($$n = 41$$,292); [2] excluded participants followed up for less than two years ($$n = 1648$$); [3] excluded non-white participants ($$n = 21$$,680). All statistical analyses were performed with R software for version 4.2.0 (R Core Team, Auckland, CA, USA). All p values were two-sided and $p \leq 0.05$ was considered statistically significant. ## 3.1. Participants and Characteristics A total of 415,589 participants ($53.54\%$ women) had available dietary data of this study. The median follow-up period was 12.12 (interquartile range: 11.32–12.84) years for UGI cancer incidence. A total of 1389 UGI cancer developed during the period, including 564 GC and 831 ESC. The baseline characteristics of participants are shown in Table 1. For 1389 UK Biobank participants (mean [SD] age, 61.21 [6.29] years; $27.93\%$ women) with incidents of UGI cancer had a mean (SD) BMI of 28.61 (5.19) kg/m2. Of all participants, the $16.99\%$ with UGI cancer were current smokers, and $23.18\%$ UGI cancer participants consumed alcohol at least three times per week. The 414,200 participants (mean [SD] age, 56.17 [8.09] years; $53.63\%$ women) had a mean (SD) BMI of 27.39 (4.75) kg/m2 without UGI cancer. A total of $10.25\%$ participants with UGI cancer were current smokers, and $18.29\%$ UGI cancer participants consumed alcohol at least three times per week. ## 3.2. Healthy Diet and the Risk of UGI Cancer The association between adherence to healthy diet and UGI cancer risk was shown in Table 2. Individuals with a high-quality diet that included high intake of fruit, vegetables, fish and whole grains and reduced amount of red meat, processed meat and refined grains had a lower risk of UGI cancer incidents compared with those in low-quality diet group, with HR of 0.76 ($95\%$ CI: 0.62–0.93, $$p \leq 0.009$$). Having a two-point increase in healthy diet score was associated with a higher UGI cancer risk, with HR of 0.90 ($95\%$ CI: 0.83–0.97, $$p \leq 0.006$$). Similar results were noted in a series of sensitivity analyses (Table S5). ## 3.3. Combined Effect and Interactions of Healthy Diet and Genetic Risk on UGI Cancer Risk We determined that participants who had an unhealthy diet and were in a high genetic risk group had an approximately 1.60-fold risk of UGI cancer risk, with HR reaching 1.60 ($95\%$ CI: 1.20–2.13, $$p \leq 0.001$$), when compared with participants with a healthy diet and low genetic risk (Figure 2). The results of the sensitivity analysis did not change materially (Figure S1A–C). The RERI, AP, and RHR were not significant, which indicated no additive and multiplicative interactions of healthy diet and genetic risk on the risk of UGI cancer (Table 3). ## 3.4. Benefits of Adherence to a Healthy Diet with UGI Cancer Risk In further stratification analyses with an unhealthy dietary pattern as the reference group according to genetic risk categories, we found that in the intermediate and high genetic risk groups, similar risk reduction for UGI cancer were observed in those who adhered to a healthy dietary pattern compared to those who adhered to an unhealthy dietary pattern. Among participants with an intermediate genetic risk, the absolute five-year incidence risk of UGI cancer were 0.13 for participants with an unhealthy dietary pattern versus 0.11 for those with a healthy dietary pattern. Similarly, for individuals with high genetic risk, the absolute five-year incidence risk of UGI cancer decreased from 0.16 for participants with an unhealthy dietary pattern to 0.10 for those with a healthy dietary pattern (Table 4). The results of sensitivity analyses were similarly (Table S6). ## 4. Discussion In this large, prospective study using UK Biobank, we investigated dietary pattern analyses based on healthy diet and UGI cancer risk. We found that improving the quality of healthy diet was associated with a lower risk of UGI cancer. *Across* genetic risk groups, analysis further showed that individuals with high genetic risk and an unhealthy dietary pattern were at a greater risk of UGI cancer compared to those with low genetic risk and a healthy dietary pattern. *Within* genetic risk groups, analysis indicated that adherence to a healthy dietary pattern was consistently associated with a decreased absolute five-year incidence risk of UGI cancer in intermediate and high genetic risk groups. Current studies suggested that dietary patterns analyses are regarded as good ways to explore diet and cancer risk. A systematic review and meta-analysis from prospective cohort studies supported an association between healthy dietary patterns and decreased risks of colon and breast cancer [42]. One study that focused on nutrition and breast cancer showed that adherence to a healthy dietary pattern might improve overall survival after diagnosis of breast cancer [43]. We performed dietary pattern analyses based on healthy diet score and the risk of UGI cancer. A systematic review and meta-analysis on dietary patterns and gastric cancer risk indicated that there is an approximately two-fold difference in GC risk between a ‘prudent/healthy’ diet, and a ‘Western/unhealthy’ diet [17]. A population-based case-control study suggested that a diet high in fruit and vegetables may decrease the risk of ESC cancer [44]. Another systematic review and meta-analysis suggested that a healthy dietary pattern was significantly associated with a decreased risk of ESC [45]. Our study also found similar results, i.e., that adherence to a healthy diet reduced the UGI cancer risk. We also compared the benefit of adherence to a healthy dietary pattern within genetic risk groups based on the calculation of absolute five-year incidence risk of UGI cancer. We found that individuals with intermediate and high genetic risk who adopted a healthy diet had a decreased risk of developing UGI cancer. For participants with high genetic risk, the absolute five-year incidence risk of UGI cancer was significantly reduced from $0.16\%$ to $0.10\%$ by having a healthy diet. Taken together, our findings along with previous evidence not only demonstrated the significance of adherence to healthy diet, but also provided collective support for public health interventions to promote a healthy dietary pattern for everyone, especially people with intermediate or high genetic risks, which will ultimately lead to a reduction of UGI cancer burden. It has been estimated that ESC and GC could be prevented in $54\%$ and $59\%$ of patients in the UK, respectively [46]. It is important to understand the contribution of modifiable risk factors to UGI cancer and how they affect or add to the inherited genetic factors. At present, several studies have summarized the association between diet and nutrition and the UGI cancer risk; however, reported meta-analytic estimates from observational studies may not represent causality. Instead, they may result from common biases across studies, such as exposure measurement error, residual confounding, and publication bias, and thereby weaken the strength of the scientific evidence [47,48,49]. In addition, few studies have focused on the combined effect and interactions of gene–diet on the risk of UGI cancer. We systematically and comprehensively investigated the association between modifiable dietary factors with UGI cancer risk and tested the hypothesis that UGI cancer risk can be modified or reduced by adopting a healthy diet in a large prospective cohort study. UK *Biobank is* a large, general population-based prospective cohort, which provides health outcomes and a wide range of potential confounders, including diet. One of the inevitable problems with large sample studies is that p values are more likely to be statistically different. In detail, a statistical p value is the distance between the data and the null hypothesis measured by an estimate of the parameter of interest. This distance is usually measured in terms of the standard deviation (standard error). The standard error shrinks as the sample size increases; in a very large sample, the standard error becomes very small, which leads to a statistically significant distance between the estimate and the null hypothesis that may be negligible. Therefore, to reduce type I errors, the null hypothesis cannot be rejected by the p-value alone in a large sample study. These problems can be solved by additionally reporting effect sizes and $95\%$ confidence intervals (CI) [50]. In our study, we provided $95\%$ CI as well as p values to more cautiously infer the association between healthy diet and UGI cancer. The present study has several limitations. First, participants in the UK Biobank are of European descent; therefore, the summary statistics should be generalized to the general population with caution. Secondly, the use of self-reported recall of FFQ could introduce some level of recall bias. Third, it is generally accepted that associations between nutrients and disease should only be considered primary if the effects are independent of energy intake [51]. We were not able to adjust for total energy intake because the baseline touchscreen brief FFQ only covered some commonly consumed foods. Therefore, our findings may be biased by the differences in body size, physical activity, and metabolic efficiency resulting from energy intake. 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--- title: Antibacterial, Anti-Biofilm and Pro-Migratory Effects of Double Layered Hydrogels Packaged with Lactoferrin-DsiRNA-Silver Nanoparticles for Chronic Wound Therapy authors: - Mohammad Aqil M. Fathil - Haliza Katas journal: Pharmaceutics year: 2023 pmcid: PMC10054788 doi: 10.3390/pharmaceutics15030991 license: CC BY 4.0 --- # Antibacterial, Anti-Biofilm and Pro-Migratory Effects of Double Layered Hydrogels Packaged with Lactoferrin-DsiRNA-Silver Nanoparticles for Chronic Wound Therapy ## Abstract Antimicrobial resistance and biofilm formation in diabetic foot infections worsened during the COVID-19 pandemic, resulting in more severe infections and increased amputations. Therefore, this study aimed to develop a dressing that could effectively aid in the wound healing process and prevent bacterial infections by exerting both antibacterial and anti-biofilm effects. Silver nanoparticles (AgNPs) and lactoferrin (LTF) have been investigated as alternative antimicrobial and anti-biofilm agents, respectively, while dicer-substrate short interfering RNA (DsiRNA) has also been studied for its wound healing effect in diabetic wounds. In this study, AgNPs were complexed with LTF and DsiRNA via simple complexation before packaging in gelatin hydrogels. The formed hydrogels exhibited $1668\%$ maximum swellability, with a 46.67 ± 10.33 µm average pore size. The hydrogels demonstrated positive antibacterial and anti-biofilm effects toward the selected Gram-positive and Gram-negative bacteria. The hydrogel containing AgLTF at 125 µg/mL was also non-cytotoxic on HaCaT cells for up to 72 h of incubation. The hydrogels containing DsiRNA and LTF demonstrated superior pro-migratory effects compared to the control group. In conclusion, the AgLTF-DsiRNA-loaded hydrogel possessed antibacterial, anti-biofilm, and pro-migratory activities. These findings provide a further understanding and knowledge on forming multipronged AgNPs consisting of DsiRNA and LTF for chronic wound therapy. ## 1. Introduction Diabetic foot infection (DFI) is a significant concern in many parts of the world, especially in countries where diabetes is highly prevalent, such as Malaysia [1,2]. Untreated or severe DFI can result in surgical amputation of the limbs, predisposing patients to other health complications and drastically reducing their quality of life [3]. To add to the woes of diabetic patients, conventional antibiotics are becoming less and less effective due to the rise of antimicrobial resistance (AMR), leaving them with minimal pharmacological options [4,5]. Diabetic wounds also have delayed regenerative capacity due to a cascade of biological implications in high blood sugar levels, which could further aggravate the condition [6]. Increasing demand for new and alternative antibiotics to tackle AMR leads to the development of silver nanoparticles (AgNPs) as antimicrobial agents. AgNPs are heavily utilized in research settings for their antimicrobial properties and have demonstrated promising results even against resistant bacterial strains [7,8,9,10]. AgNPs offer numerous advantages as antimicrobial agents in terms of their adherence and penetration ability toward the cell surface of bacteria [11,12,13]. In addition, AgNPs that are stabilized by chitosan (CS) provide avenues for complexation with biological molecules, such as deoxyribonucleic acid (DNA) and ribonucleic acid (RNA), via their phosphorus and sulfur donor ligands [14,15]. However, with the advancement of medicines, such as humans, microorganisms, such as bacteria, have also gone through numerous evolutions to thrive in harsh and foul environments [16,17]. Bacteria can form biofilms, which are a plethora of different species living under a matrix made up of exopolysaccharides (EPS) that can protect themselves from the harmful effects of traditional antibiotics, AgNPs, and Ag+ due to its complex structure [18,19,20,21]. Hence, the same concentration of AgNPs usually effective against planktonic bacteria will not work the same against bacteria protected in a biofilm [11]. In addition, bacteria living in biofilm matrices can efficiently exchange nutrients and pass on plasmids containing resistance genes to promote growth and survivability [22,23,24]. Consequently, the formation of biofilms causes persistent tissue infection and can further delay wound healing in diabetic patients [25,26]. As such, the addition of lactoferrin (LTF) to AgNP therapy makes sense, as LTF can boost the subpar and strain-dependent anti-biofilm effects of AgNPs [27,28]. Basically, LTF is an iron-chelating protein found in blood and bodily secretions, such as tears, sweat, and vaginal secretions [29,30]. In reference to its anti-biofilm property, LTF has been shown to have synergistic effects in combination with agents [31], such as AgNPs [27] and Xylitol [32], against biofilm-producing organisms. Since biofilm formers are also common pathogens associated with diabetic foot ulcers [22], combining AgNPs and LTF could potentially inhibit biofilm formation and eradicate bacteria that are living in diabetic wounds. In diabetic patients, foot ulcers are difficult to treat due to multiple factors, including defects in peripheral and endothelial vascular function [33,34]. On a cellular level, prostaglandin E2 (PGE2), which is important in maintaining proper endothelial and peripheral vascular function in the biological system, is underexpressed due to abnormally high levels of prostaglandin transporter (PGT) in hyperglycemia [35]. Dicer-substrate short interfering RNA (DsiRNA) has been extensively studied as a genetic and modern approach to silence PGT upregulation in hyperglycemic cell lines [35,36]. In vitro and in vivo studies of DsiRNA against the PGT gene have demonstrated increased VEGF levels, shortened complete wound closure time, and triple the number of blood vessels against the control [37]. DsiRNA can also form complex metallic nanoparticles with the aid of a CS monolayer due to the anionic nature of RNA [38]. This complexation of DsiRNA onto CS has been shown to improve the localization of DsiRNA in cells [39]. Hence, combining DsiRNA with LTF and AgNPs could potentially provide better healing effects due to its triple action of healing, antibacterial, and anti-biofilm properties. Hydrogels are commonly used as a drug delivery system for wound healing, as they are biocompatible, have a high water content, and have a rubbery consistency [40,41,42]. In addition, hydrogels provide moist and suitable environments conducive to wound re-epithelialization of tissues [43]. They can also utilize nanoparticles as a drug depot and significantly prolong the drug release duration, which increases drug bioavailability and patient compliance [44,45]. In this instance, gelatin is often used as a base for hydrogels because it is cheap, easily accessible, has excellent cell adhesion properties, low antigenicity, and versatile chemical and physical modifiability [46,47]. However, the downside of gelatin is that it has unstable mechanical properties under physiological conditions, despite the presence of physically crosslinked nanoparticles. This necessitates using chemical crosslinkers to enhance and strengthen connective chains from faltering in the medium [48,49]. Employment of both physical and chemical crosslinkers in a hydrogel could permanently fix the shape at rest, showing low fracture toughness and extensibility. This is ideal in a hydrogel that requires the extended release of active components [50]. Such characteristics are important because sequential and prolonged-release therapy, according to the wound healing stages that consist of the initial inflammation stage followed by a proliferation stage of up to 10 days, has been shown to have an enhanced healing effect [51]. Developing multifunctional hydrogel dressings that are able to eliminate bacterial infections and accelerate the diabetic wound healing process is often desirable to address these issues associated with diabetic wounds [43,52]. In the present study, synthesized AgNPs complexed with LTF and DsiRNA are separately compartmentalized in a double-layered hydrogel to produce a three-way therapy to combat biofilm-producing pathogens and, at the same time, expedite the healing capacity of human skin cells, which are released in accordance with the wound healing stages. The proposed treatment offers advantages, including being easy to produce, as it does not involve lengthy protocols and sophisticated instruments. Furthermore, it is also environmentally friendly, as it promotes using natural compounds to synthesize AgNPs. Both the nanocomposites and the gel were characterized for physical characteristics and drug release behaviors. The antibacterial and anti-biofilm properties of AgNPs and LTF were determined using a microbroth dilution test and crystal violet assay, whereas the in vitro migration quantification of cells after treatment with AgNP-DsiRNA was determined via the wound scratch assay. The gels that demonstrated enhanced healing properties while effectively eradicating common biofilm-forming pathogens would be very effective for application as a therapy for diabetic wounds. ## 2.1. Materials TMM powder (Lignosus rhinocerotis) was received from Lignas Bio Synergy Plt., Sepang, Malaysia, as a donation. Silver nitrate (AgNO3) (ACS reagent grade), low molecular weight (LMW) CS (50–190 kDa, 75–$85\%$ deacetylated), and human recombinant LTF (expressed in rice, iron-saturated and >$90\%$ SDS PAGE) were procured from Sigma Aldrich, MO, USA. Ciprofloxacin HCl was obtained from TargetMol, MA, USA, whereas Ciprofloxacin in 5 µg disks was purchased from Thermo Fisher Scientific, MA, USA. Three bacterial strains (*Staphylococcus aureus* ATCC 25923, *Pseudomonas aeruginosa* ATCC 27853, and *Escherichia coli* ATCC 25927) were requested and received from Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia. Mueller-Hinton broth (MHB) and Mueller-Hinton agar (MHA) were obtained from TargetMol, MA, USA. Crystal violet was purchased from Chemiz, Shah Alam, Malaysia. Ethanol ($70\%$) was procured from J-Kollin Chemicals, Midlothian, UK, and glacial acetic acid ($99.7\%$ purity) was purchased from R&M Chemicals, Subang, Malaysia. Both gelatin and genipin, which were used to form hydrogel bases, were procured from Sigma Aldrich, MO, USA. A human epidermal keratinocyte cell line (HaCaT) (passage 0) was purchased from Addexbio, CA, USA, for cell viability and migration tests. DMEM high glucose (4.5 g/L D-(+)-Glucose) and low glucose (1.0 g/L D-(+)-Glucose) with pre-added supplements L-Glutamine, phenol red, and sodium pyruvate were procured from Nacalai Tesque, Kyoto, Japan. AlamarBlue (AB) cell viability reagent was procured from Invitrogen, MA, USA. Pen-Strep (penicillin/streptomycin) and fetal bovine serum (FBS) were purchased from Tico Europe, Amstelveen, Netherlands. Protein extraction from the cells was done using radioimmunoprecipitation assay (RIPA) buffer, procured from Sigma Aldrich, MO, USA, and phenylmethylsulfonyl fluoride (PMSF) as a protease inhibitor, which was purchased from Roche, Basel, Switzerland. Prior to the assay, 1 M PMSF stock solution was prepared by dissolving 1.742 g of PMSF powder in 10 mL of dimethyl sulfoxide (DMSO) and stored at −20 °C. ## 2.2. Preparation of Biosynthesized AgNPs and Functionalization with LTF AgNPs were synthesized according to a previously reported method [53]. Briefly, 5 mL of water extract of tiger milk mushroom (WETMM) (0.1 mg/mL) was mixed with 1 mL of 0.01 M silver nitrate solution ($0.017\%$ w/v) and 5 mL of CS solution ($0.09\%$ w/v). The reaction was performed at room temperature (RT) and left to stand until the yellow color turned reddish brown (the target color), indicating the formation of AgNPs. The mixture was sonicated for 20 min, followed by stirring at 300 rpm for 30 min. The resulting mixture was washed three times with deionized water by centrifugation (15,000 rotations per minute (rpm) for 15 min) to remove excess unreacted reactants. Formed AgNPs were re-suspended in 5 mL of distilled water and incubated with 5 mL of LTF solution to produce AgLTF complex at various concentrations (Ag/LTF concentration: $\frac{1000}{2000}$, $\frac{500}{1000}$, $\frac{250}{500}$, $\frac{125}{250}$, and $\frac{62.5}{125}$ µg/mL). The formation of the AgLTF complex was analyzed using a UV-vis spectrophotometer (Shimadzu 180, Centurion Scientific, New Delhi, India). The scan range was 200–500 nm at a 480 nm/min scan speed. Biosynthesized AgLTFs were kept at −80 °C for three days before lyophilization. Then, AgLTF was freeze-dried in a freeze dryer (ScanVac CoolSafe, Labogene, Lillerød, Denmark) at −110 °C for 24 h, and the lyophilized samples were viewed under a transmission electron microscope (TEM) at different magnifications (Philips, CM12, CA, USA). ## 2.3. FTIR Analysis Samples for Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR) were prepared by suspending lyophilized AgLTF and LTF in distilled water. Then, a few drops of the samples were placed on the ATR crystal. FTIR-ATR analysis of AgLTF and LTF was conducted in the range of 4000–400 cm−1 using an FTIR spectrophotometer (Perkin Elmer 100 Spectrum, Walthman, MA, USA). The spectra were acquired using 32 scans and a 4 cm−1 resolution. ## 2.4. X-ray Diffraction Analysis X-ray diffraction (XRD) patterns were recorded using a D8 Advance X-ray diffractometer (Bruker, Rheinstetten, Germany) equipped with a high-speed energy-dispersive LYNXEYE XE-T detector to characterize the structure and crystallinity of LTF, AgNPs, and AgLTF. Before analysis, the samples were prepared via lyophilization and kept in an airtight container. ## 2.5. DsiRNA Adsorption to AgLTF Similarly, 1 mL of various concentrations of AgLTF suspensions (125 µg/mL) was added to 1 mL DsiRNA against PGT gene solution (0.015 µg/mL), and the mixture was incubated at RT for 30 min to produce AgLTF-DsiRNA. ## 2.6. Particle Size, Polydispersity Index (PDI), and Zeta Potential The mean particle size, polydispersity index (PDI), and zeta potential (surface charge) of prepared biosynthesized AgNPs, AgLTF, and AgLTF-DsiRNA were determined using a Malvern Zetasizer Nano ZS (Malvern Instruments, Worcestershire, UK). All measurements for particle size were performed at 25 °C with a detection angle of 90°. Samples were measured in triplicate, and the data were presented as the mean ± standard deviation. ## 2.7. DsiRNA Entrapment and Binding Efficiency The entrapment efficiency (EE) of DsiRNA complexed with AgLTF was measured using a UV-vis spectrophotometer. The samples were centrifuged at 10,000 rpm for 30 min, and the absorbance of the supernatant recovered from centrifugation was measured at 260 nm and scanned at 480 mm/min. The following Equation [1] was used to calculate DsiRNA EE [39]:[1]DsiRNA EE %=DsiRNA added OD260 nm−DsiRNA in supernatant OD260 nmDsiRNA added OD260 nm · 100 The binding efficiency (BE) test was conducted using the electrophoresis method. Agarose gel $5\%$ was prepared in a 60 mL TAE buffer with 2 µL of red gel stain (Vivantis, Shah Alam, Malaysia). Samples were prepared by mixing dye with samples at a 1:5 ratio. Samples (10 µL) containing different concentrations of AgLTF with DsiRNA were then loaded into the wells prior to electrophoresis. Each sample contained 56 ng of RNA. Naked DsiRNA was used as the positive control, blank gel as the negative control, and a 10 bp DNA ladder (Invitrogen, MA, USA) as a size reference. The gel was run at 70 V for 45 min. The migration of the RNA in the agarose gel was captured and viewed under the ChemiDoc XRS+ System (Bio-Rad Laboratories, Hercules, CA, USA) using Image Lab software. ## 2.8. Preparation of the Hydrogel Two kinds of hydrogels were prepared in this study: a simple single-layered (SL) hydrogel and a double-layered (DL) hydrogel consisting of different complexes (AgNPs-DsiRNA and AgLTF) in each layer. DL hydrogels were proposed as a means of modulation and prolonged release of DsiRNA in the upper layer. The hydrogel was prepared using a method and formula reported previously with slight modifications [54]. Briefly, in a DL hydrogel, 5.7 mL AgLTF suspensions were mixed with 180 mg of gelatin to make $3\%$ w/v gelatin as a hydrogel base and were left on a hot plate at 40 °C for 30 min until the powders were fully dissolved [54]. Then, 0.3 mL genipin solution ($0.005\%$ w/v) was added to the mixture to make a total volume of 6 mL of gel. The cross-linking process was left for 24 h at RT until the gel was fully manifested to form the first or lower layer of DL hydrogel. Similarly, pre-incubated AgNPs-DsiRNA was mixed with gelatin ($3\%$ w/v) and genipin of various concentrations (0.005, 0.01, 0.02, and $0.04\%$ w/v) to make up a 6 mL volume of the hydrogel. After fully dissolved gelatin powder, the mixture was poured onto the first layer of gel to form the second or upper layer of the DL hydrogel. As for SL hydrogel, 5.7 mL pre-incubated AgLTF-DsiRNA was mixed with gelatin ($3\%$ w/v) and genipin ($0.005\%$ w/v) at 40 °C for 30 min until the gelatin powder was dissolved fully. The mixture was left for 24 h for the cross-linking process to complete. Then, the formed gels’ visual appearance, texture, smoothness, and stickiness were evaluated. DL and SL gels were also inverted and inclined for 1 h to observe their adhesion. ## 2.9. Morphological Observation Scanning electron microscope (SEM) imaging of hydrogels was taken using Merlin at magnification 500–1000× (Zeiss, Wetzlar, Germany) to observe 3-dimensional (3D) microporous structures of the hydrogels. The prepared hydrogels were kept at −80 °C in a freezer for 3 days and were lyophilized at −110 °C for 24 h using a freeze dryer before analysis. ## 2.10. Swelling Capacity The swelling behavior of the hydrogels was studied to determine their maximum hydration capacity. First, the hydrogels were freeze-dried for 24 h prior to the test. The swelling capacity (Is, %) of gelatin hydrogels was measured by weighing approximately 100 mg of dried sample (Wd) followed by immersion in 50 mL of phosphate buffer saline (PBS) with pH 7.4 at RT. The hydrogels were then superficially dried using filter paper, and the wet weight (Ww) was taken every 30 min up to 5 h and at 24 h. Is % was calculated using Equation [2] below [55]:[2]Is %=Ww−WdWd. 100 ## 2.11. In Vitro Drug Release of Active Agents In vitro release of AgNPs, LTF, and DsiRNA from the hydrogels was determined using Franz diffusion cells (PermeGear Inc, Hellertown, PA, USA). Cellulose acetate (Sartorius Stedim Biotech, Göttingen, Germany) with a pore size of 0.45 µm was used as the membrane, which was fixed between the donor and the receptor chamber. The diffusion area of the orifice between the donor and receptor chamber was 0.7855 cm2. The receptor chamber was filled with 5 mL PBS (pH 7.4 and 8.0) and maintained at 37 ± 2 °C throughout the process. A magnetic stirring bar was also added to the receptor chamber containing PBS to preserve the homogeneity of the system. Hydrogel samples (1 mL) were then directly inserted into the donor chamber and allowed to flow until the gels settled on the membrane. As for DL hydrogels, they were directly placed on the membrane without the donor chamber to maintain their integrity and shape to accurately represent the release profile of active agents from the respective upper and lower layers. Sampling was done by drawing 0.5 mL of PBS in the receptor chamber via a sampling port at predetermined time points (1, 2, 3, 4, 5, 6, 7, 8, 24, 48, and 72 h). Then, 0.5 mL of the drawn sample was immediately replenished with the same volume of fresh PBS. The absorbance of the samples was analyzed using a UV-vis spectrophotometer at 260 nm for DsiRNA, 280 nm for LTF, and 430 nm for AgNPs. Each active component’s percentage drug release (%) was plotted against time (h). As for DsiRNA, the percentage of drug release (%) was adjusted based on the average EE calculated. ## 2.12.1. Inoculum Preparation by Growth Method S. aureus (ATCC 25923), E. coli (ATCC 25927), and P. aeruginosa (ATCC 27853) were cultured on agar plates containing MHA using the streak method and then incubated (Memmert, Büchenbach, Germany) for 18 h at 37 °C. Inocula were prepared by transferring 3–5 colonies into a universal bottle containing 5 mL of MHB using a sterile loop. The bacterial suspension was incubated overnight to allow bacterial growth. After 18 h, the turbidity was adjusted using a UV-vis spectrophotometer to an absorbance of 0.08–0.10 at 625 nm by adding sterile broth to obtain a standardized microbial suspension of 1 × 108 CFU/mL for all bacterial strains. ## 2.12.2. Microbroth Dilution Method The minimum inhibitory concentration (MIC) value of AgLTF against the selected pathogens was determined using the microbroth dilution method [56,57]. Serial dilutions were performed from a starting concentration of 1000 to 2 µg/mL using MHB as a diluent. Each dilution reduced the concentration by two-fold. Then, a 1 × 108 CFU/mL bacterial suspension was prepared by adjusting the overnight (18 h) bacterial cultures using a UV-vis spectrophotometer. The bacterial suspension was then diluted with MHB at a 1:100 ratio to obtain approximately 1 × 106 CFU/mL. Subsequently, 100 µL of each type of bacterial strain was dispensed into each well of a 96-well plate containing 100 µL of treatment samples to give a final bacterial concentration of 5 × 105 CFU/mL. Finally, the plates were incubated at 37 °C for 18 h. Then, the plates were stained using 20 µL triphenyl tetrazolium chloride (TTC) reagent ($0.2\%$ w/v), and the results were obtained by observing the presence of a red formazan color. The lowest concentration at which no visible growth (no formation of red color) occurred was noted as the MIC value of the samples. ## 2.12.3. Agar Well Diffusion Test The antimicrobial properties of AgLTF (1000 and 125 µg/mL) and LTF (125, 250, 500, and 1000 µg/mL) were determined using the agar well diffusion method. The test protocols of this study were taken from a method reported previously with some modifications [57]. Adjusted bacterial suspensions with a concentration of 1 × 108 CFU/mL for all three bacterial strain cultures were prepared and spread on the surface of MHA by using a sterile cotton swab. The agar surface was swabbed uniformly with the bacterial suspensions by rotating several times and pressing firmly to cover the entire agar, including its rim. Four wells were created on the agar plate using a sterile 6 mm diameter pipette tip. Ciprofloxacin HCl (20 µg/mL solution) and distilled water were used as the positive and negative controls, respectively. Approximately 40 µL of AgLTF was loaded into different wells using a micropipette for sample testing. The plates were incubated at 37 °C for 18 h. The diameter of the inhibition zones was measured using a plastic ruler. The measurements were made in triplicate. ## 2.12.4. Disk Diffusion Method The disk diffusion test was used to evaluate the antimicrobial properties of the prepared hydrogels. Similar concentrations of bacterial suspensions (1 × 108 CFU/mL) were uniformly spread onto the surface of MHA on agar plates. Filter papers (particle retention 11 µm) were cut into small disks with dimensions of 6 mm diameter and 180 µm thickness. Disk-shaped filter papers were then placed aseptically onto the agar. DL and SL hydrogels (70 µL) were carefully transferred on the disks using a sterile spatula and incubated at 37 °C for 18 h. A blank gel containing only gelatin ($3\%$ w/v) and genipin ($0.005\%$ w/v) in distilled water was used as the negative control, and Ciprofloxacin disk (5 µg) was used as the positive control. The assay was conducted in triplicate. ## 2.13. Anti-Biofilm Potential The anti-biofilm properties of the respective active agents were evaluated using the crystal violet assay by measuring biofilm inhibition [58]. First, a standardized bacterial suspension was acquired by spectrophotometrically adjusting the absorbance at 560 nm to 0.02. One hundred microliters of each culture was transferred to the wells of a flat-bottomed 96-well plate and incubated for 24 h without shaking for biofilm formation. Then, 100 µL of solutions containing AgLTF (Ag/LTF: $\frac{1000}{2000}$, $\frac{500}{1000}$, $\frac{250}{500}$, $\frac{125}{250}$, $\frac{6.25}{125}$, and $\frac{32}{62.5}$ µg/mL) and LTF (2000, 1000, 500, 250, 125, and 62.5 µg/mL) at six different concentrations were added to the wells and further incubated at 37 °C for 24 h. Sterile distilled water was used as the negative control. After the second incubation, the 96-well plates were washed three times with distilled water and dried in an oven at 40 °C for 45 min. Then, 100 µL of $1\%$ crystal violet solution was added to the wells and incubated at RT for 15 min. Then, the plates were re-washed three times with distilled water to remove the excess purple stain of crystal violet. Biofilms were then observed as a thin layer of purple gel-like films attached to the side and bottom of the wells. Subsequently, 150 µL of ethanol was added to destain the wells. Finally, a 100 µL aliquot of the destaining solution from each well was transferred to a new plate. As for the hydrogel samples, a similar method was used, except that the crystal violet assay was conducted in a 6-well plate to accommodate the gels. One milliliter of bacterial cultures were added to their assigned wells and incubated until the biofilm formed. After the first incubation, the MHB media containing the bacterial cultures were replaced with 1 mL of fresh MHB containing AgNPs, SL, and DL hydrogels (approximately 1 mL of gel volume). The plates were incubated for another 24 h. The wells were then washed, dried, and stained with a crystal violet solution. The plates were re-washed and destained with 1 mL ethanol. One milliliter of the destaining solution from each well was also transferred to a new plate for further evaluation. The absorbance of all samples was recorded at 590 nm using a microplate reader (Thermo Scientific Multiskan GO, Thermo Fisher Scientific, MA, USA). The mean absorbance for each sample was determined, and the percentage of biofilm inhibition was calculated using Equation [3] below [59]:[3]Biofilm inhibition %=Control OD590nm−Treatment OD590nmControl OD590nm · 100 After the assay, unstained biofilms (post-treatment) were collected and dispersed in 5 mL of MHB using an ultrasonicator for 15 min at 40 Hz. 0.1 mL of dispersed biofilms were diluted in 9.9 mL of MHB (1:10 ratio) and spread uniformly onto a dried agar surface using a sterile loop. Diluted suspensions were plated on the MHA and incubated for 24 h before calculating the CFU. ## 2.14.1. Cell Viability Determination The AB cell viability assay reagent was used in this test. HaCaT cells (1.0 × 104 cells/well) were seeded in a 96-well plate containing 100 µL of DMEM and incubated for 24 h until they reached $50\%$ confluency. All cells were maintained in an incubator at 37 °C in a humidified $5\%$ CO2/$95\%$ air atmosphere. After the 24 h incubation period, the cells were treated with 20 µL SL containing various concentrations of AgNPs (125, 250, and 500 µg/mL), LTF (250, 500, and 1000 µg/mL), and DsiRNA (15, 30, and 60 ng/mL). A blank media without cells was used as the negative control, whereas untreated cells in DMEM were used as the positive control. Then, 12 µL of AB reagent ($10\%$ of the volume in the well) was aseptically added to the wells, and the cells were further incubated for 72 h. The absorbance of each sample at 570 and 600 nm was measured spectrophotometrically using a microplate reader (Biotek PowerWave XS, Marshall Scientific, NH, USA) at 24, 48, and 72 h. The number of viable cells was expressed as a percentage of AB reduction. The percentage of AB reduction (AB reduction %) was determined using Equation [4] below [60]:[4]AB reduction %=ℇoxℷ2Aℷ1−ℇoxℷ1Aℷ2ℇredℷ1A′ℷ2−ℇredℷ2A′ℷ1 · 100 In the formula, ℇℷ1 and ℇℷ2 are constants representing the molar extinction coefficient of AB at 570 and 600 nm, respectively, in the oxidized (ℇ ox) and reduced (ℇ red) forms. The constant values are 117,216 (ℇoxℷ2), 80,586 (ℇoxℷ1), 155,677 (ℇredℷ1), and 14,652 (ℇredℷ2). Aℷ1 and Aℷ2 represent the absorbance of the test wells at 570 and 600 nm, respectively. A′ℷ1 and A′ℷ2 represent the absorbance of the negative control wells at 570 and 600 nm, respectively. The values of AB reduction % were corrected for background values of negative controls containing medium without cells. ## 2.14.2. Cell Migration Assay Before testing, HaCaT cells were cultured in low glucose DMEM ($10\%$ FBS) in T75 flasks until full confluency was reached. The treatment groups were split between cells exposed to low and high glucose. In the low glucose treatment group, cells were seeded in 6-well plates (4.0 × 105 cells/well) in low glucose DMEM and pre-incubated until 90–$95\%$ confluency was reached. As for the high glucose treatment group, cells were seeded (5.0 × 105 cells/well) similarly, except that high glucose DMEM was pre-incubated for 48 h prior to the assay. Subsequently, a monolayer of cells formed was washed with PBS, and a scratch was made using a sterile 200 µL micropipette tip at a predetermined line in each well. PBS was then replaced with fresh low and high glucose DMEM ($1\%$ FBS) according to their treatment groups to remove cell debris. Two milliliter hydrogels (blank, AgNPs, AgLTF, SL, and DL) were placed in a cell strainer with a pore size of 70 µm and slowly added into each well containing 2 mL media (1:1 ratio). Growth media (DMEM) without hydrogel was used as a control. Finally, the cells were incubated further for another 72 h. The cell migration was viewed under an inverted phase contrast microscope (Olympus CK30, Tokyo, Japan) connected to a digital camera (Xcam-α) using DigiAcquis version 2.0 software (Matrix Optics, Petaling Jaya, Malaysia). Images of cells within the scratch area were taken at 0, 24, 48, and 72 h. The migration rate (%) is calculated using Equation [5] below [61]:[5]Migration rate %=A0 Initial scratch distance−At Remaining scratch distance at time tA0 · 100 ## 2.14.3. Measurements of PGE2 Protein in HaCaT Cells Protein was extracted from the cells after 72 h of treatment by scraping the cells in a cold RIPA buffer-PMSF ($\frac{500}{0.5}$ µL per well) cocktail. Scraped cells in each well were aspirated into centrifuge tubes and placed in an ice-filled container for 30 min to 1 h to start the cell lysis process. The tubes were intermittently shaken every 5 min using a vortex instrument to ensure that the cell lysate was homogenized during lysis. Then, the tubes were centrifuged at 10,000 rpm and 4 °C for 10 min. The supernatant was pipetted into an Eppendorf tube and stored in a −80 °C freezer until the assay. PGE2 levels were measured using an ELISA kit (FineTest, Wuhan, China). Briefly, 50 µL of standard dilution buffer (blank), standard, and sample solutions were added to the assigned wells. Then, 50 µL of biotin-labeled antibody working solution was added to each well and incubated for 45 min at 37 °C. After 45 min of incubation, the plate was washed 3 times with wash buffer. Then, 100 µL of horseradish peroxidase (HRP)-streptavidin conjugate working solution was added to the wells, followed by incubation for 30 min at 37 °C. Once incubated, the plate was re-washed 5 times, and 90 µL of 3,3′,5,5′-tetramethylbenzidine substrate, the substrate for HRP, was added to each well. The plate was then incubated in the dark at 37 °C for 20 min until a notable color change to pale blue was observed in each well. Lastly, 50 µL of stop solution was added to all the wells, and the color turned yellow immediately. The absorbance of each sample at 450 nm was measured spectrophotometrically using a microplate reader. The target concentrations of the samples were interpolated from the standard curve. ## 2.15. Statistical Analysis The data acquired are presented as the mean ± standard deviation. The data were analyzed by one-way ANOVA followed by Tukey’s post-hoc test. Analyses were computed using jamovi. Values of $p \leq 0.05$ were considered to indicate a statistically significant difference between the samples tested. ## 3.1. Formation of AgLTF AgNPs were formed after 3 days using WETMM as a reducing agent. A gradual color change from colorless to pale yellow and finally to brownish red indicated the formation of an AgNP suspension due to the biomolecules contained in WETMM that facilitated the conversion of Ag+ from AgNO3 to Ag0 (Figure 1A) [62]. After successful conversion into AgNPs, CS played a crucial role in stabilizing the AgNPs from an agglomerated state by forming a monolayer around the AgNPs [53]. Incubation between AgNPs and LTF to form AgLTF did not show any color changes of brownish-red AgNPs, as well as their lyophilized form (Figure 1B); hence, other tests were used to identify the presence and interactions between the two components. UV-vis spectrophotometry was used as a primary analysis to detect the formation of NPs due to the intense surface Plasmon resonance and LTF (Figure 1C) [7]. The typical Plasmon resonance band can confirm the formation of AgNPs at 445 nm, corroborating another publication using an extract of edible mushrooms as a reducing agent [63]. A small peak at the 270–300 nm area indicates the presence of LTF in the AgLTF complex [54]. When viewed under TEM, AgLTF complexes were seen to be well dispersed (PDI 0.271) particles and have an average size of 20.50 nm ± 5.56 (Figure 1D). The high presence of primary amines in CS (75–$85\%$ deacetylation degree) contributes to the overall positive charge of CS monolayers around AgNPs, which causes a stabilization effect by repelling against each other [64]. Consequently, this minimizes AgNP particles from agglomerating into larger sizes. In addition, positive charges from the primary amines of CS also allow for anionic molecules to form complexes [65]. AgNPs and LTF were presumably complexed via electrostatic interaction between the anionic thiol groups of LTF and cationic amine groups of CS. AgLTF appeared in doublet form (green circle), which could indicate the successful complexation of AgNPs and LTF. Some doublets were also seen grouped, probably due to the diminished stabilizing effect of CS since LTF occupied the primary amines on the chemical structure of CS. AgLTFs were generally spherical with some presence of cubes. Spherical AgNPs obtained through controlled thermodynamic conditions could offer advantages such as stability due to the minimum availability of surfaces [66]. ## 3.2. FTIR Analysis Interactions between AgNPs, WETMM (reducing agent), and CS were established using FTIR [53]. WETMM possessed free aldehyde groups that served as electron donors to reduce metal ions into Ag0, whereas CS molecules formed C-O-C bridges as a protective layer around AgNPs to prevent aggregation of NPs [67]. In this study, LTF was complexed with AgNPs, and the interactions between the functional groups of these components were examined (Figure 2). LTF was individually presented with a broad band at 3317.9 cm−1, representing aromatic C-H compounds and O-H stretching. LTF has large amine groups in its chemical structure, which usually appear around 3300 cm−1. Primary amine (RNH2) groups typically form a band with two sharp spikes on IR spectra; however, it is overshadowed by the dominant (four times more in abundance) secondary amine (R2NH), forming a broad band around the 3300 cm−1 area. The sharp band at 1633.7 cm−1 represents C=O stretching from the amide and ring C=C vibrations from benzene. The small band at 1284.3 cm−1 could also be due to the primary and secondary amide groups. As for the spectrum of AgLTF, there were mainly overlapping absorption bands from AgNPs and LTF. The strong band at 3314.2 cm−1 represents the aromatic C-H compounds from the aromatic hydrocarbons and O-H stretching from the primary amines, primary hydroxyl, and secondary hydroxyl groups. The band at 1644.7 cm−1 corresponds to C=C stretching from the ring structure, whereas the subdued 1284.3 cm−1 band corresponds to C-O-C bending within the ring structure, and the C-O-C bridges formed during the stabilization process. There were no changes in the functional groups in AgLTF after LTF was incorporated into the AgNPs. This suggests that the complexation between AgNPs and LTF was held together by weak non-covalent electrostatic interactions. ## 3.3. X-ray Diffraction Analysis XRD analyses were incorporated in this study to confirm the crystalline nature of AgLTF [7]. Figure 3A shows two broad humps without sharp diffraction peaks at 2 theta 9.64° and 20.99°, indicating characteristic XRD patterns for pure protein in amorphous forms [68,69,70]. On the other hand, CS from the AgNPs spectrum has a linear semi-crystalline structure with sharp peaks at 2 theta 12.79° from the [020] planes and 21.88° from the [110] planes of ordered crystalline units (Figure 3B) [71]. Tall peaks at 2 theta 31.14° and 35.54° represent the crystallization of the bio-organic phase occurring on the surface of the AgNPs [72]. The presence of subdued peaks at 39.09°, 46.35°, 62.52°, and 76.77° indicates that AgNPs are face-centered cubic and crystalline in nature [73,74], consistent with those found in the Joint Committee on Powder Diffraction Standards database. The relative intensity of these peaks is due to the ratio of CS and AgNPs being used to formulate the stabilized AgNPs, which was supported by the wide scan XPS spectrum, which revealed the atomic percentages of O, C, N, and Ag to be $34.64\%$, $57.88\%$, $4.92\%$, and $2.56\%$, respectively [53]. In Figure 3C, the two peaks at 2 theta 9.64° and 20.99° that were present in the LTF spectrum became very weak once they complexed with AgNPs due to the crystal formation of the product via freeze-drying during the drying process [75]. The characteristic peaks of CS were also significantly decreased as a result of the complexation process with LTF due to its excellent sorption ability [76]. The highly deacetylated structure and low molecular weight of CS allow for the adsorption of hydrophilic moieties of LTF onto the hydroxyl and amine groups of CS [77]. The characteristic peaks for AgNPs were shifted, probably because of the change in AgNPs (stabilized by CS) structure geometry due to interaction or complexation with LTF [78]. More importantly, the peaks at 2 theta 38.00°, 46.08°, 64.43°, and 76.57° together with their relative intensity can be assigned to the planes of [111], [200], [220], and [311], which show the crystalline structure of AgLTF [73,74]. ## 3.4. DsiRNA Adsorption to AgLTF The binding of DsiRNA to AgLTF was achieved via simple complexation. As shown in Table 1, AgNPs have a high zeta potential of +31.7 ± 4.8 mV, primarily due to the protonated amino groups in CS. LTF has a molecular size of 80 kDa, whereas DsiRNA has a molecular size of 16 kDa. When AgNPs were complexed with LTF and DsiRNA, the particle sizes progressively increased from 58.4 ± 6.3 nm to 113.3 ± 25.0 nm and finally to 157.4 ± 5.0 nm, which could indicate successful complexation between the compounds. The zeta potential was also decreased from +31.7 ± 4.8 mV to +18.3 ± 1.5 mV and further reduced to +16.3 ± 12.3 mV, probably due to the occupation of cationic amine groups of CS with anionic groups of LTF and later with DsiRNA. The low PDI of AgLTF and AgLTF-DsiRNA showed that they were homogenous and moderately dispersed [79]. EE was measured to determine the DsiRNA carrying efficiency of AgNPs and AgLTF [80]. According to Table 2, two concentrations (500 and 125 µg/mL) of AgLTF and AgNPs were able to load with DsiRNA at moderate EE levels [$72\%$ and $70\%$ for 500 and 125 µg/mL, respectively, and they were not statistically significant ($p \leq 0.05$, $F = 0.934$)], which corroborates the previous finding that different concentrations of gold nanoparticles (AuNPs) did not affect the entrapment capacity of DsiRNA [35]. In fact, increasing the concentration of the carrier molecule might have a negative effect on EE [39,80]. AgLTF and AgNPs-DsiRNA only achieved 70–$72\%$ EE, probably due to the shielding effects and steric hindrance, which interfered with the interaction between negatively charged DsiRNA molecules and positively charged amine groups of CS [39]. The gel electrophoresis method with $5\%$ agarose and red gel staining was used to analyze the DsiRNA binding efficiency to AgLTF. The black trailing bands in Figure 4 represent the DNA being electrophoresed along the agarose gel. Generally, the heavier the molecule, the shorter the distance it travels. On this basis, the column DNA Ladder highlights the position of DNA with different molecular weights based on its number of base pairs. With this as a reference, the naked DsiRNA against the PGT gene (27 base pairs) acted as the positive control and traveled to the position between 20 to 30 bp DNA, whereas blank gel (without DsiRNA) served as the negative control. Hydrogel samples loaded with various concentrations of AgLTF and AgNPs (500 and 125 µg/mL) and 15 ng/mL DsiRNA showed no trailing bands of DsiRNA after being electrophoresed, which demonstrated that there was strong binding between DsiRNA and AgLTF and AgNPs. These findings indicate that AgNPs could be complexed and carry sufficient DsiRNA to the wound site. Moreover, DsiRNA carried by AgNPs (stabilized by CS) was reportedly more likely to be taken up by cells through the endocytosis process due to the electrostatic interaction of CS with cellular membranes [81]. ## 3.5. Formation of the Hydrogel After 24 h incubation, the pale brownish color of the nanocomposites and gel polymer mixture turned dark blue, indicating successful gelation (Figure 5A). A blue-colored SL hydrogel was obtained when removed from the beaker (Figure 5B). As for DL hydrogel, when it was extracted, a clear separation between the upper and bottom layers containing two different complexes of active components was observed (Figure 5B). The extracted hydrogel had a consistent dimension of 0.4 cm height (0.2 cm height for each layer), with each layer holding a 6 mL volume. Gel was constructed in such a way because sequentially treating infected wounds in each critical stage of the wound healing process resulted in a better healing effect [51]. Usually, when a skin layer is damaged, inflammation starts immediately and can last for a week, whereas proliferation only occurs from day 2 up to day 10 [51]. Hence, AgNPs-DsiRNA was compartmentalized in the upper layer to achieve delayed and slow release from the hydrogel to synchronize with the biological angiogenesis process, preceded by immediate release of AgLTF in the bottom layer for fast eradication of biofilm-producing pathogens during the inflammation stage. ## 3.6. Characterization of the Hydrogel According to Table 3, all of the hydrogels formed using various concentrations of genipin (0.005, 0.01, 0.02, and $0.04\%$ w/v) displayed mostly similar physical characteristics, except for the lowest genipin concentration ($0.005\%$ w/v). Hydrogels consisting of genipin $0.005\%$ w/v in the upper layer were bouncy on touch, in contrast to the other hydrogels with higher concentrations of genipin, forming rigid and very sticky hydrogels. This supports the previous finding that the viscoelasticity of hydrogel can be adjusted by varying the crosslinker concentration [54]. As the genipin concentration increases, the tensile strength of the hydrogel increases. Sufficient hardness is often needed to withstand handling during packaging and administration without disrupting the integrity of the gel. However, excessive hardness and stickiness may cause undesirable effects, as removing the gels from the glass beakers and cutting them into smaller pieces would be more challenging. In addition to having a rigid structure, many samples were wasted while handling hydrogels with genipin concentrations higher than $0.005\%$ w/v (0.01, 0.02, and $0.04\%$ w/v). Thus, genipin $0.005\%$ w/v in the upper layer of the DL gel was selected for further tests. SEM micrographs showed interlinking chains between gelatin polymers, which created 3D microporous structures in the hydrogels. Gelatin is a polypeptide with high molecular weight and many functional groups, so it can readily be crosslinked with [40]. A previous report showed that uncrosslinked gelatin ($3\%$ w/v) has an average pore size of 105 ± 22 µm [54]. In Figure 6A, gelatin ($3\%$ w/v) crosslinked with genipin ($0.005\%$ w/v) hydrogel appeared to have a 46.67 ± 10.33 µm pore size for the first layer. On the other hand, the second layer of hydrogel had an average pore size of 45.77 ± 11.00 µm, which was similar to the first layer, as they both had the same compositions of hydrogels. Smaller and more consistent pore sizes in crosslinked gelatin hydrogels are a result of the crosslinking effects of genipin. Genipin stabilizes and tightens the hydrogel matrix, reducing the structure’s pore size and flexibility [63]. In SEM, genipin was seen to form interconnective chains between the gel polymers, increasing the mechanical properties and reducing the likelihood of collapsing in media (Figure 6A). Genipin is necessary to maintain the integral stability of gelatin, as uncrosslinked gelatin gels are not stable under physiological conditions (37 °C and pH 7.4) [48]. AgNPs, represented by the spheres in the image, can be seen dispersed within the gelatin polymers and outside the polymers along the interconnectivity chains of genipin. AgNPs can form nanoparticle–hydrogel hybrid systems using strong hydrophobic interactions [50,82]. Through this dynamic, AgNPs can further enhance the mechanical stability of the hydrogel in the matrix system. The swelling index over time graph demonstrated reduced swelling capacity in a 24-h window period when the genipin concentration in the second layer of hydrogel was increased (Figure 6C). SL hydrogel with $0.005\%$ w/v genipin achieved the highest swelling index ($1668\%$), whereas DL hydrogel with $0.04\%$ w/v genipin achieved the lowest swelling index ($1166\%$) due to the smaller pore sizes in hydrogels with higher concentrations of genipin, which restrained the capacity of gelatin peptide chains to undergo relaxation when water was absorbed. When swelling occurs, the hydrogel matrix expands. The expansion in hydrogel causes pore sizes to increase, facilitating the release of AgNPs from the hydrogel [63]. Thus, when the genipin concentration is increased, the hydrogel’s swelling capacity is reduced, which could potentially slow down the release of entrapped drugs. Hence, it is vital to strike a balance when finding a suitable concentration of crosslinker that provides gel stability and timely release of AgNPs. In this experiment, all prepared formulations exhibited excellent adhesive properties (Figure 6B). Adhesion is an important quality of hydrogels, especially in topical applications, so it remains intact with the skin throughout the treatment process. ## 3.7. In Vitro Drug Release of Active Agents Gelatin hydrogel follows the principle of swelling-controlled drug release [82]. When in contact with bio-fluid, the hydrogel expands beyond its limit and increases its pore size, facilitating the drug diffusion process along with polymer chain relaxation. In this case, AgNPs, LTF, and DsiRNA diffuse down the concentration gradient during swelling within the hydrogel matrix toward the injury site to exert their effects. The in vitro release profile of each active component was conducted using the Franz cell diffusion system. Many factors affect drug release from a hydrogel, such as pH, temperature, and ionic strength [82]. However, only the pH values of the media were varied (7.4 and 8.0) during the test to mimic the possible pH elevation of human skin tissue during infection [83]. Cellulose acetate membrane of 0.45 µm pore size was used for Franz cell diffusion, as it had been shown to be able to support a wide range of hydrophobic (LTF) and hydrophilic (AgNPs and DsiRNA) samples and applications [84]. *In* general, drug release behavior from gelatin hydrogels occurs in the following phases: a typical initial burst release followed by diffusion, combined diffusion and degradation, and finally, polymer degradation [40]. In SL hydrogel, burst release was displayed by the steep increase in drug release at the first hour to demonstrate the rapid release of AgNPs ($19.54\%$), LTF ($12.55\%$), and DsiRNA ($17.30\%$) from the hydrogel polymer matrix (Figure 7A). This was followed by a steady release of the actives until finally achieving $81.39\%$ for AgNPs, $82.99\%$ for LTF, and $87.52\%$ for DsiRNA at the 24 h time point. In a previous study, complete DsiRNA release from hydrogel using PF127 occurred within an 8 h window period [35]. At pH 8.0, all active ingredients in the hydrogel demonstrated slower and incomplete release of $52.77\%$ for AgNPs, $35.74\%$ for LTF, and $62.96\%$ for DsiRNA. Since gelatin polymers crosslinked with genipin were maintained in the gel form throughout the process, its charge groups were probably not disrupted to affect the drug release of entrapped components. However, the cationic nature of CS, which is responsible for enveloping AgNPs and forming complexes with LTF and DsiRNA, could be affected. In a higher pH medium, the basic amine groups of CS were not protonated. Thus, there were fewer positively charged ions to repel and cause swelling to facilitate drug release [85]. As for the DL hydrogel, the Franz cell diffusion study was extended up to 72 h (Figure 7B). During the first hour, AgNPs achieved $11.55\%$ drug release and $11.16\%$ and $16.54\%$ LTF and DsiRNA, respectively. The initial release of these components was reduced in the DL hydrogel compared to the SL hydrogel. However, they were not significantly different ($p \leq 0.05$, $F = 0.083$) as some AgNP-DsiRNA in the upper layer might have diffused into the bottom via pores during storage. At 24 h, only $44.98\%$ of AgNPs, $49.24\%$ of LTF, and $56.06\%$ of DsiRNA were released from the DL hydrogel and finally achieved $62.31\%$ (AgNPs), $71.52\%$ (LTF), and $73.38\%$ (DsiRNA) at 72 h ($p \leq 0.05$). The drug release profiles of different components (AgNPs and DsiRNA) in DL hydrogel were significantly different from the SL counterpart, except for the release profile of LTF in these formulations, due to the hydrophobic nature of LTF diffusing across a hydrophilic cellulose acetate membrane in the Franz cell diffusion system [86]. Hydrophobic compounds typically have a concave-up drug diffusion pattern across various synthetic membranes, with a slow diffusion at the starting point, which accelerates over time [87]. Compared to DsiRNA, at 72 h, LTF release was a total of $86.14\%$, which is higher than $73.38\%$ for DsiRNA despite the slow start within 24 h ($49.24\%$ for LTF vs. $56.06\%$ for DsiRNA) of the diffusion process. Hence, there was no significant difference in the release profiles for LTF in DL and SL hydrogel because of the compound’s physicochemical properties and the membrane used [87]. Although only DsiRNA was intended to have a prolonged release in the DL hydrogel, AgNPs and LTF were also impacted, probably due to the equilibrium process in the first and second layers of the DL hydrogel. ## 3.8. Antibacterial Activity In this study, microbroth dilution and agar well diffusion methods were employed to determine the antibacterial effects of AgLTF in solution, while the disk diffusion assay was for the gel form. SL and DL gels were tested against the three most common bacterial pathogens found in diabetic wounds or foot infections: S. aureus, P. aeruginosa, and E. coli [88]. In the microbroth dilution method using gels containing AgLTF, starting from concentrations 1000 to 2 µg/mL, all three tested organisms had red formazan stains in the wells containing 62.5 µg/mL AgLTF and lower (Figure 8). This indicated that the MIC value of AgLTF was 125 µg/mL, which is consistent with the biosynthesized AgLTF reported elsewhere [54]. The antibacterial efficacy of AgNPs is well established, and the mechanisms by which AgNPs exert their effects are diverse. In the nanoparticle state, AgNPs can accumulate in the pits or edges on the bacteria’s cell wall after they anchor to the cell surface and cause cell membrane denaturation [89], preceded by penetration into bacterial cells due to their small size and damaged organelles [11]. In addition, AgNPs can also release Ag+, the killer for microbes. Ag+ has an electrostatic affinity toward the cell wall and cytoplasmic membrane, disrupting the bacterial envelope. When Ag+ enters the cell, respiratory enzymes can be deactivated due to their electrostatic interaction with thiol groups and cause the generation of reactive oxygen species. Additionally, Ag+ can also prevent the synthesis of proteins by denaturing ribosomes in the cytoplasm [11]. The efficacy of AgNPs as antibacterial agents also depends on their morphology. AgNP crystals are more likely to attach to the surface of the cell membrane due to their reactive [111] facets [90]. Spherical and smaller AgNPs are also prone to release more Ag+ for their toxic effects against bacterial pathogens [11]. Agar well diffusion was conducted to investigate the antibacterial properties of AgLTF and LTF alone. Zones of inhibition from this assay are presented in Table 4. AgLTF at a concentration of 125 µg/mL formed the biggest zone of inhibition against E. coli (11.3 ± 7.5 mm), followed by S. aureus (10.3 ± 1.5 mm) and P. aeruginosa (7.3 ± 0.6 mm) ($p \leq 0.05$). AgNPs have more activity against Gram-negative bacteria due to the thin layer of peptidoglycan (PG) cell wall and the presence of lipopolysaccharides (LPS), which makes it easier for positively charged CS and Ag+ to bind to [27]. However, inhibition zones against P. aeruginosa were lower than both E. coli and S. aureus because they are more resistant to AgNPs [90]. When the concentration of AgLTF was increased to 1000 µg/mL, the zones of inhibition were also increased to 13.3 ± 2.9 mm for E. coli, 11.3 ± 1.2 mm for S. aureus, and 9.3 ± 0.6 mm for P aeruginosa, which indicates that the antibacterial effect is dose-dependent. Although recombinant human LTF derived from rice and human milk LTF were reported to have a broad spectrum of antibacterial effects [91,92], the LTF (1000, 500, 250, and 125 µg/mL) used in this study demonstrated nil antibacterial effects against E. coli, S. aureus, and P. aeruginosa. This finding is consistent with a previous report that LTF exerted no antibacterial effects against E. coli, S. aureus, Bacillus sp., and P. aeruginosa [27]. A disk diffusion assay was conducted to determine the antibacterial properties of AgLTF after it was formulated into a hydrogel. This method is preferred when assessing the antibacterial effects of hydrogels because it allows active components to diffuse from the gel matrix through a filter paper disk and disperse into agar, which better mimics a topical application onto the skin. In contrast, agar well diffusion was more suited to extract solutions [93]. SL gel demonstrated the highest activity against E. coli (13.3 ± 0.6 mm) and P. aeruginosa (13.3 ± 0.6 mm), followed by S. aureus (10.3 ± 1.5 mm). Similarly, DL gel also showed the highest activity against E. coli (15.0 ± 1.0 mm), followed by P. aeruginosa (14.7 ± 0.6 mm) and S. aureus (10.0 ± 1.7 mm). The difference between the antibacterial activity of SL and DL was insignificant ($p \leq 0.05$, $F = 1.93$). The results indicate that the main antibacterial component (AgNPs) was not impacted by the gel matrix and could diffuse through the agar and exert antibacterial effects. ## 3.9. Anti-Biofilm Potential This study employed a microtiter plate assay using crystal violet stain to quantitatively determine the anti-biofilm potential of SL and DL hydrogels containing AgLTF-DsiRNA. P. aeruginosa and S. aureus were selected as the test organisms, as they are known biofilm formers [22]. Previously, AgNPs were tested against these two microbes, and they showed inconsistent anti-biofilm activity [53]. Some of the higher doses of AgNPs were shown to have decreased anti-biofilm activity, partly due to the sub-bacteriostatic concentration of LMW CS ($0.09\%$ w/v), which might have triggered the stress response mechanism of the bacteria [94]. Furthermore, another study reported the pro-biofilm activity of certain antibiotics and NaCl when high doses were used due to the increased expression of polysaccharide intercellular adhesin, a component of the biofilm matrix [95]. Hence, this negative anti-biofilm effect might be a coping mechanism for bacteria to increase their survivability against these toxic agents. Much of the anti-biofilm effects were due to the nanoscale feature of AgNPs, which can easily penetrate the complicated architecture of biofilm [11]. However, findings from other reports have concluded that the anti-biofilm properties of AgNPs are ultimately inconclusive and strain-dependent [11,28,54]. In this study, LTF was incorporated with AgNPs to enhance the overall anti-biofilm effects of this complex. When tested against S. aureus, LTF in solution form demonstrated an increase in anti-biofilm activity from 47.43 ± $6.95\%$ at 62.5 µg/mL to 68.90 ± $16.01\%$ at 1000 µg/mL, with an exception for concentration 500 µg/mL where it displayed a dip (44.53 ± $22.62\%$) in anti-biofilm activity (Figure 9). A significant jump in biofilm inhibition % was observed when the concentration of LTF was increased from 125 µg/mL (47.43 ± $6.95\%$) to 250 µg/mL (65.11 ± $6.50\%$) ($p \leq 0.05$). The increase in activity from 250 µg/mL to 500 µg/mL (68.89 ± $15.62\%$) and 2000 µg/mL (68.90 ± $16.01\%$) was not significant ($p \leq 0.05$, $F = 1.55$). Interestingly, LTF at 125 and 250 µg/mL concentrations had higher anti-biofilm activity than the positive control ($p \leq 0.05$), highlighting the importance of using lower doses for AgNPs and LTF to avoid the negative or stress feedback mechanism of the bacteria. As for P. aeruginosa, the anti-biofilm activity of LTF was remarkably higher than the positive control at all concentrations (2000, 1000, 500, 250, and 125 µg/mL) ($p \leq 0.05$). LTF had the highest activity (76.54 ± $1.05\%$) at 250 µg/mL and the lowest activity (67.19 ± $3.39\%$) at 500 µg/mL. In a previous study, LTF was tested for its anti-biofilm effect against 25 different strains of Group B Streptococcus (GBS) [96]. LTF at 250 µg/mL decreased biofilm formation in 20 out of 25 strains of GBS and significantly inhibited biofilm formation in both high and low biofilm formers. On the other hand, LTF at 500 µg/mL decreased biofilm formation of 21 out of 25 strains of GBS, but only inhibited biofilm formation of the high biofilm formers. Similarly, LTF against S. aureus and P. aeruginosa in this study did not show a dose-dependent relationship with activity and had the most optimal effect at 250 µg/mL. The discrepancy between the activity against Gram-negative and Gram-positive bacteria is probably due to the different matrix types produced by the bacteria. P. aeruginosa is known to have a thick matrix composed mainly of polyanionic EPS. In contrast, S. aureus has EPS that is polycationic [97]. LTF and AgNPs (stabilized by CS) are highly cationic due to the abundant amine groups present in their structure, which could facilitate the attachment and penetration of these compounds into the EPS matrix of P. aeruginosa [32]. LTF is an iron-chelating protein that disrupts the iron regulation of the biochemical and metabolic functions of bacteria, which are essential for growth and development [98]. LTF can prevent lectin-dependent bacterial adhesion or motility to the surface via EPS synthesized by bacteria, which is the first step in biofilm formation [99]. In addition, LTF can exert direct effects by depriving the biofilm of iron nutrients and nullifying the scavenging system of biofilm to gather essential minerals and nutrients, as it can diffuse through the bacterial biofilm [32]. When AgNPs and LTF were combined to form AgLTF, the anti-biofilm activity was mostly enhanced compared to AgNPs alone. In a previous study, AgLTF showed the strongest anti-biofilm activity due to their synergism [27]. LTF has also been used with other agents, such as Xylitol, to further improve efficacy against biofilm-producing organisms [32]. Since AgNPs had an MIC value of 125 µg/mL against all three of the tested microbes in the antibacterial assay and LTF produced optimal anti-biofilm effects at 250 µg/mL, AgLTF complex containing 125 µg/mL of AgNPs and 250 µg/mL of LTF was selected for further testing. In the gel form, all three of the treatment groups (hydrogel containing AgNPs, SL, and DL) had higher biofilm inhibition against both P. aeruginosa and S. aureus than the blank gel ($p \leq 0.05$) (Figure 10). SL (51.53 ± $6.14\%$ against S. aureus and 60.88 ± $6.74\%$ against P. aeruginosa) and DL (69.94 ± $2.00\%$ against S. aureus and 79.94 ± $2.03\%$ against P. aeruginosa) produced higher anti-biofilm inhibition than gel containing AgNPs alone (33.82 ± $12.43\%$ against S. aureus and 37.06 ± $8.85\%$ against P. aeruginosa), showing the enhanced anti-biofilm effect of LTF and AgNPs. Interestingly, DL had a higher anti-biofilm effect than SL, prompting the question of the AgLTF release pattern’s role in biofilm inhibition. In contrast to the results obtained, a previous study that utilized usnic acid as an antibacterial and anti-biofilm agent in biodegradable polymers against S. aureus demonstrated better dual effects in polymers with a faster release profile [100]. When controlled release of plectasin NZ2114 loaded in a catheter matrix was tested against S. aureus biofilm, the highest antibacterial and anti-biofilm effects (highest CFU reduction) at day 1 were observed, with a significant drop in activity at day 7 [101]. Since the anti-biofilm assay was only run for 24 h (LTF release percentage was approximately $49\%$ in DL and $86\%$ in SL) and LTF displayed better activity at lower doses, this could be the reason for the higher biofilm inhibition in DL as compared to SL at the 24 h time point. Further investigation and a longer assay duration are warranted to confirm this anti-biofilm activity over time in AgLTF. ## 3.10. Cell Viability HaCaT cells, a keratinocyte cell line, were selected for in vitro cell viability and migration testing because keratinocytes and fibroblasts are the main components of granulation tissue. They are also the dominant cells involved in the wound closure mechanism [102]. The AB cell viability assay reagent was used to quantify cellular metabolic activity and thus determine the viable HaCaT cells when cultured with hydrogels containing three different concentrations of AgLTF-DsiRNA. AB cell viability reagent can also determine the proliferation rate of cell lines by measuring it at two or more time points in the sample. This test was chosen explicitly over the classical 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, as it is highly stable and non-toxic to the cells, which offers an advantage for continuous monitoring of cultures over time [60]. Mechanism-wise, AB utilizes an oxidation–reduction indicator that fluoresces and changes color due to the chemical reduction process during cell growth. The oxidized form of water-soluble AB dye is blue in color and non-fluorescent (non-viable), whereas the reduced form of AB dye is fluorescent red (viable). In this study, absorbance was measured at 24, 48, and 72 h to observe the viability and proliferation rate of HaCaT cells under the influence of the hydrogels tested. Figure 11 demonstrates the cytotoxic effects of AgLTF-DsiRNA hydrogels on HaCaT cells. SL125 denotes AgLTF-DsiRNA in SL gel containing 125 µg/mL AgNPs, 250 µg/mL LTF, and 0.015 µg/mL DsiRNA, whereas SL250 represents AgLTF-DsiRNA containing 250 µg/mL AgNPs, 500 µg/mL LTF, and 0.015 µg/mL DsiRNA and lastly SL500 refers to AgLTF-DsiRNA containing 500 µg/mL AgNPs, 1000 µg/mL LTF, and 0.015 µg/mL DsiRNA. At 24 h, all gels were comparable to the positive control in the range of AB reduction of 47.24–$53.33\%$ ($p \leq 0.05$). However, SL250 and SL500 were significantly lower in AB reduction compared to the positive control ($p \leq 0.05$) at 48 h and 72 h. Hence, SL125 remained non-cytotoxic throughout the assay. Many factors affect the cytotoxicity potential of AgNPs, such as their size, shape, surface chemistry, and cell type. However, in general, the cytotoxic effects are due to the oxidative stress caused by AgNPs and the release of Ag+. When internalized in cells, they can induce a series of effects, such as impairment of cell membrane, inflammatory response, DNA damage and genotoxicity, chromosome aberration, and apoptosis [103]. However, AgGO biosynthesized using flower extract of *Legistromia sepiosa* on a human embryonic kidney cell line (HEK-293) were non-toxic at an effective antibacterial concentration (94 µg/mL) [104]. Chemically synthesized AgNPs using NaBH4 with particle sizes lower than 20 nm were also reported to be safe at the highest tested concentration of 25 µg/mL as a topical agent when evaluated on HDFs and human epithelial keratinocytes for 24 h [105]. Although AgNPs are generally known for their toxic effects on human cells, they are safe when used at lower doses. In the current study, AgNPs were biologically synthesized using WETMM, thus avoiding the employment of toxic and harmful chemicals that may have lingered on the formed AgNPs. Additionally, AgNPs were coated with CS as a stabilizer, which could have also improved its overall safety profile by preventing any direct effects of AgNPs on the cells. Currently, no study has evaluated the cytotoxic effects of LTF on human skin cells. Still, when used in combination with AgNPs, it did not seem to significantly enhance its cytotoxicity. A study by Abdalla et al. [ 27] showed that AgLTF at concentrations (32, 62, and 125 µg/mL; 1:1 AgNPs to LTF ratio) was non-cytotoxic on human dermal fibroblasts (HDFs) for 48 h. However, cell viability determination using the AB test at 72 h showed a significant reduction in cell viability %, which may pose an issue in treatments requiring a longer duration. In a separate study, biosynthesized AgLTF using *Pleurotus ostreatus* (16–125 µg/mL) also showed characteristic dose and time-dependent cytotoxicity on HDFs over 72 h but were generally safe except for dose 125 µg/mL [54]. Although these reports exhibited the alarming cytotoxicity nature of AgLTF on HDFs at 125 µg/mL, it is essential to note that both studies used the extracted solution of AgLTF, which means that AgLTF was in direct contact with the cell cultures throughout the assay to exert its toxicity. This study formulated AgLTF-DsiRNA in hydrogel and further crosslinked it with genipin to allow a steady release of its active components over 24 h for SL and 72 h for DL, respectively, preventing the tested HaCaT from suffering from full-blown toxicity of AgLTF. ## 3.11. Cell Migration Wound healing requires the complex coordination of various cell types, including keratinocytes, fibroblasts, endothelial cells, macrophages, and platelets [106]. It mainly involves cell proliferation and migration. In particular, the migration of keratinocytes is essential for wound re-epithelialization associated with angiogenesis, and any defects in this process may hamper wound closure [102]. Two methods are generally used to evaluate the cell migration of HaCaT, namely wound scratch assay and transwell cell migration assay. The wound scratch assay is the most common in vitro method to test compounds for their migratory properties due to its simplicity and cost-effective procedure [107]. Additionally, the scratch assay is comparable to the in vivo wound healing process because it involves the removal of cells using a pipette tip, which wounds the monolayer and causes destroyed and activated cells [108]. In a comprehensive study done by Ueck et al. [ 2016] to validate the in vitro scratch assay as a replacement for the expensive in vivo wound healing assay using pig model systems, they discovered that supplemented media are important to allow hyperglycemic conditions to affect in vitro wound healing of keratinocytes, and preincubation of the model in high glucose medium for at least 48 h is necessary to enable the glucose to execute its effects before testing [108]. In addition, HaCaT cells have strong cell-to-cell interaction and are facilitated by Ca2+-dependent interactions at the desmosome junction. Hence, prior to the scratch, washing with PBS is an essential step to weaken the cell-to-cell adhesion of HaCaT for easy removal, eliminating one of the disadvantages of performing manual scratches, as the cells tend to accumulate across the edge of the scratch due to this strong interaction [107]. The in-house scratch assay confirmed that hyperglycemic conditions impaired the wound healing ability (Figure 12) when two controls were compared in different treatment groups. The control in the treatment group cultured in low glucose DMEM ($78.15\%$) had a significantly higher migration rate than the control in the treatment group cultured in high glucose DMEM ($36.38\%$) at 72 h ($p \leq 0.01$). LTF and its effect on cell migration and proliferation are still being determined because many contradictory reports exist [109,110]. The AgLTF complex (32 and 62 µg/mL; 1:1 ratio of AgNPs and LTF) did not differ from the control group when tested on HDFs over 72 h [27]. Furthermore, bovine- and human-derived LTF also had distinct effects against MAC-E (bovine mammary epithelial cell line) and MCF-7 (human breast tumor epithelial cell line). Bovine-derived LTF had inhibitory effects on the cell proliferation of MAC-E cells and did not affect MCF-7 cells. In contrast, human-derived LTF had a slight inhibitory effect on MCF-7 cells and no effect on MAC-E cells [111]. However, various forms of LTF, including recombinant LTF, have shown positive cell proliferation and migration results at concentrations of 10–1000 µg/mL in multiple studies [109,110,112]. In a study, LTF with an iron saturation level of over $90\%$ had the highest proliferation activity (3.5×) greater than other forms of LTF with lower iron saturation levels when tested on four cell lines [110]. LTF is also reportedly able to stimulate HDF migration at 50–200 µg/mL in a dose-dependent manner [109] and human keratinocytes at 10–100 µg/mL [112]. The mechanism by which LTF stimulates the proliferation and migration of cells is unclear. Still, this is probably because it can bind to lipoprotein receptor-related protein 1 (LRP-1), a major LTF receptor in mammalian cells, to stimulate growth. This LRP-1 receptor can be found mainly in keratinocytes and fibroblasts [112]. In addition, LTF also has synergistic effects with other growth factors and can delay cell apoptosis [110]. In the current study, when HaCaT cells were cultured in low glucose DMEM, the migration rate of cells treated with AgLTF was significantly higher than the control group from 24 h of incubation until the end of the assay at 72 h. AgLTF achieved a $100\%$ wound closure rate at 48 h, surpassing the migration rate of the control group even at 72 h. AgNPs alone only reached $69.29\%$ at 72 h, which is a testament to LTF’s pro-migratory effects on skin cells. However, in the high glucose DMEM treatment group, AgLTF ($43.88\%$) achieved only a comparable migration rate to the control group ($36.38\%$). Considering that the migration rate of AgNPs alone was significantly lower than the control at 72 h, incorporating LTF into AgNPs resulted in an improved overall migration rate of the complex, albeit it was non-significant to control. As for the SL gels containing DsiRNA, they were only able to achieve higher migration rates of HaCaT cells ($54.47\%$) than the control group ($36.38\%$) after 48 h when cultured in high glucose DMEM ($p \leq 0.01$). At 72 h, SL had a significantly higher migration rate than both the control and AgLTF groups in the high glucose treatment groups. Generally, incorporating DsiRNA into the formulation was derived from a study by Syeda et al. [ 2012], which concluded that diabetic wounds are difficult to treat due to the increased PGT protein expression and mRNA levels. It negatively affects PGE2 and VEGF levels, wound closure, and angiogenesis. In this study, the sequence of the DsiRNA was designed to target a specific mRNA for PGT and cause degradation at the cellular level. Hence, this DsiRNA silences the protein-coding genes and restores the PGE2 to a normal level. Additionally, DL gel was included as a treatment sample to test and validate the hypothesis that treating wounds in their respective phases (inflammation phase: 1–3 days and proliferation phase: 2–10 days) is better than focusing on a single healing stage [51]. However, DL achieved underwhelming results for both the low glucose treatment group ($88.58\%$) and the high glucose treatment groups ($32.67\%$) at 72 h, which were non-significant to the control group, probably due to insufficiency in the study duration. Ma et al. [ 2020] demonstrated a 5-day release of a conditioned medium of RAW 247 cells in sodium alginate microparticles to stimulate the formation of vascularized granulation tissue during the proliferation stage in an 18-day in vivo wound healing study. In this study, only 72 h of wound scratch assay duration was permitted due to the potential toxicity of AgNPs. As previously mentioned, the proliferation phase in wound healing usually occurs after the inflammation phase on day 2 up to day 10 after injury. Therefore, there is a high chance that the synchronized effect of the biological proliferation of cells and DsiRNA did not occur. Hence, a simple SL gel remains superior to a DL gel in this research setting. Moreover, further research involving prolonged-release DsiRNA on at least a 5-day wound scratch assay is warranted to investigate whether the migratory capacity of HaCaT cells is enhanced. The findings from the scratch assay were further supported by the protein levels of PGE2 obtained using the ELISA technique (Figure 13). PGE2 is vital for wound healing because it stimulates angiogenesis via the VEGF protein [37]. Therefore, when PGE2 increases, angiogenesis and the wound healing rate are also increased. PGE2 levels in the low glucose treatment group were much higher than the PGE2 levels in the high glucose treatment group ($p \leq 0.01$). Despite this, PGE2 levels of SL and DL, when cultured in high glucose DMEM, were significantly higher than their control groups, implicating the importance of DsiRNA to correct PGT overexpression in a hyperglycemic condition. Overall, the treatment results of SL and DL gel were not comparable to those in the treatment groups cultured in low glucose DMEM. This reflects a normal person’s wound healing capacity, probably because of other cellular impairments in diabetic wounds. For instance, the basic fibroblast growth factor (bFGF) signaling protein Rac1, which is essential to promote cell migration and increase fibronectin expression, is abnormally activated in hyperglycemic conditions to delay wound healing [106]. Since DsiRNA in this study was only used to correct the overexpression of PGT proteins in diabetic wounds, other cellular abnormalities may persist and delay wound healing to an extent. Ultimately, LTF and DsiRNA complexed to AgNPs in hydrogel enhanced cell migration of HaCaT cells and improved the wound healing capacity of diabetic wounds, although it was not to its full capacity. ## 4. Conclusions In this study, AgNPs were successfully complexed with LTF to form AgLTF, and the fabricated complex was in crystalline nano-sized particles and primarily spherical. AgLTF demonstrated antibacterial activity against S. aureus, E. coli, and P. aeruginosa. AgLTFs were later successfully loaded with DsiRNA and packaged in SL and DL hydrogels made of gelatin and genipin with two different drug release profiles. DL hydrogels demonstrated slower release for AgNPs, LTF, and DsiRNA than SL hydrogels at 72 h. Antibacterial tests for SL and DL hydrogels exhibited positive effects against Gram-positive and Gram-negative bacteria, consistent with the antibacterial results obtained in its solution form. AgLTF, SL, and DL hydrogels showed higher biofilm inhibition against P. aeruginosa and S. aureus than the control group, indicating that LTF plays an essential role in combating biofilm-forming pathogens by enhancing the anti-biofilm effect of AgNPs. AgLTF-DsiRNA in SL gel containing 125 µg/mL AgNPs, 250 µg/mL LTF, and 0.015 µg/mL DsiRNA were non-cytotoxic at 72 h treatment with HaCaT cells. As for the cell migratory properties, SL and AgLTF gels increased the migration rate of HaCaT cells in both low and high glucose DMEM, indicating an improved wound healing rate due to the pro-migratory effects of DsiRNA and LTF. Moreover, PGE2 protein levels were also increased in SL hydrogels, showing that PGE2 was indeed underexpressed in hyperglycemic conditions and was improved via the effects of DsiRNA to enhance wound healing rate in diabetic patients. However, DL hydrogels demonstrated underwhelming results regarding their migratory capacity, probably due to the slow release of DsiRNA from the hydrogels. On this basis, further optimization of AgLTF is needed to improve its biocompatibility so that the in vitro wound healing assay can be extended to at least 5 days. This is to synchronize the migratory effects of DsiRNA with the biological proliferation phase in the wound healing process, which occurs from day 2 to day 10, and to observe the additional impact of the prolonged release of DsiRNA on diabetic wound healing. Perhaps in a future study, a diabetic wound model using rats or mice could also be considered to solidify the in vitro results obtained from this study. 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--- title: Comparison of COVID-19 Severity and Mortality Rates in the First Four Epidemic Waves in Hungary in a Single-Center Study with Special Regard to Critically Ill Patients in an Intensive Care Unit authors: - Éva Nagy - Péter Golopencza - István Barcs - Endre Ludwig journal: Tropical Medicine and Infectious Disease year: 2023 pmcid: PMC10054791 doi: 10.3390/tropicalmed8030153 license: CC BY 4.0 --- # Comparison of COVID-19 Severity and Mortality Rates in the First Four Epidemic Waves in Hungary in a Single-Center Study with Special Regard to Critically Ill Patients in an Intensive Care Unit ## Abstract Different variants of coronavirus 2 (SARS-CoV-2), a virus responsible for severe acute respiratory syndrome, caused several epidemic surges in Hungary. The severity of these surges varied due to the different virulences of the variants. In a single-center, retrospective, observational study, we aimed to assess and compare morbidities and mortality rates across the epidemic waves I to IV with special regard to hospitalized, critically ill patients. A significant difference was found between the surges with regard to morbidity ($p \leq 0.001$) and ICU mortality ($$p \leq 0.002$$), while in-hospital mortality rates ($$p \leq 0.503$$) did not differ significantly. Patients under invasive ventilation had a higher incidence of bloodstream infection (aOR: 8.91 [4.43–17.95] $p \leq 0.001$), which significantly increased mortality (OR: 3.32 [2.01–5.48]; $p \leq 0.001$). Our results suggest that Waves III and IV, caused by the alpha (B.1.1.7) and delta (B.1.617.2) variants, respectively, were more severe in terms of morbidity. The incidence of bloodstream infection was high in critically ill patients. Our results suggest that clinicians should be aware of the risk of bloodstream infection in critically ill ICU patients, especially when invasive ventilation is used. ## 1. Introduction A new type of coronavirus pandemic causing acute respiratory illness started in China in December 2019 and has rapidly become a global public health emergency of international concern. The new type of coronavirus has been given the name SARS-CoV-2, and the disease it causes is known as coronavirus disease-19 (COVID-19) [1]. According to a World Health Organization (WHO) aggregate report, the disease caused by the virus has affected more than 663 million people worldwide and caused the deaths of more than 6.5 million people as of mid-January 2023 [2]. The course of the infection ranges from mild symptoms to fatally severe respiratory failure [3]. The first reports from China described patients with signs of viral pneumonia and fever, coughing, chest discomfort, and dyspnea [4,5,6]. Gastrointestinal symptoms have also been frequently reported [7,8]. In more severe cases, the virus may induce a strong immune response by rapid replication in the alveolar epithelial cells of the lung, resulting in a cytokine storm which in turn causes acute respiratory distress syndrome (ARDS) and respiratory failure [9,10]. Patients over 60 years of age and those with severe comorbidities are at increased risk of developing ARDS [11,12,13] but may also develop multi-organ failure [14,15,16], a leading cause of death in COVID-19 patients [17,18,19]. Secondary bloodstream infections are more common in patients with severe respiratory tract infections [20,21] and may increase the risk of a fatal outcome. According to a WHO communication, five variants of concern (VOC) of SARS-CoV-2 were identified between the start of the pandemics and December 2021. These are Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529) [22,23]. These strains cause epidemics of varying severity. Such a high mutation frequency is natural for RNA viruses (such as HIV, influenza, and coronaviruses). Lacking a complementary strand to provide for conservatism, the replication errors of the single-stranded nucleic acid of these viruses are not corrected. If this impacts the structure of a viral protein, antigenicity will also be affected, which in turn may lead to the loss of the protection already acquired [24]. Our study aimed at characterizing the epidemiology of the first four SARS-CoV-2 surges in Hungary, as well as identifying the differences between them. We hypothesized that the course of the disease, the need for intensive care unit (ICU) admission, mortality from complications, and symptoms differed between the surges. We also wished to identify factors influencing high ICU mortality rates. This paper does not include an examination of the effects of co-morbidities and risk factors. The results of our study on the impact of comorbidity and lifestyle risk factors on disease outcome and progression are summarized in another publication [25]. ## 2.1. Study Design and Data Sources Our single-centered, retrospective, observational study was conducted at the Bajcsy-Zsilinszky Hospital (Budapest, Hungary), during the first 4 epidemic waves in Hungary, from 15 March 2020 to 31 December 2021, on patients hospitalized with laboratory-confirmed SARS-CoV-2 infection. The total inpatient capacity of the hospital is 804 beds. The Intensive Care Unit has 18 beds; however, with the rise in the number of COVID-19 patients in the second wave of the pandemic, the ventilation capacity needed to be increased to 38 beds. The following information was collected from the hospital’s medical IT system (MedScribe, E-Consult 2000 Kft., Debrecen, Hungary): demographic data, co-morbidities, radiology results, days of care, need for ICU admission, methods of ventilation and oxygen supplementation, vaccination status, vaccine types, symptoms, severity, and outcome and, in the case of ICU patients in critical condition, the data from positive blood cultures. Data was collected using Microsoft Excel spreadsheet (Microsoft Corp., Redmond, WA, USA). To visualize the dynamics of the epidemic, an epidemic curve was constructed, plotting daily changes in the number of cases, indicating the date of positive SARS-CoV-2 tests, and, for infections confirmed before hospital admission, the date of admission. The hospital load curve illustrates the daily evolution of the number of patients requiring ventilation. The start and end dates of each surge were determined on the basis of information from the Epidemiology and Infection Control Department of the National Centre for Public Health (NNK). Data were collected and analyzed with the permission of the Institutional Committee of Science and Research Ethics and General Ethics. ## 2.2. Definitions The infection was considered confirmed in patients with nasopharyngeal or lower respiratory tract samples giving positive results in real-time polymerase chain reaction (RT-PCR) or in vitro immunochromatography (rapid antigen test) for the antigen of the virus. The RT-PCR tests were carried out by accredited laboratories. The antigen-based rapid tests were performed and documented by physicians using approved tests. On admission, after physical examination, patients were classified into five categories based on their nutritional status (1 = underweight; 2 = normal weight; 3 = overweight; 4 = obese, and 5 = severely obese). The relevant category was indicated on the medical record of patients. During data collection, patients were classified into non-obese (categories 1 and 2) and obese (categories 2, 3, and 4) groups based on their nutritional status. To define the severity of the disease, the criteria set forth in the Therapeutic Manual by the Ministry of Human Resources [26] were used. The Manual establishes severity on a scale of 0 to 4, from asymptomatic to critical. The clinical and pathological diagnosis for the cause of death, as provided by the treating physician and pathologist, was used as the basis for the assessment of COVID-19-related mortality. To identify cases of bloodstream infection (BSI), ventilator-associated pneumonia (VAP), hospital-acquired pneumonia (HAP), urinary tract infection (UTI), and other infections, we used the epidemiological case definitions published in the Official Journal of the European Union [27]. ## 2.3. Participants and Study Size The present study included adult patients over 18 years of age who were diagnosed with an acute infection. Acute illness was defined as cases where the patient was admitted to hospital within 14 days of taking a sample for a coronavirus infection. For patients with multiple episodes of acute infection, the first episode or the one requiring hospitalization was considered. Patients who required hospital admission with post-COVID symptoms following a previous infection were excluded. After applying the exclusion criteria, 2873 patients requiring at least 24 h of inpatient care were considered during the study period. Hospitalization was mostly necessary in the case of patients with moderate/severe/critical conditions and those whose admission was justified by some underlying condition. In total, 358 critically ill patients were admitted to the ICU for respiratory support. From the COVID-infected patients admitted to our hospital during the study period, 399 were fully immunized, with doses prescribed by the relevant vaccine application instructions. ## 2.4. Blood Culture Sample Collection and Laboratory Procedures According to the hospital’s protocol, hemocultures were obtained from all critically ill patients within 48 h of ICU admission. Samples were collected in BD Bactec blood culture bottles, with 1 aerobic and 1 anaerobic bottle being used at each sampling occasion. Samples were incubated in a BD-Bactec 9240 (Becton, Dickinson and Company, Sparks, Nevada, USA) automaton. From positive samples, bacteria/fungi were recovered and identified. Resistance was determined and multi-resistant strains identified according to national and international (European Committee on Antimicrobial Susceptibility Testing) recommendations [28,29,30]. ## 2.5. Statistical Methods In this paper, continuous and categorical variables are presented as percentages, with means, medians, standard deviations, and interquartile ranges provided. For the epidemic curves, the numbers of new cases are presented as absolute numbers and 7-day moving averages. To determine differences between categorical variables, Fisher’s exact test and the χ2 test (Pearson’s chi-squared test) were used. Positive probabilities for independent variables affecting ICU mortality were calculated using multivariate logistic regression. The Hosmer–Lemeshow test was applied to assess the goodness of fit of the logistic regression model. In the logistic regression analysis, an odds ratio was calculated to determine the degree of risk, with a $95\%$ confidence interval. The regression model was built using the backward elimination method. After applying the elimination method, the results of the initial and final models were compared. The results of the initial model are reported in this paper wherever the significant variables remaining in the last step of the elimination did not change significantly. Non-significant variables are also provided. Statistical tests were performed using SPSS Statistics V22 (IBM Corp., Armonk, NY, USA). Two-tailed α values below 0.05 were considered as statistically significant. Our study design and the presentation of results followed the guidelines of Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) [31]. ## 3.1. Epidemiological Description of Epidemic Waves The epidemiological descriptions of individual surges are summarized in Table 1. The highest number of hospitalized and artificially ventilated infected patients was recorded in Wave III. The median age was the highest in Wave I (75.5 ± 12.67, IQR: 66–84; Table 1). The median number of days of care at the COVID ward exceeded 10 days in all waves, with the number of days of ICU care varying between 6 and 11. ## 3.2. Epidemic Dynamics The dynamics of an epidemic is illustrated by the absolute numbers and 7-day moving averages of new cases and the 7-day moving averages of mortality cases (Figure 1). Hospital load trends are illustrated in Figure 2. The peak load was measured on 5 April 2021 at 183 hospitalized patients, of which 24 people were ventilated in the ICU; this number corresponds to $48\%$ of the patients treated in the hospital that day. ## 3.3. Severity of Course and Disease Outcome The distribution of severity categories in the individual surges showed significant differences. In the majority of cases, severity was moderate, with a shift towards the severe category in the third wave only (Table 2). Rates of mortality due to COVID-19 complications did not show significant differences ($$p \leq 0.504$$; Table 2). A detailed summary of symptoms observed during the epidemic waves is presented in Table A1 in Appendix A. The leading symptoms across the whole study period were dyspnea, fever/high temperature, weakness, and cough. Almost half of the patients admitted to the inpatient COVID-19 ward (1372 patients, $47.8\%$) required oxygen supplementation during their stay. The highest number and highest proportion of patients requiring oxygen supplementation were observed in Wave III and Wave IV, respectively (545 patients, $48.8\%$ and 359 patients, $50.1\%$; $p \leq 0.001$). ## 3.4. Proportions of Vaccinated Patients in the Total Study Population and the Impact of Vaccination on Mortality and ICU Admission In our study, altogether, 399 fully immunized patients were hospitalized with COVID-19 after the SARS-CoV-2 vaccines had become available during Waves III and IV. Most of them were admitted to the hospital in Wave IV. In Wave III, immunization significantly reduced both mortality and the need for ICU admission ($$p \leq 0.016$$ and $$p \leq 0.033$$, respectively; Table 3). In Wave IV, immunization had a lesser but still significant effect on the need for ICU admission ($$p \leq 0.039$$); however, it did not significantly affect mortality ($$p \leq 0.8$$; Table 3). ## 3.5.1. Need for ICU Admission In the first two years of the epidemic, the number of ICU patients did not differ significantly compared to previous years; however, mortality showed an upward trend (Figure 3a). In 2020, $16.7\%$ of patients requiring ICU care were confirmed as being infected with SARS-CoV-2; their proportion increased to $37.5\%$ in 2021. The proportion of patients requiring ICU care compared to the total number of cases is illustrated in Figure 3b. The proportion and number of patients ventilated ($14.4\%$, 161 patients) was the highest in Wave III. The proportions and numbers of ICU patients requiring artificial ventilation in Wave II, Wave IV, and Wave I were $13\%$ (102 patients), $11.6\%$ (83 patients), and $4.7\%$ (12 patients), respectively ($p \leq 0.001$). ## 3.5.2. Mortality in Critically Ill Patients The causes of high ICU mortality were further analyzed. Results concerning possible risk factors are summarized in Table 4. Of the patients studied, $90.2\%$ had some co-morbidities at the time of infection, and $46.6\%$ were obese. Concerning comorbidities, the significant and most common risk factors identified in our previous study (hypertension, diabetes mellitus, cardiovascular disease, cancer, chronic kidney disease) are highlighted. The median age of patients was above 60 years across all surges. A total of $10.1\%$ of patients had received SARS-CoV-2 vaccination before contracting the disease, with most of them having been infected during Wave IV. Ventilator-associated pneumonia (VAP) was confirmed in 73 ($28.5\%$) of the invasively ventilated patients. In addition to these cases, hospital-acquired pneumonia (HAP), urinary tract infection, and other infections (surgical site infections and skin and soft tissue infections in most cases) were confirmed in five, six and fourteen patients across the waves, respectively (Table 4). A multivariate logistic regression model was used to examine the effect of potential risk factors on ICU mortality (Table 5). The risk effects of BSI and VAP were analyzed separately. Other infections were combined into the category ‘Other infections’ due to the low number of cases. No statistically significant risk factors were identified in Waves I or II. In Wave IV, age had a marginally significant effect on mortality, slightly increasing it ($$p \leq 0.005$$). In Wave III, in addition to age, bloodstream infection also became a significant risk factor, causing a profound, more than nine-fold increase in mortality ($p \leq 0.001$; Table 5). Over the entire study period, BSI patients showed a higher mortality rate compared to the non-BSI group ($78.7\%$ vs. $54.1\%$; $p \leq 0.001$). Ventilator-associated pneumonia in Wave III was a high yet statistically insignificant risk factor, ($$p \leq 0.064$$; Table 5). Other infections were not proven to be significant risk factors regarding the mortality caused by COVID-19 complications. ## 3.5.3. Bloodstream Infections In total, bloodstream infections developed in $38\%$ of ICU patients, with the highest rate observed in Wave III ($45.3\%$). Bloodstream infection cases were divided according to cause into monomicrobial and polymicrobial infections (84 and 52 patients, respectively). On average, BSI patients spent more time in the ICU compared to the non-BSI group (12 ± 11.3 vs. 7.6 ± 5.8 days). The distribution of pathogens and the prevalence of multi-drug resistant (MDR) pathogens are summarized in Table 6. As for the relative frequency of pathogens in hemocultures testing positive, Gram-positive and Gram-negative pathogens as well as fungal strains were identified in $39\%$, $56.5\%$, and $4.5\%$ of patients, respectively. Of the pathogens cultured from hemocultures, $58.7\%$ were difficult-to-treat pathogens (methicillin-resistant *Staphylococcus aureus* (MRSA), Enterococcus faecalis, Enterococcus faecium, Klebsiella pneumoniae, Acinetobacter baumannii, Acinetobacter sp., *Pseudomonas aeruginosa* and Stenotrophomonas maltophilia). Of the isolates, $22\%$ contained MDR bacteria (MRSA, vancomycin resistant Enterococcus sp. ( VRE), extended-spectrum beta-lactamase (ESBL) and AmpC-producing Enterobacterales, and MDR Acinetobacter sp.). ## 3.5.4. Effect of Invasive Ventilation on the Development of Bloodstream Infection The distribution of ventilation modes used in ICU patients according to epidemic wave is illustrated in Figure 4. Invasive mechanical ventilation (IMV)—divided into the categories IMV, airway pressure release ventilation (APRV), and extracorporeal membrane oxygenation (ECMO) in the figure—was required for $71.5\%$ of patients (256 patients). The proportion of invasively ventilated patients was above $60\%$ across all epidemic waves. A total of seven patients were transferred to another institution for ECMO treatment to make up for their missing lung function (Figure 4). Table 7 illustrates the proportion of patients with bloodstream infections among invasively ventilated patients. Bloodstream infections occurred more frequently in the IMV group compared to non-IMV patients ($p \leq 0.001$). A significant difference between the two groups was observed in all surges except for the first one. The effect of invasive ventilation on the development of bloodstream infections was tested by an adjusted regression model. IMV was identified as a significant risk factor when considering all patients (aOR: 8.92 (CI: 4.44–17.95); $p \leq 0.001$). VAP also significantly increased the odds of developing healthcare-associated bloodstream infection (aOR: 7.95 (4.19–15.09); $p \leq 0.001$). ## 4. Discussion In our study, we analyzed the characteristics of the first four waves of the SARS-CoV-2 epidemic in Hungary among hospitalized patients over a long period of time. Our results demonstrate that the surges were significantly different concerning the severity of morbidity, the need for ICU admission and ICU mortality. Furthermore, invasive ventilation and ventilator-associated pneumonia increased the odds of critically ill patients developing bloodstream infections, which in turn significantly increased the overall risk of mortality. There was no statistically significant difference in in-hospital mortality between the surges. As for the symptoms, our results were similar to the findings of other national studies [32,33]. In Hungary, the original variant was responsible for the first two surges. The third wave was caused by the alpha variant and the fourth by the delta variant [34,35]. The first two surges differed in several aspects, probably due to different epidemiological management strategies. Patients in the first wave had the highest mean age and mortality. In the first half of 2020, as a result of strict epidemiological measures, the majority of patients admitted to hospital were of advanced age, had many co-morbidities, and were living in nursing homes, which may explain the high mortality rate observed. Over the course of the second surge of the epidemic, three times as many patients needed hospitalization and 8.5 times as many ICU patients were ventilated than in the first wave. The average age of patients, the average number of days of care, and the mortality rate were lower in the second wave. Epidemic management was hampered by the high incidence of hospital-acquired outbreaks and the high number of healthcare workers acquiring the disease. With the emergence of the alpha variant, the third surge started in Week 4 of 2021 [34,35]. The third wave was the most severe in terms of hospital loads and disease progression. The average age of patients dropped below 70 years and nearly $60\%$ were in severe or critical condition. The morbidity rate among health workers was lower, presumably due to the vaccination campaign launched at the beginning of the year and the immunity acquired by contracting the disease in the previous wave. The fourth surge was dominated by the delta variant. It spread more rapidly than the alpha variant and caused more severe cases, in the unvaccinated population in particular [34]. Hospital loads decreased, probably as a result of the widespread availability of SARS-CoV-2 vaccines. The proportion of critically ill patients requiring ventilation was lower, but mortality among hospitalized and ICU patients remained high. This surge showed the highest number of breakthrough infections. Half of the patients admitted to the hospital had received active immunization before contracting the illness. Our results suggest that in the wave caused by the delta variant, active immunization was no longer a significant protective factor for in-hospital mortality, which prompted the development of further preventive measures and the administration of booster vaccines, especially among the vulnerable and the elderly, as well as health workers. The disease course of COVID-19 ranges from asymptomatic viral shedding to fatal multi-organ dysfunction. The related risk factors and genetic predisposing factors influencing the progression of the disease are the subject of much research. Turk et al. divided disease progression into three clinico-biological phases: 1. initial phase also known as the asymptomatic or presymptomatic phase; 2. propagation phase, with mild/moderate/severe respiratory symptoms; 3. complication phase, a multisystemic clinical syndrome with impaired and/or defective immunity. The third clinical phase, manifested in multi-organ failure, septic shock, and ARDS, may be considered as COVID-19 syndrome due to the complex clinical course. This study demonstrated that the different phases have different genomic features, which in turn lead to different clinical symptoms driven by different mechanisms [36]. In comparison with our previous study, some differences were observed in the mortality risk factors identified in the general population and ICU patients. In addition to age and male sex, obesity, and the presence of certain comorbidities (e.g., cardiovascular disease, cancer, chronic renal failure) were significant risk factors for all patients included in the study [25]. Of the ICU patients studied, $90\%$ had comorbidities and nearly half of them were obese, yet these factors did not impair survival to a statistically significant extent. Of the 2873 patients, $12.5\%$ were admitted to the ICU due to the severity of their condition and/or the need for ventilator support. Among the $71.5\%$ of ICU patients who required invasive mechanical ventilation, the mortality rate was $80.5\%$. The risk effect of invasive ventilation on mortality could be statistically demonstrated. Besides invasive ventilation, age and bloodstream infection were significant risk factors. In our study, the incidence of bloodstream infection in critically ill patients was high; this finding is supported by similar results reported by other studies [20,21,37,38]. High ICU mortality may be explained by several factors. Much like in many other hospitals in Hungary, the number of days patients spent in ICU increased significantly during the COVID epidemic [39]. Combined with the increased use of invasive techniques and medical devices typical of COVID care, long hospital stay significantly increases the risk of infection. Across all surges, the need for invasive ventilation was high, and this method is a known risk factor for bacterial superinfection of the lung and subsequent bloodstream infection. In our study, we identified invasive ventilation as a significant risk factor for healthcare-associated bloodstream infections. A proportion of bloodstream infections ($14.5\%$) developed prior to invasive ventilation, suggesting that primary bloodstream infections may have increased the severity of illness, making IMV use in these cases forced and secondary. However, given that in the majority of cases BSI developed after invasive ventilation, we consider that the statistically demonstrated risk role of IMV is valid. Furthermore, the immune dysfunction induced by severe SARS-CoV-2 infection and the immunosuppressive effect of prolonged steroid treatment as part of COVID-19 therapy may predispose patients to concurrent infections [10,40,41]. ICU load was high, especially in the third wave. Increased workload meant healthcare workers were forced to deal with more patients daily, which led to a decrease in their infection control compliance. This in turn may have contributed to the increased incidence of BSI. A recent publication has shown that SARS-CoV-2 causes dysbiosis of the gut microbiome, resulting in the increased translocation of gut bacteria into the bloodstream, causing severe, potentially mortal secondary sepsis [42]. This may explain our observation of a high proportion of bloodstream infections in ICU patients having been caused by the gut microbiota. There are some limitations to this study. Being a single-center study, it cannot be generalized to the entire Hungarian population nor to the characteristics of COVID-19 care in Hungary. In addition to IMV and VAP, the use of invasive devices (e.g., central venous catheters and peripheral vascular catheters) may have increased the risk of bloodstream infections, but the present study did not include an assessment of device use rates and their risk impact due to limited data. The statistical analysis of the data from the first surge is of limited value due to the low number of cases, especially regarding ICU mortality. The study did not include a follow-up of therapy and laboratory parameters; thus, the extent to which long-term steroid treatment might have influenced the risk of bloodstream infections cannot be assessed. ## 5. 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--- title: Omega-3-Supplemented Fat Diet Drives Immune Metabolic Response in Visceral Adipose Tissue by Modulating Gut Microbiota in a Mouse Model of Obesity authors: - Néstor D. Portela - Cristian Galván - Liliana M. Sanmarco - Gastón Bergero - Maria P. Aoki - Roxana C. Cano - Susana A. Pesoa journal: Nutrients year: 2023 pmcid: PMC10054794 doi: 10.3390/nu15061404 license: CC BY 4.0 --- # Omega-3-Supplemented Fat Diet Drives Immune Metabolic Response in Visceral Adipose Tissue by Modulating Gut Microbiota in a Mouse Model of Obesity ## Abstract Obesity is a chronic, relapsing, and multifactorial disease characterized by excessive accumulation of adipose tissue (AT), and is associated with inflammation mainly in white adipose tissue (WAT) and an increase in pro-inflammatory M1 macrophages and other immune cells. This milieu favors the secretion of cytokines and adipokines, contributing to AT dysfunction (ATD) and metabolic dysregulation. Numerous articles link specific changes in the gut microbiota (GM) to the development of obesity and its associated disorders, highlighting the role of diet, particularly fatty acid composition, in modulating the taxonomic profile. The aim of this study was to analyze the effect of a medium-fat-content diet ($11\%$) supplemented with omega-3 fatty acids (D2) on the development of obesity, and on the composition of the GM compared with a control diet with a low fat content ($4\%$) (D1) over a 6-month period. The effect of omega-3 supplementation on metabolic parameters and the modulation of the immunological microenvironment in visceral adipose tissue (VAT) was also evaluated. Six-weeks-old mice were adapted for two weeks and then divided into two groups of eight mice each: a control group D1 and the experimental group D2. Their body weight was recorded at 0, 4, 12, and 24 weeks post-differential feeding and stool samples were simultaneously collected to determine the GM composition. Four mice per group were sacrificed on week 24 and their VAT was taken to determine the immune cells phenotypes (M1 or M2 macrophages) and inflammatory biomarkers. Blood samples were used to determine the glucose, total LDL and HDL cholesterol LDL, HDL and total cholesterol, triglycerides, liver enzymes, leptin, and adiponectin. Body weight measurement showed significant differences at 4 (D1 = 32.0 ± 2.0 g vs. D2 = 36.2 ± 4.5 g, p-value = 0.0339), 12 (D1 = 35.7 ± 4.1 g vs. D2 = 45.3 ± 4.9 g, p-value = 0.0009), and 24 weeks (D1 = 37.5 ± 4.7 g vs. D2 = 47.9 ± 4.7, p-value = 0.0009). The effects of diet on the GM composition changed over time: in the first 12 weeks, α and β diversity differed considerably according to diet and weight increase. In contrast, at 24 weeks, the composition, although still different between groups D1 and D2, showed changes compared with previous samples, suggesting the beneficial effects of omega-3 fatty acids in D2. With regard to metabolic analysis, the results did not reveal relevant changes in biomarkers in accordance with AT studies showing an anti-inflammatory environment and conserved structure and function, which is in contrast to reported findings for pathogenic obesity. In conclusion, the results suggest that the constant and sustained administration of omega-3 fatty acids induced specific changes in GM composition, mainly with increases in Lactobacillus and Ligilactobacillus species, which, in turn, modulated the immune metabolic response of AT in this mouse model of obesity. ## 1. Introduction Obesity is a major public health problem contributing to increased morbidity and mortality worldwide [1]. It is very well known that obesity is a chronic, relapsing, and multifactorial disease representing a risk factor for other non-communicable diseases (NCDs), such as type 2 diabetes mellitus, cardiovascular disease, and cancer, among others [2]. This condition is the consequence of a sustained positive energy balance, leading to excessive accumulation of adipose tissue (AT) [3]. Under physiological conditions, AT plays critical roles in whole-body homeostasis, including the storage and release of energy, thermoregulation, and secretion of adipokines that regulate the energy balance, metabolism, and immune responses [4]. In contrast, obesity is associated with AT inflammation, mainly in white adipose tissue (WAT), showing an increase in pro-inflammatory M1 macrophages and other immune cells, due to tissue remodeling in response to adipocyte apoptosis [5]. This pro-inflammatory milieu favors the secretion of pro-inflammatory cytokines and adipokines, contributing to AT dysfunction (ATD) and metabolic dysregulation [6]. In recent decades, numerous articles have been published linking specific changes in the GM to the development of obesity and its associated disorders [7,8]. The GM is involved in many functions, including nutrient absorption, protection of intestinal mucosal integrity, regulation of immune responses, and being a central regulator of host metabolism [9]. Both structural components, lipopolysaccharides (LPSs) and peptidoglycans, and specific microbial-derived metabolites, such as short-chain fatty acids (SCFA), may act as the central factors in the pathogenesis of obesity and other NCDs [10,11,12]. Remarkably, the GM participates in the development of AT in both normal and pathological conditions. The obesity-associated gut microbiome has an increased capacity to harvest energy from the diet, contributing to increased total body fat, especially VAT [13]. Bäckhed et al. showed that germ-free (GF) mice are protected from diet-induced obesity (DIO) compared with conventional mice, which contained $42\%$ more total body fat [14]. Additionally, it has been shown that certain changes in the abundance and diversity of microbiota are associated with AT inflammation, one of the most significant features of ATD [10]. Different reports have shown that the level of circulating LPS is the key factor linking the GM with the inflammation of AT, resulting in an increase in the number of cells positive for the inflammation marker F$\frac{4}{80}$ in AT [10,15,16]. Moreover, ATD-associated obesity is characterized by the presence of cellular infiltrates rich in pro-inflammatory M1 macrophages and deficient in anti-inflammatory M2 macrophages [17]. These reports denote the importance of the GM in the regulation of adiposity, the inflammatory state, and the correct functionality in relation to the metabolic state. It is well established that both the GM structure and function are dynamic and strongly affected by diet nutrients, such as the content and composition of lipids. As a consequence, dietary lipids influence host physiology through interactions with the GM [18], although the mechanisms involved are not well defined. However, it has been shown that high-fat diets (HFDs) decrease the GM diversity and epithelial barrier-protecting bacteria while increasing the abundance of deleterious and pro-inflammatory species [19,20], inducing low-grade chronic inflammation, a phenomenon known as metabolic endotoxemia, which is associated with the development of obesity and numerous NCDs [10,21]. In this context, most of the studies in murine models used diets with a fat content of $60\%$ or higher; these levels accelerated the development of obesity, generating exacerbated metabolic and physiological responses. However, Speakman et al. stated that HFDs with a $60\%$ fat content represent a large distortion of a normal rodent chow, and the results obtained in these studies cannot be potentially extrapolated to humans [22]. Additionally, as mentioned above, different types of dietary fatty acids can differentially influence the GM composition, obesity development, and metabolic manifestations, producing either beneficial or harmful responses [23,24]. Overall, a diet rich in saturated fatty acids (SFAs) promotes low-grade inflammation through direct action on TRL4 [25], reduces the diversity of the GM, increasing the relative abundance of Firmicutes, decreasing Bacteroidota [26,27], and increasing the proportion of Proteobacteria [28]. On the other hand, polyunsaturated fatty acids (PUFAs), a subgroup of essential fatty acids, have differential effects on health and the GM; a diet rich in n-6 PUFA promotes dysbiosis associated with weight gain and the infiltration of macrophages and neutrophils into the ileal submucosae. In contrast, fish oil-supplemented diets rich in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) (n-3 PUFA) restore the GM composition, recruit regulatory T cells (Treg), and decrease the infiltration of macrophages and neutrophils [29]. In addition, n-3 PUFAs have been shown to reduce the production of reactive oxygen species (ROS) and to inhibit the production of pro-inflammatory cytokines, reducing metabolic endotoxemia [30]. However, information on models mimicking, in rodent studies, aspects of the diet that are similar to those found in humans is lacking. As mentioned above, the high fat content in HFD models is not extrapolated to humans. This prompted us to analyze the effect of a medium-fat-content diet ($11\%$) supplemented with omega-3 fatty acids on the development of obesity and its impact on the composition of the GM compared with a control diet with low fat content ($4\%$) over a 6-month period. The proportions of SFAs, monounsaturated fatty acids (MUFAs), and PUFAs were comparable in both diets. Furthermore, we evaluated the contribution of Omega-3 supplementation to metabolic parameters and the modulation of the immunological microenvironment in VAT. ## 2.1. Animals and Experimental Design Male C57BL/6J (B6) mice (6-weeks-old) were purchased from the Facultad de Ciencias Veterinarias of the Universidad Nacional de La Plata, Buenos Aires, Argentina. All animals were housed in isolation rooms at the Animal Facilities of the Facultad de Ciencias Químicas of the Universidad Católica de Córdoba. This research has the authorization of the Institutional Committee for the Care and Use of Laboratory Animals—CICUAL-FCQ- Universidad Nacional de Córdoba, Córdoba, Argentina. Resolution N° 939, EXP-UNC: $\frac{0023836}{2018.}$ The environmental conditions in the facility were set according to CICUAL Guidelines. All animal procedures were performed in accordance with the guidelines of Directive $\frac{2010}{63}$/EU of the European Parliament on the protection of animals used for scientific purposes. The mice were randomly divided into two groups of eight mice each and adapted for two weeks to the experimental conditions. Then, the mice were fed a low-fat diet, “Control Diet” (D1, $4\%$ fat), or an “obesity-induced diet” with medium fat content (D2, $11\%$ fat) for a period of 24 weeks. Both groups were maintained under a standard light cycle (12 h light/dark), with free access to water and food, and temperature conditions (21 ± 2 °C). The food was replaced every two days to keep it fresh. ## 2.2. Evaluation of Development of Obesity The body weight of the mice was evaluated at 0, 4, 12, and 24 weeks. DIO was defined by the cut-off point of the mean body weights of the mice at week 0 plus 3 standard deviations in both groups (D1 and D2). ## 2.3. Food Composition Control Diet composition (D1): $4\%$ fat, $26\%$ protein, $52\%$ carbohydrate, $8\%$ crude fiber, and $10\%$ total minerals (GEPSA Pet Foods, Pilar, Argentina). Obesity-Inducing Diet composition (D2): $11\%$ fat, $27\%$ protein, $48\%$ carbohydrate, $6\%$ crude fiber, and $8\%$ total minerals. Ingredients: Corn, wheat, rice, soybean meal, chicken by-product meal, beef fat and/or chicken oil preserved with mixed tocopherols, beef and egg meal, corn and/or wheat gluten meal, fish flour (natural source of DHA), and animal digest based on chicken and/or pork by-products and salt (Purina Nestlé). The lipid composition was as follows: D1, SFAs: $24.61\%$, MUFAs: $39.37\%$, PUFAs: $36.02\%$, omega-3 fatty acids: $20.29\%$, omega-6 fatty acids: $15.73\%$, and omega-3/omega-6 ratio: 1.29; and D2, SFAs: $25.81\%$, MUFAs: $35.38\%$, PUFAs: $38.81\%$, omega-3 fatty acids: $30.14\%$, omega-6 fatty acids: $8.67\%$, and omega-3/omega-6 ratio: 3.48. ## 2.4. Food Intake Assay To assess the acceptance of both the D1 diet and D2 diet, we carried out a consumption assay to measure food intake by mice. Briefly, we used individual mouse cages ($$n = 10$$/each diet) with one mouse each in the animal laboratory facility under the conditions cited above under Animals and Experimental Design. The initial amount of feed was weighed (5 g/cage to record daily feed intake). Consumption was measured by the differential weighing of the food at 0 and 24 h after feeding using an Ohaus digital scale model CS200, precision ± 0.1 g. Two independent experiments were performed to obtain an acceptable trend prior to the statistical analysis of the data (p-value < 0.05 was considered statistically significant) [31]. ## 2.5. Analysis of Gut Microbiota Composition The GM composition was studied in stool samples, collected individually in metabolic cages over a period of 6 h at weeks 0, 4, 12, and 24. The feces were frozen immediately after collection and stored at −40 °C until analysis. ## 2.6. DNA Extraction Stool samples were handled under a laminar flow hood using a sterile technique. Microbial DNA was isolated from 220 mg of stool using the QIAmp DNA Stool Mini Kit (Qiagen, Germantown, MD, USA) following the manufacturer’s standard protocol. The DNA concentrations were measured using fluorometric quantitation with a Qubit 2 and the Qubit dsDNA high-sensitivity kit (Thermo Fisher Scientific, Carlsbad, CA, USA). The DNA was stored at −40 °C. ## 2.7. 16S rRNA Gene Amplicon Library Preparation Sequencing and Taxonomic Identification of Bacteria Sequencing was performed using an Ion 16S Metagenomics Kit (Thermo Fisher Scientific, Carlsbad, CA, USA) on the Ion Torrent Personal Genome Machine (PGM) platform (Thermo Fisher Scientific, Carlsbad, CA, USA). The libraries were generated from 20 ng of fecal DNA with the Ion 16S Metagenomics Kit using a combination of two pools of primers targeting the V2, V4, and V8 hypervariable regions of the 16S rRNA gene in pool 1, and the V3, V6-7, and V9 regions in pool 2. The primers were partially digested and bar-codes were ligated to the amplicons, purified using the Agencourt AMPure XP beads (Beckman Coulter; Pasadena, CA, USA) according to the manufacturer’s protocol, and stored at −20 °C. The concentration of each 16S library was determined by qPCR using the Ion Universal Library Quantitation Kit (Thermo Fisher Scientific Carlsbad, CA, USA). The library was diluted to ~10 pM before template preparation. Template preparation of the barcoded libraries was performed using the Ion PGM Hi-Q View OT2 kit (Thermo Fisher Scientific Carlsbad, CA, USA) and the Ion OneTouch 2 System (Thermo Fisher Scientific Carlsbad, CA, USA). A mock community dataset was generated from mixed bacterial genomic DNA from ATCC strains, including *Escherichia coli* ATCC 25922, *Staphylococcus aureus* ATCC 25923, *Pseudomonas aeruginosa* ATCC 27853, *Enterococcus faecalis* ATCC 29212, and *Streptococcus group* B; the latter was isolated and typified in the LACE Laboratory. A maximum of 12 barcoded 16S samples were sequenced on an Ion 316v2 chip using the Ion PGM Hi-Q view Sequencing Kit (Thermo Fisher Scientific; Carlsbad, CA, USA) according to the manufacturer’s instructions. The sequence quality control, annotation, and taxonomical assignment were performed using the DADA2 v1.22.0 [32], phyloseq v1.38.0 [33], and microbiome v1.16.0 [34] packages in R software v4.1.2 [35] following the standard pipeline from demultiplexed fastq files. DADA2-formatted Silva Database Version 138.1–Updated 10 March 2021, was used for taxonomical assignment [36]. For the generation of functional profiles based on the composition of the GM, the Tax4Fun2 package v 1.1.5 [37] was used on the R platform for genus-level taxonomy. Linear discriminant analysis Effect Size (LEfSe), performed using an online tool on the galaxy platform (http://huttenhower.sph.harvard.edu/galaxy/) accessed on 28 November 2022 [38], was applied to determine the existence of differential characteristics between the study groups for taxonomy in the GM or for the predicted functional profiles. Sequencing data are accessible in the National Center for Biotechnology Information (NCBI) database under BioProject accession number PRJNA929200 (https://ncbi.nlm.nih.gov/bioproject/?term=PRJNA929200) accessed on 29 January 2023. ## 2.8. Evaluation of Blood Metabolic Profile and Immune Cells Population in VAT After 24 weeks of differential feeding, 4 mice per group were randomly selected and anesthetized using inhaled FORANE (isoflurane). Blood samples were obtained after 12 h of fasting by cardiac puncture in heparinized tubes, centrifuged at 3000 rpm, and the separated plasma was stored at −20 °C. The plasma triglyceride (TG, mg/dL), total cholesterol (TC, mg/dL), HDL-Cholesterol (HDL-c, mg/dL), glucose (Glu, mg/dL), aspartate aminotransferase activity (AST, U/L), and alanine aminotransferase activity (ALT, U/L) levels were assessed using enzymatic kits (Roche Diagnostic) in a ROCHE Cobas 8000 auto-analyzer; and LDL-Cholesterol (LDL-c) was estimated using the *Friedewald formula* as: (LDL-c = TC − [HDL-c + TG/5]). The adiponectin and leptin levels were quantified using an Adiponectin Mouse ELISA Kit (Abcam) and Leptin Mouse ELISA Kit (Invitrogen), respectively, following the manufacturer’s instructions. The mice were then sacrificed by cervical dislocation and the VAT was kept for studies of cell populations in stromal vascular fraction (SVF) as described below. ## 2.9. Isolation of the SVF from Adipose Tissue Mouse epididymal AT was processed by mechanical degradation and digested for 45 min at 37 °C with type 2 collagenase (0.8 mg/mL; Sigma) in Hanks’ Balanced Salt solution (pH = 7.4). After the addition of 3 vol. PBS containing $5\%$ FBS and filtration of the digested tissue through nylon mesh (70 μm), the filtrate was centrifuged at 200× g. The SVF was recovered from the resulting supernatant [39]. ## 2.10. Flow Cytometry The SVF of mouse epididymal AT was prepared as described above. Red blood cells were separated by centrifugation at 500× g for 5 min, and the remaining cells were suspended in PBS and exposed to FcBLOCK (BD Biosciences) for 20 min. Five hundred thousand SVF cells were washed in ice-cold FACS buffer (PBS-$2\%$FBS) and incubated with fluorochrome-labeled antibodies for 30 min at 4 °C. Different combinations of the following antibodies were used: PeCy5-labeled: anti-CD11b, PE-labeled: anti-F$\frac{4}{80}$, APCCy7-labeled: anti-CD11c, PeCy7-labeled: anti-CD206, and APC/Alexa 647-labeled: anti-CD36. Cells were permeabilized with BD Cytofix/Cytoperm and Perm/Wash (BD Biosciences) to detect intracellular ROS according to the manufacturer’s instructions. Then, the cells were incubated with FITC/Alexa 488-labeled antibody for ROS. The cells were acquired on FACS Canto II (BD Bioscience). The results were expressed as the percentage of cells per gram of AT. ## 2.11. Statistical Data Analysis Statistical analysis was carried out and visualized using R v4.1.2 software [35]. The alpha diversity (observed ASVs, and Shannon and Simpson indexes) and beta diversity (PCA and UniFrac, weighted and unweighted) were calculated based on the ASV table representing the relative abundances of bacterial taxa from the microbiome v1.6.0 R package [34]. The association between diets and the overall microbiota composition was tested using the Adonis test through the Adonis function in the vegan v2.4.6 R package [40]. The normality of the variables was assessed using the Shapiro–Wilk test. A p-value of < 0.05 was considered significant. Comparative and differential analysis between variables was performed using the two-tailed Student’s t test for variables with a normal distribution (result expressed as the mean ± standard deviation (SD)), and the Wilcoxon or Friedman tests for variables without a normal distribution (result expressed as the median, min., and max.), as appropriate. Pairwise comparisons using the paired Wilcoxon signed-rank test were performed if the Friedman test yielded a significant result. The p-values were adjusted using the Bonferroni multiple-testing correction method. Correlations between the bacterial taxa’s abundances and metabolic parameters and cell populations in SVF were calculated using the corrplot package v 0.92 [41]. For Lefse analysis, LDA scores of 2 and a p-value of <0.05 were considered significant. All data were represented using ggplot2 v3.4.0 [42] and ggpubr v0.5.0 [43]. ## 3.1. Effect of Diets on Body Weight As can be seen in Figure 1, the body weight in mice from Group D2 progressively increased along weeks 4, 12, and 24 compared with those from Group D1, and 25, 87.5, and $100\%$ of mice respectively presented DIO in Group 2 (Figure 1B–D). Remarkably, the weight gain, considered as the delta weight between different weeks, showed a significant difference between groups, being higher in D2-fed mice at weeks 4 and 12 (p-value = 0.0331 and 0.0059), not showing a significant change after 24 weeks of feeding (p-value = 0.3438), respectively (Figure 1E–G). Is important to mention that no significant differences were observed in food intake between the groups (D1 = 2.7 ± 0.5 g/24 h vs. D2 = 2.9 ± 0.2 g/24 h, p-value 0.5747). ## 3.2.1. Alpha and Beta Diversity within and between Diet Groups The comparative analysis of alpha diversity, measured as observed ASVs, Shannon and Simpson Indexes, between Groups D1 and D2 at weeks 0, 4, 12, and 24 is shown in Figure 2. There were no differences at time 0, but mice from Group D2 showed a significant increase compared with those from Group D1 at weeks 4 and 12; likewise, at week 24, observed ASVs and Simpson index had higher values in Group D2 compared with Group D1, in contrast to Shannon Index, which showed a similar trend, although the differences were not statistically significant. The analysis within Group D1 only showed significant differences for Shannon and Simpson indexes when comparing week 4 and week 24 (Figure 2E). In contrast, in Group D2, significant differences in observed ASVs were found when comparing week 0 with weeks 4, 12, and 24. A similar pattern was seen for Shannon Index at weeks 12 and 24, while Simpson Index was only higher at week 12 in relation to week 0. ( Figure 2F). Supplementary Tables S1A–C show statistical comparisons of the alpha diversity indexes. ## 3.2.2. Beta-Diversity Analysis The comparative analysis between diets at different times revealed no differences at week 0, in contrast to weeks 4, 12, and 24, when the groups clustered separately, indicating dissimilarities in the composition and taxonomic abundance of their microbiota (Figure 3A–D). Similar results were reported by the Unifrac test in both the weighted and unweighted analyses, with the exception of week 24, showing a certain overlap of the clusters for the weighted Unifrac in contrast to the unweighted Unifrac, denoting dissimilarity between the groups, probably due to the presence of taxa in low abundance. ( Figure 4A–H). ## 3.2.3. Analysis of Relative Abundances at the Phylum and Genus Levels Figure 5 illustrates the relative abundances of bacterial phyla per group at different times. Statistical analysis revealed no differences at week 0; a higher abundance of the phyla Campylobacterota, Cyanobacteria, Deferribacterota, Desulfobacterota, and Firmicutes and lower abundance of Bacteroidota and Proteobacteria in Group D2 compared with D1 at week 4; different changes were detected at week 12, when D2 presented a higher prevalence of Deferribacterota, Desulfobacterota, and Firmicutes and lower prevalence of Actinobacterota, Bacteroidota, and Proteobacteria compared with Group D1; meanwhile, at week 24, Group D2 showed a higher abundance of Desulfobacterota and Pastescibacteria and lower abundance of the Cyanobacteriota Phylum in comparison with the control group. Supplementary Table S2 shows the statistical comparison of the relative abundances at the phylum level. Figure 6 shows the 15 main genera found in all samples at all times, which represent more than 70 percent of the relative abundance of the total genera detected in the samples. The comparative analysis for genera shows higher relative abundances of bacteria from the Eubacterium eligens group, Lachnospiraceae UC5-1-2E3, and *Mycoplasma genus* for Group D2 at week 0; while the abundances of Escherichia-Shigella and Olsenella were higher in group D1, these genera were not present among the more abundant showed in Figure 6. A higher abundance of *Helicobacter and* Alistipes, and lower abundance of Prevotellaceae UCG-001 and Muribaculum was seen at week 4 in Group D2 compared with D1; meanwhile, at week 12, a higher prevalence of Lachnospiraceae NK4A136 group and lower prevalence of Parasutterella and Muribaculum was detected in group D2 compared with group D1; these genera were present within the main genera defined above. At week 24, Group D2 had a higher proportion of the genera Lachnoanaerobaculum, Candidatus Saccharimonas, and Ligilactobacillus, and a lower proportion of Alistipes compared with Group D1. Supplementary Table S3 shows the statistical comparison of the relative abundances at the genus level. ## 3.3. LEfSe Differential Analysis To determine which taxa were enriched in the different groups, linear discriminant analysis (LDA) coupled with effect size measurements (LEfSe) was applied. First, the effect of diet in each sampling week was compared and, later, each group was analyzed over time to determine specific changes not associated with diet. Significant differences at the levels of phylum, class, order, family, and genus were found among the different groups. Only enriched genera will be mentioned below to simplify interpretation. ## 3.3.1. LEfSe Analysis by Time These results are shown in Figure 7. At week 0, group D1 presented a high proportion of Escherichia/Shigella, Orsenella, and Parasutterella in contrast to group D2, presenting higher abundance of the Eubacterium eligens group, Mycoplasma, and Lachnospiraceae UC5-1-2E2 genera (Figure 7A). At week 4, the most relevant genera were Butyricicoccus, Lachnospiraceae A2, Anaerovoracaceae Family XIII AD3011 group, *Eubacterium fissicatena* group, *Ruminococcus gnavus* group, Anaerovorax, Mobilitalea, Lachnospiraceae UCG-006, Lachnospiraceae GCA-900066575, Veillonella, Desulfovibrio, Prevotellaceae UCG-001, and Muribaculum for D1; and Helicobacter, Mucispirillum, Anaerotruncus, Alistipes, Lachnospiraceae AC2044 group, Oscillibacter, Flavonifractor, *Eubacterium siraeum* group, Oscillospiraceae UCG-002, Oscillospira, Ruminococcaceae UBA1819, Lachnospiraceae ASF356, Shuttlewoethia, Roseburia, Prevotellaceae NK3B31 group, Oscillospiraceae V9D2013 group, *Eubacterium nodatum* group, Harryflintia, Tyzzerella, Ruminococcus, Paladicola, Peptococus, and Eubacterium eligens group for Diet D2 (Figure 7B). Oscillospiraceae UCG-003, Butycicicoccus, Dobosiella, Ureaplasma, Faecalibaculum, Lachnospiraceae FCS020 group, Anaerosporobacter, Christensenellaceae R-7 group, Anaerovoracaceae Family XIII AD3011 group, *Eubacterium fissicatena* group, Orsenella, Lachnospiraceae UCG-009, Veillonella, Ligilactobacillus, Candidatus Saccharimonas, Muribaculum, and Sutterella were relevant for D1 at week 12, while the genera Lachnospiraceae NK4A136 group, Mucispirillum, Lachnospiraceae AC2044 group, Rikenella, Tuzzerella, Anaerotruncus, Lachnospiraceae ASF356, Ruminococcaceae UBA1819, Oscillibacter, Harryflintia, Tyzzerella, Anaerovorax, and Lachnospiraceae UCG-003 characterized group D2 (Figure 7C). Finally, LEfSe analysis revealed that the abundances of Prevotella 7, Veillonella, Anaeroplasma, Coriobacteriaceae UCG-002, Salmonella, Prevotellaceae NK3B31 group, Faecalibacterium, and Alistipes on one hand, and Candidatus Saccharimonas, Ligilactobacillus, Lachnospiraceae ASF356, Lactobacillus, Lachnospiraceae UCG-004, Lactobacillaceae HT002, Anaerotruncus, *Eubacterium nodatum* group, Harryflintia, Ruminococcaceae UBA1819, Oscillospiraceae NK4A214 group, Anaerovoracaceae Family XIII UCG-001, Christensenellaceae R-7 group, Anaerostipes, Peptococcus, Tyzzerella, Lachnospiraceae UCG-003, Lachnospiraceae AC2044 group, and Monoglobus on the other allowed for the best characterization of groups D1 and D2, respectively (Figure 7D). Overall, these results show that the genera Harryflintia, Lachnospiraceae AC2044 group, Lachnospiraceae ASF356, Mucispirillum, Ruminococcaceae UBA1819, and Tyzzerella could be considered a microbial signature for GM in mice fed with a fatty acid-rich diet, as they presented the same distribution profile in the differential analysis between diets over time. In contrast, the *Eubacterium fissicatena* group, Anaerovoracaceae Family XIII AD3011 group, Butyricicoccus, Muribaculum, and *Veillonella* genera could represent a microbial signature for the chow diet, although just for weeks 4 and 12, when they presented similar distribution patterns. These observations confirm that there was not a single taxon or few taxa allowing the prediction of changes associated with eating patterns involving fatty diets in GM. ## 3.3.2. LEfSe Analysis by Diet over Time The results are shown in Figure 8. The analysis over time for D1 revealed that Lachnospiraceae ASF356, Negativibacillus, Tyzzerella, Anaerotruncus, Lactobacillus, Lactococcus, and Ureaplasma were the main genera allowing the discrimination of the basal state of the group; at week 4, Colidextribacter, Desulfovibrio, Anaerostipes, *Ruminococcus gnavus* group, Tuzzerella, Anaeroborax, Bilophila, Anaerovoracaceae Family XIII AD3011 group, Anaerovoracaceae Family XIII UCG-001, Eschericha-Shigella, and Lachnospiraceae A2 described the gut microbial community. Candidatus Saccharimonas, Ligilactobacillus, Flavonifractor, Faecalibaculum, Oscillospiraceae NK4A214 group, Shuttlewoethia, Butyricicoccaceae UCG-009, Lactobacillaceae HT002 and Christensenellaceae R-7 group were predominant at week 12. Finally, Bacteroides, Alistipes, Prevotellaceae NK3B31 group, and Oscillospiraceae UCG-003 allowed the prediction of the phylotype at week 24 (Figure 8A). The study of D2 showed that Alistipes, Odoribacter, Rikenella, Herbinix, Mobilitalea, *Eubacterium fissicatena* group, Mycoplasma, Anaeroplasma, Lachnospiraceae GCA-900066575, Ureaplasma, Shuttleworthiam, and Lachnospiraceae FCS020 group described the community for week 0. Helicobacter, Mucispirillum, Anaerotruncus, *Eubacterium siraeum* group, Oscillospira, Paludicola, Negatibacillus, Ruminococcus, Prevotellaceae NK3B31 group, Akkermansia, Escherichia-Shigella, and Eubacterium eligens group characterized week 4. Lachnospiraceae NK4A136 group, Colidestribacter, Flavonifractor, Tuzzerella, Lachnospiraceae AC2044 group, Bilophila, Tyzzerella, and Peptococcus were predominant at week 12. Finally, Candidatus Saccharimonas, Parasutterella, Ligilactobacillus, Lactobacillus, Lachnospiraceae ASF356, Desulfovibrio, Intestinimonas, Anaerovoracaceae Family XIII UCG-001, Lactobacillaceae HT002, *Eubacterium nodatum* group, Anaerovoracaceae Family XIII AD3011 group, Oscillospiraceae NK4A214 group, Monoglobus, Ruminococcaceae Incertae Sedis, Christensenellaceae R-7 group, Anaeroborax, and Ruminococcaceae UBA1819 were more abundant at week 24 (Figure 8B). ## 3.4. Prediction of Metabolic Pathways To explore the metabolic pathways associated with different gut microbial communities over time, we carried out functional metagenome prediction using Tax4fun2. This approach allowed the identification of 151 metabolic pathways whose abundances were compared between diet groups at each week tested. LEfSe was applied to determine which metabolic pathways were enriched in the different groups. The results are presented in Figure 9. The ascorbate and aldarate metabolism pathway from carbohydrates metabolism were more abundant in group D1 than in group D2 at time 0 (Figure 9A); in contrast, 27 metabolic pathways were differentially represented at week 4. Alanine, aspartate, glutamate, glycine, serine, and threonine metabolism were increased in group D1, while cysteine and methionine metabolism formed amino acid metabolism in group D2. A higher capacity of streptomycin and phenylpropanoid biosynthesis was also present in group D1. The pyruvate metabolism and citrate cycle (TCA cycle) pathways were increased in Group D2, and the galactose, starch, and sucrose metabolism pathways formed carbohydrate metabolism in Group D1. A higher proportion of nitrogen metabolism pathway involved in energy metabolism characterized group D1, whereas the carbon fixation pathways in prokaryotes were relevant in Group D2. Glycan biosynthesis and metabolism were represented in group D1 by a high proportion of glycosaminoglycan degradation, glycosphingolipid biosynthesis—globo and isoglobo series—and other glycan degradation pathways, while Group D2 presented a high proportion of the peptidoglycan biosynthesis pathway. Relative to lipid metabolism, group D1 showed increased glycerolipid metabolism, fatty acid biosynthesis, and sphingolipid metabolism pathways, while group D1 presented a higher proportion of pathways related to nicotinate and nicotinamide metabolism, cyanoamino acid metabolism, Polyketide sugar unit biosynthesis, and nucleotide metabolism, including the purine metabolism and pyrimidine metabolism pathways. Group D2 had a higher prevalence of metabolic pathways related to the degradation of aromatic compounds and nitrotoluene degradation (Figure 9B). Thirty-three metabolic pathways with differential prevalence were found at week 12. As for Group D1, 15 out of the 20 routes present at week 4 continued to show a similar pattern; the same was true for four pathways in group D2. Higher abundances of flavone and flavonol biosynthesis, flavonoid biosynthesis; stilbenoid, diarylheptanoid, and gingerol biosynthesis; amino sugar and nucleotide sugar metabolism; one carbon pool by folate and drug metabolism—other enzyme pathways were present in D1, and a high proportion of the arginine and proline metabolism, 2-oxocarboxylic acid metabolism, carbon metabolism, microbial metabolism in diverse environments, porphyrin and chlorophyll metabolism, and biosynthesis of type II polyketide backbone pathways were shown in Group D2 (Figure 9C). It is interesting to note that a new functional metabolic pathway profile was observed in both groups at week 24. A higher proportion of histidine metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis; citrate cycle (TCA cycle, tricarboxylic acid cycle); glyoxylate and dicarboxylate metabolism; glycerolipid metabolism; carbon fixation pathways in prokaryotes; and oxidative phosphorylation for amino acid, carbohydrate, lipid, and energy metabolism was shown in Group D1. In addition, a high prevalence of the biosynthesis of antibiotics, biosynthesis of secondary metabolites, carbon metabolism, and pantothenate and CoA biosynthesis was observed. In contrast, a high prevalence of pathways related to carbohydrate metabolism, such as amino sugar and nucleotide sugar metabolism, fructose and mannose metabolism, galactose metabolism, glycolysis/gluconeogenesis, pentose phosphate pathway, and starch and sucrose metabolism; a high capacity for streptomycin biosynthesis, sulfur metabolism, peptidoglycan biosynthesis, glycerolipid metabolism, and polyketide sugar unit biosynthesis; and a high ability for xenobiotics biodegradation, including chloroalkane and chloroalkene degradation, naphthalene degradation, and polycyclic aromatic hydrocarbon degradation, were described for Group D2. ( Figure 9D). ## 3.5. Metabolic Status and Immune Cell Populations Profiling in VAT To evaluate the relationship among the changes detected in the GM composition, immune cells phenotype in the VAT, and metabolic markers, we analyzed four mice per group that were randomly sacrificed after 24 weeks post-differential feeding. Regarding the metabolic state, it can be seen in Figure 10 that the leptin levels in Group D2 were higher than those in Group D1, whereas the levels of adiponectin did not show significant differences between the groups. Additionally, a significant increase in the total cholesterol values was observed in Group D2 compared with Group D1, which could be attributed mainly to a higher level of HDL-cholesterol particles. The triglyceride levels were also higher in Group D2. No other statistically significant changes were observed in the rest of the parameters evaluated, i.e., glucose, LDL-c, AST, and ALT (Figure 10A–I). Furthermore, Group D2 presented higher body and VAT weights compared with Group D1 (p-value = 0.0039 and 0.0007). Supplementary Table S4 shows the statistical comparisons of the metabolic parameters and body and VAT weights. The characterization of immune cells in the VAT showed that mice fed with diet D2 had a significantly lower proportion of cells of myeloid lineage (CD11b+), total macrophages (CD11b+ F$\frac{4}{80}$+), and pro-inflammatory M1 macrophages (CD11b+ F$\frac{4}{80}$+ CD206-CD11c+) compared with those fed with diet D1. A marked decrease in ROS production was detected in all of these cells and a similar pattern was found in CD36+ expression, indicating an anti-inflammatory microenvironment in the VAT of group D2. No significant difference in the prevalence of anti-inflammatory M2 macrophages (CD11b+ F$\frac{4}{80}$+ CD206+ CD11c−) was observed. ( Figure 11). Supplementary Table S5 shows the statistical comparison of the cytometry parameters. In order to determine whether there was a relationship between metabolic parameters, immune cells present in VAT, and the bacterial genera of the GM, we performed a correlation analysis among these attributes. Figure 12 shows the correlation graphs for each of the variables studied. It can be seen that the abundances of Lactobacillus and Ligilactobacillus were negatively correlated with pro-inflammatory immune parameters, such as ROS production by total leukocytes and macrophages, M1 macrophages, and CD11b+ cells. Similar results were found for Anaerostipes, Anaerovorax, Christensenellaceae R-7 group, *Eubacterium nodatum* group, Lachnoanaerobaculum, Lactobacillaceae HT002, Lachnospiraceae ASF356, Lachnospiraceae UCG-004, Negativibacillus, Oscillospiraceae NK4A214 group, and Peptococcus. In contrast, Bilophila, Anaeroplasma, Alistipes, Lachnospiraceae GCA-900066575, and Lachnospiraceae FCS020 group were positively correlated with ROS production by immune cells in VAT. Additionally, Negativibacillus, Anaerotruncus, Lactobacillus, *Eubacterium nodatum* group, Lachnospiraceae ASF356, Anaerovorax, Peptococcus, Anaerostipes, and Lachnospiraceae UCG-004 were negatively correlated with the prevalence of pro-inflammatory M1 macrophages in VAT, while Rikenellaceae RC9 gut group, Alistipes, and Lachnospiraceae GCA-900066575 were positively correlated. The abundances of Alistipes and Lachnospiraceae GCA-900066575 were correlated inversely with the mice body and VAT weights. Moreover, these genera plus Rikenellaceae RC9 Gut Group were negatively correlated with the leptin levels. In contrast, the abundances of Butyricicoccaceae UCG-009, Candidatus Saccharimonas, Harryflintia, Lachnospiraceae AC2044 group, Lachnospiraceae ASF356, Lachnospiraceae UCG-004, Lactobacillaceae HT002, Lactobacillus, Monoglobus, Negativibacillus, Peptococcus, and Ruminococcaceae Incertae Sedis were positively correlated with the body weight and leptin levels. Anaerostipes, Christensenellaceae R-7 group, *Eubacterium nodatum* group, Harryflintia, Lachnoanaerobaculum, Lachnospiraceae ASF356, Lachnospiraceae UCG-004, Lactobacillaceae HT002, Lactobacillus, Ligilactobacillus, Negativibacillus, and Oscillospiraceae NK4A214 group were positively correlated with some of the lipid levels studied (TC, HDL-c or TG). Only Ruminococcaceae Incertae Sedis was correlated with LDL-c. Odoribacter, Anaeroplasma, Prevotellaceae NK3B31 group, Eubacterium eligens group, Angelakisella, Bilophila, and Lachnospiraceae FCS020 group showed a significant negative correlation with the glucose levels, unlike the genus Muribaculum, which showed a positive correlation. Supplementary Table S6 presents the correlation coefficient for variables showing significant correlations. ## 4. Discussion There is increasing evidence that the GM plays a fundamental role in the regulation of homeostatic mechanisms and metabolism to exert either beneficial or detrimental effects on the host’s health. Different studies have shown that the qualitative and quantitative composition of the diet is a key factor modulating the host microbiota structure and function, or leading to gut dysbiosis, which may impact the development or prevention of certain NCDs [18]. Indeed, diet influences the composition of the microbiota, providing nutrients for both the host and the gut bacteria [44]. In this context, the aim of this study was to analyze the effect of the diet’s composition on the development of obesity, GM structure, and immune metabolic response on VAT, focusing on the fatty acids and omega-3 content. We observed that, after a feeding period of 12 and 24 weeks, mice fed with diet D2 showed a significant increase in body weight and obesity. Remarkably, these results reveal that it is feasible to induce obesity with a considerably lower fat content than that traditionally used in HFD models, generating an experimental model and changes that better reflect the biological conditions leading to human obesity [22]. Besides contributing to the development of obesity through the first 12 weeks, diet D2 generated significant changes in the GM composition, resulting in an increase in Firmicutes and a decrease in Bacteroidota, which is in agreement with findings reported previously [7,13,14,45,46]. In addition, other differences previously reported, such as increases in Campylobacterota [47], Cyanobacteria [48], Deferribacterota, and Desulfobacterota [49,50], were evidenced. These taxa are considered harmful or potentially pathogenic, as they favor the development of inflammation and alter the intestinal microenvironment, generating changes in intestinal permeability, enabling, in turn, the development of metabolic endotoxemia [49,51,52]. When analyzing, at the genus level, the bacteria present, we observed that group D2 showed a greater abundance of taxa involved in fiber digestion contributing to the production of SCFAs, including Eubacterium eligens group, *Eubacterium nodatum* group, Lachnospiraceae AC2044 group, Prevotellaceae group NK3B31, Ruminococcaceae UBA1819, among others. Furthermore, we found that mice with a higher dietary fat intake had higher abundances of Oscillibacter, Harryflintia, Mucispirillum, Flavonifractor, and Anaerotruncus. These bacteria have been related to inflammatory processes and the development of different chronic diseases in numerous reports. Lam et al. reported a significant increase in the abundance of Oscillibacter in HFD-fed mice compared with LFD-fed mice. At the same time, these changes were associated with weight gain, as well as being negatively correlated with gut permeability [53]. Similar results have been demonstrated by Jo et al., who also reported an increase in Harryflintia under a HFD [54]. On the other hand, an increase in Mucispirillum, a potentially pathogenic genus, has been reported in different conditions associated with gut inflammation [55] and related to HFD [56]. Additionally, an increase in the abundance of Flavonifractor and a decrease in the Christensenellaceae family have been associated with the development of affective disorders in humans; these findings are also associated with greater oxidative stress and low-grade systemic inflammation [57]. Anaerotruncus, a butyrate producer, exhibited higher abundance in mice fed with diet D2; to note, this genus has also been associated with the development of obesity [58]. Overall, these findings could explain, at least in part, some of the potential mechanisms of obesity-associated dysbiosis, which involve increased ability to harvest and store energy from dietary components, mainly exacerbated ability to produce SCFA [13], leading to increased intestinal permeability and inflammation in this experimental model, as evidenced by the presence of a cellular infiltrate rich in pro-inflammatory M1 macrophages and a low number of anti-inflammatory M2 macrophages in the VAT. Overall, these findings show that most of the changes produced in the GM by this medium-fat-content diet are compatible with the previously described obesity-associated dysbiosis. With regard to mice fed with diet D1, they showed a dominance of mainly SCFA-producing taxa and lactic acid producers, both considered beneficial bacteria. Surprisingly, a higher prevalence of Bilophila and *Desulfovibrio* genera was also observed, contrary to previous reports, where levels of Bilophila wadsworthia, a sulfite-reducing pathobiont associated with increased intestinal inflammation, were found when mice were fed a diet enriched with milk fat [59]. Similar results were presented by Shen et al., where mice fed with HFD ($60\%$ of energy from fat; $95\%$ lard and $5\%$ soybean oil) had a greater abundance of three types of sulfidogenic bacteria (Desulfobacter spp., Desulfovibrio spp., and Bilophila wadsworthia) in colonic mucosa compared with mice fed with LFD ($10\%$ of energy from fat; $55\%$ soybean oil and $45\%$ lard) after 20 weeks of feeding [20]. It has been postulated that sulfidogenic bacteria can contribute to diminished epithelial integrity and increased intestinal permeability, possibly through the production of the pro-inflammatory and genotoxic gas hydrogen sulfide [20]. In contrast, a higher prevalence of the genus Muribaculum, associated with intestinal barrier function markers, was also detected [60]. Interestingly, at week 24, the changes observed in the composition of the GM in Group D2 were different to the alterations described earlier. In line with different reports, these findings may be attributable to the sustained dietary intake of omega-3; we detected a correction of the Firmicutes and Bacteroidota abundances, although the differences between groups D1 and D2 were not statistically significant. Su et al. showed that the contribution of high doses of PUFAs, especially EPAs and DHAs, reversed the changes produced by HFD in the abundance of Firmicutes and Bacteroidota within a period of 18 weeks [61]. Additionally, mice fed with D2 presented an increase in the abundances of certain bacterial genera, such as Lachnospiraceae AC2044 group, Lachnospiraceae ASF356, Lachnospiraceae UCG-003, and Lachnospiraceae UCG-004, which are related to the production of SCFAs, and a decrease in the abundance of Faecalibacterium. In our cohort, we also observed an enrichment of Anaerostipes, one of the most abundant butyrogenic bacteria of the healthy microbiota and a high consumer of lactate in the colon [44,62]. Remarkably, we found greater abundances of Akkermansia and Lactobacillus compared with the GM from mice fed with D1; the former has the ability to improve the intestinal microenvironment, increasing the thickness and maintaining the barrier function of the intestinal mucosa [63]. Additionally, it has been associated with weight loss by controlling the expression of genes related to fat metabolism [64]. This is in agreement with a report by Watson et al., demonstrating that the administration of omega-3 PUFAs supported an increase in the abundances of the Clostridiaceae, Sutterellaceae, and Akkermansiaceae families, among other changes that were reversible after a washout period [65]. Similar results were found when examining the abundance of Lactobacillus, which is known to decrease intestinal inflammation and provide competitive resistance against pathogens [65,66]. The different impact of diet over time observed in our study is probably due to the fact that the proportion of the saturated and/or omega-6 fatty acid component of D2 would favor the growth of bacteria associated with the development of metabolic endotoxemia throughout the first 12 weeks of differential feeding, favoring the development of obesity and potential associated metabolic disturbances. Later, throughout weeks 12 and 24, the effect of omega-3 fatty acids became predominant, favoring the growth of bacteria with probiotic potential, which would contribute to controlling the intestinal inflammation, modulating both metabolism and the immune system, as observed by the presence of an anti-inflammatory environment in VAT [57,61]. Further studies to confirm these considerations are anticipated. Interestingly, the genera Harryflintia, Lachnospiraceae AC2044 group, Lachnospiraceae ASF356, Mucispirillum, Ruminococcaceae UBA1819, and Tyzzerella could be considered a microbial signature for GM in mice fed with a fatty-acid-rich diet, as they presented the same distribution profile in the differential analysis between diets over time. Our study also explored the metabolic activities of GM from Groups D1 and D2; the differential feeding generated distinct functional profiles in each group at different times, indicating that the content of dietary fatty acids influenced the functional profile of the microbiota in a time-dependent manner. However, knowledge of the connections between omega-3 and the GM metabolic activities is still limited [44]. Even so, when evaluating the influence of an omega-3-supplemented fat diet, we found interesting effects on metabolic parameters and on the modulation of the immunological microenvironment in VAT. It is very well known that the accumulation of AT in obesity is characterized by changes in the circulating levels of various adipokines, such as leptin and adiponectin [67]. Leptin affects both endocrine functions and different aspects of the immune response; it has been demonstrated that elevated leptin in obesity contributes to a low-grade inflammatory state [68], acting on the regulation of T cells, macrophages, and increasing the production of pro-inflammatory cytokines and ROS [68,69,70]. In contrast, adiponectin, an anti-inflammatory adipokine, decreased in obesity, acts as an insulin-sensitizing hormone in muscles and the liver; low levels of adiponectin contribute to peripheral insulin resistance [71]. Our results showed high levels of leptin at week 24; however, the comparable levels of adiponectin in Groups D1 and D2 could explain the significant increase in body weight in Group D2, almost double that of their counterpart, without the development of metabolic alterations for carbohydrates or for the liver enzymes AST and ALT. In agreement with these results, Chacińska et al. demonstrated that PUFAs can prevent the development of insulin resistance in response to high-fat feeding and can regulate the expression and secretion of adipocytokines in animal models [72]. Finally, the considerable increase in HDL-c levels in Group D2 was attributable to the intake of omega-3, as described by different authors both in humans and animal models [73,74,75,76]. Although obesity is characterized by the inflammation of AT, with an important infiltrate of mainly pro-inflammatory M1 macrophages [5,6], our findings show that the VAT of mice fed with diet D2 presented lower numbers of myeloid cells, lower total and M1 macrophages infiltration, and decreased production of ROS compared with mice fed the control diet. No differences in the percentage of anti-inflammatory M2 macrophages were found. Overall, these results show that omega-3 generates an environment with anti-inflammatory characteristics in the VAT, maintaining its architecture and functionality, which is reflected by the adiponectin levels found. This is in agreement with previous reports [77]. Finally, we were able to corroborate that the abundance of certain bacterial genera in the GM was significantly correlated not only with the presence of different cell populations in the VAT, but also with a series of metabolic parameters. It is interesting to remark here that the most outstanding finding of this analysis is the negative correlation found between the abundance of Lactobacillus and Ligilactobacillus with the production of ROS by total leukocytes, CD11b+ cells, and M1 macrophages. It is important to note that these genera presented differential abundances at week 24 after feeding D2, showing that the effect of long-term intake of omega-3 on the modulation of the intestinal microbiota favored immunomodulation in VAT. In this context, Huang et al. demonstrated that Lactobacillus-induced anti-inflammatory macrophages associated with REG3γ in the intestinal lamina propria may play a role in adipose tissue homeostasis and be involved in high-fat-diet-mediated resistance to obesity [78]. Regarding the Christensenellaceae family, which also increased in Group D2, it has been shown that certain species have powerful immunomodulatory properties [79], correlating negatively with ROS production by immune cells in VAT, as well as intestinal inflammation [79,80], although further studies should be performed to confirm these results. On the other hand, Alistipes and Lachnospiraceae GCA-900066575 showed an inverse correlation with the mice body and VAT weight. This has been also reported in humans by Tavella et al., who stated that a high abundance of Alistipes was associated with a lower proportion of VAT and healthier metabolic profile in older adults [80]. Additionally, Pesoa et al. showed that the abundance of certain species of the genus Alistipes, such as *Alistipes shahii* and Alistipes sp., was significantly lower in obese subjects in comparison to normal-weight subjects [81]. In contrast, other genera associated with metabolic endotoxemia or the high production of SCFA were correlated positively with body weight, as has been demonstrated by others [13,54]. Additionally, different findings suggest that the GM has the capacity to modulate the blood lipid composition through distinct mechanisms, such as microbial products or bile acid metabolism regulation [82,83,84]. We found that Rikenellaceae RC9 Gut Group and Oscillospiraceae UCG-003 were correlated inversely with the triglyceride level, which is in agreement with previous findings [85]. Moreover, we observed that Lactobacillus was correlated positively with the TC, TG, and HDL-c levels, which is in opposition to reports where mice treated with probiotics, *Lactobacillus curvatus* alone or together with Lactobacillus plantarum, fed with a HFD showed reduced cholesterol in the plasma and liver [86]. In addition, Lachnospiraceae UCG-004 also showed a positive correlation with HDL-c, similar to results reported by Lan et al. in the Chinese population [87]. Taken together, these results suggest that the administration of a diet with medium amounts of saturated fat supplemented with omega-3 fatty acids contributed to the development of obesity, associated with specific changes in the composition and diversity of the intestinal microbiota, metabolic pathways profiles, and VAT immuno-metabolism in a time-dependent manner. The stabilization of weight gain with preserved metabolic state noted by week 24 after differential feeding was probably due to beneficial changes in the intestinal microbial communities, such as the increased abundance of probiotic bacteria, such as Lactobacillus and Ligilactobacillus, promoted by the sustained intake of omega-3 PUFAs, which, in turn, contributed to the generation of an anti-inflammatory microenvironment in the VAT with a marked decrease in pro-inflammatory cells and ROS production. Despite these findings, our study has some limitations: the sample size to determine the microbiota composition, metabolic markers, and immune cell profile was small ($$n = 8$$ and $$n = 4$$), respectively. On the other hand, we only analyzed the bacterial taxonomy up to the genus level; thus, it was possible that information on the existence of some species/strains that could be considered microbial biomarkers associated with the contribution of omega-3 is missing. The results obtained do not allow us to determine the mechanism underlying the relationships among nutrition, GM, and immune-metabolism. These observations need further validation by performing studies of metabolic parameters and immunological profiles in VAT at different time intervals and considering a diet of medium fat composition without omega-3 supplements. ## 5. Conclusions Remarkably, these results reveal that it is feasible to induce obesity with a considerably lower fat content than that traditionally used in HFD models, generating an experimental model and changes that better reflect biological conditions contributing to human obesity. The constant and sustained administration of omega-3 fatty acids induced specific changes in the GM composition, mainly with increases in Lactobacillus and Ligilactobacillus species, which, in turn, modulated the immune metabolic response of AT in this mouse model of obesity. The identification of different taxonomic signatures associated with the healthy functionality of VAT and metabolic state in obesity could be a new, promising tool to design treatment or prevention strategies for obesity and associated comorbidities, focusing on the modulation of the intestinal microbiota through the consumption of omega-3 fatty acids. ## References 1. 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--- title: A Multi-Label Detection Deep Learning Model with Attention-Guided Image Enhancement for Retinal Images authors: - Zhenwei Li - Mengying Xu - Xiaoli Yang - Yanqi Han - Jiawen Wang journal: Micromachines year: 2023 pmcid: PMC10054796 doi: 10.3390/mi14030705 license: CC BY 4.0 --- # A Multi-Label Detection Deep Learning Model with Attention-Guided Image Enhancement for Retinal Images ## Abstract At present, multi-disease fundus image classification tasks still have the problems of small data volumes, uneven distributions, and low classification accuracy. In order to solve the problem of large data demand of deep learning models, a multi-disease fundus image classification ensemble model based on gradient-weighted class activation mapping (Grad-CAM) is proposed. The model uses VGG19 and ResNet50 as the classification networks. Grad-CAM is a data augmentation module used to obtain a network convolutional layer output activation map. Both the augmented and the original data are used as the input of the model to achieve the classification goal. The data augmentation module can guide the model to learn the feature differences of lesions in the fundus and enhance the robustness of the classification model. Model fine tuning and transfer learning are used to improve the accuracy of multiple classifiers. The proposed method is based on the RFMiD (Retinal Fundus Multi-Disease Image Dataset) dataset, and an ablation experiment was performed. Compared with other methods, the accuracy, precision, and recall of this model are $97\%$, $92\%$, and $81\%$, respectively. The resulting activation graph shows the areas of interest for model classification, making it easier to understand the classification network. ## 1. Introduction The retina is the light-sensitive layer within the optic nerve tissue on the inner surface of the eyeball. Retinal damage caused by various diseases can eventually lead to irreversible vision loss. With population aging becoming a major demographic trend worldwide, the number of patients with retinal diseases such as age-related macular degeneration (AMD) and diabetic retinopathy (DR) will increase year by year [1,2,3]. Other retinal diseases, including retinal vascular occlusion, hypertensive retinopathy, and retinitis, are important causes of visual impairment. Vision loss can be avoided in most cases if it is diagnosed and treated early in the initial stages. Therefore, more precise screening protocols are needed for the early treatment of high-risk groups to reduce stress on families and the socioeconomic burden of patients with vision loss caused by retinal disease. Screening using fundus images is generally applicable to patients with fundus diseases. With the improvement of image classification network performance in the field of computer vision [4,5,6], fundus image classification tasks often include the classification of single diseases, such as DR, AMD, and glaucoma disease staging [7,8,9] and multi-disease fundus image classification [10]. Networks commonly used for fundus image classification include Alex Net, VGG Net, ResNet, and EfficientNet. By fusing the training results of multiple models, it can not only learn more features but can also improve the accuracy of the overall model, which is suitable for multi-classification networks. Due to the complexity of fundus diseases, difficulties in the classification of multi-disease fundus images always exist. Firstly, the differences between different fundus images are very slight, and the same fundus lesions are often included in multiple categories. Secondly, the training data are seriously uneven, and some disease datasets are private. Due to the above reasons, it is very difficult to achieve global classification results for multi-disease fundus images. The number of categories in the RFMiD multi-disease fundus image dataset is 46. For neural networks, the larger the number of categories, the poorer the classification performance [11]. Thus, it is necessary to use the optimization method of neural networks to improve the accuracy and other indicators. For example, by improving activation functions, batching, transfer learning, ensemble learning, and model fusion methods. However, the model fine-tuning technique utilized in transfer learning will ignore diseased areas, which have a major impact on classification outcomes, and this leads to model over-fitting. Diseases with a large patient base and a large amount of public data are diabetic retinopathy, glaucoma, and cataracts, while there is very little data for retinal pigment epithelial changes (RPEC), retinitis choroiditis (CRS), and other diseases. Insufficient model learning results in the problem of high overall classification accuracy but low single-disease classification accuracy. Data augmentation methods amplify the amount of data through transformations. Common methods are folding, rotating, cropping, translation, and adding noise. In the random cropping method, background pixels may be included that are independent of the lesion area, affecting the model’s ability to extract features. Therefore, the key to multi-disease fundus image classification is how to improve the classification accuracy of each disease when the dataset is unevenly distributed, and its amount is small. In view of this, this paper proposes an integrated network multi-disease classification model based on Grad-CAM [12,13,14] data enhancement to improve classification accuracy on uneven datasets. The gradient-weighted class activation mapping (Grad-CAM) generated by a convolution neural network is used as the data enhancement module. ## 2.1. Fundus Image Classification Multi-layer convolution kernels are used to extract image features such as color and texture, which are shallow features, while deep features include more abstract aspects when utilizing deep learning for fundus image classification tasks. Better extraction and identification of these features is the key to improving classification network performance. Attention modules are commonly added to the network to help the model pay more attention to the lesion area on the fundus image. According to studies on the attention module, they can be broadly split into space-level and channel-level attention mechanisms [15], which have applications in various tasks, such as image classification and segmentation [16,17]. Xi Xu et al. [ 18] utilized the channel attention mechanism in combination with the maximum mean difference to extract fundus image features from glaucoma patients, which can flexibly adjust the input data to focus on the key areas for glaucoma classification. Liu et al. [ 19] designed attention-based convolutional neural networks (CNNs) for glaucoma detection, which, unlike other attention-based CNN methods, are also visualized as local lesion areas to improve the performance of glaucoma detection. Lin et al. [ 20] fused input images and lesion information using attention-based mechanisms to identify diabetic retinopathy. The detection model can learn the weights between the original image and the lesion information, reducing the impact of missing annotations. Jun et al. [ 21] proposed a fine-grained image classification based on attention-induced image enhancement, which knows the image enhancement process through attention maps and studies the impact of image enhancement on the classification network. Tao et al. [ 22] used an attention map as a guide and cropped and down-sampled the images to reduce the background noises introduced in the process. Guo Wenming et al. [ 23] used a class activation map to enlarge and crop the image attention area, which guided the model to learn more subtle feature differences and improve the model’s feature extraction ability. In addition to adding modules to the network, other deep learning techniques have also made great progress. For example, dropout can reduce the risk of overfitting by introducing regularization. The rectified linear unit (ReLU) solves the problem of gradient disappearance or explosion to some extent, making deeper networks easier to train. Batch normalization (BN) speeds up the network training process. Global average pooling (GAP) significantly reduces the total training parameters [24,25] and effectively reduces the risk of overfitting. J. He et al. [ 4] proposed an attention-based feature-weighted fusion network, which extracts the features of both fundus images through ResNet and classifies them after the feature fusion module. The network can classify 8 types of fundus images with an accuracy of 0.934, but a lower kappa value indicates that more samples have been misclassified. Dominik et al. [ 26] used ensemble learning to combine the prediction results of several heterogeneous deep convolutional neural network models and used cross-validation for data training, which increased the accuracy and reliability of predictions. Although the existing methods have achieved good results in extracting fundus lesion features [27], the data volume still affects the classification performance of the network, and the classification effect of the network cannot be visually analyzed. Different from the above methods, this paper proposes a data enhancement method guided by Grad-CAM visual attention based on the integrated neural network, which amplifies the fundus image dataset in a targeted manner, helps the model learn rich subtle features, and improves recognition accuracy. ## 2.2. Data Enhancement In Zalier’s [28] deconvolution method, the accuracy of the classification network is affected by occlusion, rotation, and enlargement of the input images, so basic data augmentation using the above method can improve the network’s performance. Guo Fan et al. [ 29] used 4854 fundus images in the experimental data, and the dataset was enriched by random contrast, random brightness, random gamma transform, random saturation, random cropping, random rotation, and horizontal flipping to increase sample diversity. Wu Xue et al. [ 30] used translation, flip, and rotation methods to enhance the data of positive samples and compared the data to enhance the network’s performance before and after. It was found that the data-enhanced network can gradually restrain, reducing the risk of overfitting. Tan Run et al. [ 31] used semantic information to cut the original image to achieve data enhancement, and the enhanced semantic type of image paid more attention to the local detail information of the classification target to further improve the classification accuracy. Xu et al. [ 32] proposed a local attention network to process the cataract classification task, which improved the performance of cataract classification by acquiring cataract identification features such as the optic disc and the vascular region through local attention. ## 3. Methodology The model of the multi-label classification method is shown in Figure 1. The training set is input to the convolutional network to extract features to obtain the feature map, and the Grad-CAM map is constructed using the feature map and the real label. Using the attention mechanism of the Grad-CAM graph, the original image is cropped to generate different training images, which are input into two convolutional networks for training. Finally, the outputs of the two networks are fused to obtain the final classification result. The most advanced medical image classification technique is the deep convolutional neural network model. In it, the hyperparameter setting and the choice of model structure highly affect the results of the computer vision task. Therefore, the model is a classifier for multi-label labeling of abnormal images. The model shown in Figure 1 combines two different types of CNN networks, VGG16 and ResNet50, and is represented as BaseModel1 and BaseModel2, respectively. ## 3.1. Data Enhancement The earliest visualization method used was to introduce deconvolution into the original network to visualize the feature map. However, due to the need to change the network structure and large amounts of computation, class activation mapping was introduced as a new classification network visualization method. In the literature [33], it was proposed that each layer of a convolutional neural network will provide the location information of the target, but it disappears after passing through the fully connected layer. Using global average pooling (GAP) instead of the fully connected layer not only reduces the number of parameters but also preserves location information. Guided backpropagation in combination with gradient-weighted class activation mapping is used to produce high-resolution detail. Grad-CAM [10] is a general form of CAM that can be applied to any deep learning model with a convolutional structure. Usually, the last convolutional layer can be selected to calculate Grad-CAM. Suppose the output mapping of the last convolutional layer is denoted as Ak, where k is the number of these output maps. The final Grad-CAM can be calculated as follows:[1]wkc=1Z∑$i = 1$W∑$j = 1$H∂yc∂Aijk [2]IGrad−CAMc=ReLU(∑$k = 1$Kwkc⋅Ak) where yc represents the scores of class c before the softmax layer. The size of *Ak is* W×H. Pass yc to each Ak of differential operations, and wkc is obtained because the class c and Z mapping Ak are weighted as a normalization factor. In mapping Ak after the weighted summation, the activation function of the linear modified unit (ReLu) is applied. In addition, by modifying ReLu gradient backpropagation, the fraction less than 0 is not propagated, and only the fraction higher than 0 is propagated. As a result, when the first convolution layer is reached, the gradient acquired is the gradient that is used in further ReLu activation. At this point, we display the gradients and determine which region is important in the network; a Guided Grad-Cam IGuide−Grad−CAMc for each prediction result is calculated by multiplying the backpropagation and the class activation map. [ 3]IGuide−Grad−CAMc=IGuide−Backpropc⋅IGrad−CAMc To give the results of the final integrated Guided-Grad-CAM multi-label classification, all of the Guided-Grad-CAMs are combined using normalization. [ 4]IGuide−Grad−CAM=1Z∑$c = 1$CIGuide−Grad−CAMc where Z represents the normalization factor and C represents the total number of categories classified. Guided-Grad-CAM captures the most critical attention regions of a category, which were initially applied to CNN visualization and target localization under weakly supervised conditions, and this paper uses it to generate cropped images of attention guidance. In order to obtain the local area of fundus images with regard to Guided-Grad-CAM, we devised a way to identify the lesion area. Set the masking threshold to θ∈[0,255]; MC represents the image after threshold segmentation:[5]MC={1,IGuide−Grad−CAM>θ0,others Because x,y represent the upper-left coordinates of the smallest circumscribed rectangle of the mask, respectively, h,w represent the height and width of the rectangle, respectively; then, the four-point coordinates of the rectangular area are, respectively, [x,y+h,x+w,y]. As shown in Figure 2, the attention area is obtained by superimposing the mask with the original image, and it is enlarged to the original image size after up-sampling to ensure that it is consistent with the input dimension of the model. Figure 2 shows the process of extracting the image lesion area by the Grad-CAM method. Figure 2a is the fundus image with black edges removed, Figure 2b is the Grad-CAM image of the fundus image, Figure 2c is the superposition of Figure 2a,b, which is used to show the position of Grad-CAM on the original image, Figure 2d is the lesion area cut according to the position of red area in the Grad-CAM image, Figure 2e is the position of the lesion area in the Figure 2a, and Figure 2f is to adjust the length and width of the image in order to input the image into the model. ## 3.2. Feature Fusion The above enhanced data are fed into the classification networks of BaseModel1 (VGG16) and BaseModel2 (ResNet50). The global average pooling layer is added after the last convolutional layer so that both networks can distinguish the local features of the enhanced data. The two networks are able to extract fundus image features at different depths, which can complement each other to improve predictive performance. The prediction scores of the two networks are combined to obtain the final classification result Gf:[6]Gf=λ×G1+σ×G2 where G1 and G2 indicate the classification results of BaseModel1 and BaseModel2, respectively; λ and σ indicate the weights of each component’s influence (λ+σ=1). ## 3.3. Loss Function Design Lin et al. [ 34] used weighted focal loss to make the model more focused on hard-to-classify samples when training by reducing the weight of easily classifiable samples, as follows:[7]FL(pc)=−αc(1−pc)γlog(pc) where pc is the probability that the class, c is the true value, γ is an adjustable focusing parameter (set to 2.0), and αc is the loss weight of class c. ## 4. Experimental Results and Analysis In order to verify the effectiveness of the proposed multi-label classification model, this paper performed experiments on the fundus image public dataset. The experimental results from previous studies are compared, and the contributions of the data enhancement algorithm and ensemble model are analyzed. Meanwhile, the classification results are visualized to verify the model’s ability to acquire lesion areas. ## 4.1. Experimental Datasets The Retinal Fundus Multi-Disease Image Dataset (RFMiD) consists of 3200 images with labels for 45 different diseases. The dataset is divided into 3 subsets: $60\%$ for the training set (1920 images), $20\%$ for the test set (640 images), and $20\%$ for the validation set (640 images). Each subset has 26 diseases labeled independently, and 19 other disease categories are combined and labeled “other”. This ultimately constitutes 28 categories for the classification of diseases. Figure 3 shows the histogram statistics of the number of images versus the number of disease categories in the RFMiD dataset, including the number of images for 23 diseases in the [10, 200] interval and the number of images for only 1 disease in the (580, 770] interval. Figure 4 shows the multi-label image information statistics, and the number of images with only 1 disease in the RFMiD dataset accounts for $55.72\%$, and the number of images with 2 or more diseases accounts for $23.38\%$. Table 1 lists the image distribution used for the training set. It can be seen from Figure 4 and Table 1 that the distribution of the image numbers of different categories is uneven, and most images have more than one disease label. ## 4.2. Experimental Parameter Setting The experiment was based on the Python and Tensorflow deep learning framework and used an RTX 2080Ti GPU to complete accelerated training. Considering the efficiency and complexity of the network and the cost of training, this study resized all the input images to 224 × 224. The training set was divided into two steps. The VGG16-based framework network was trained on the entire fundus image in the first step, and the local lesion features were extracted and cropped from the original image using Grad-CAM to obtain amplified data. In the second stage, the original dataset and the cropped image were further amplified with random brightness, random gamma transform, random saturation, random cropping, random rotation, and horizontal flipping. Data were fed into the integrated network of VGG19 and ResNet50 for training. The ImageNet [34] dataset was used to train both VGG19 and ResNet50. Transfer learning training, i.e., frozen architectural layers except for classification heads, and fine-tuning procedures utilizing unfrozen layers, were utilized in the fitting process. The transfer learning fit used Adam to optimize the initial learning rate 1 × 104 and was dynamically lowered to 1 × 107 (reduction factor 0.1) across 10 epochs. Validation set loss increased the learning rate without optimization after eight epochs. Furthermore, for the fine-tuning process, early stop and model checkpointing techniques were used, ending the operation after 20 epochs without improvement and saving the best model evaluated by the verification loss. The training strategy applied a bagging method based on five-fold cross-validation as ensemble learning, creating different models and training on different subsets of the training data. This approach not only allows for more efficient use of the available training data but also increases the reliability of predictions. This strategy yielded an integration of 10 disease label classifier models (2 structures, each with 5 folds). Finally, the weight parameters that appear in Section 2.2 (λ and σ) were set to (0.6 and 0.4), respectively. ## 4.3.1. Classification Performance Evaluation Figure 5 shows the loss function fit of the training and validation sets on the model, with it showing a downward trend. The loss of the validation set gradually exceeds the training set after 26 epochs of data. The lines were computed via locally estimated scatterplot smoothing and represent the average loss across all folds. The red areas around the lines represent the confidence intervals. Figure 6 shows the ROC curve for each disease type, and it can be seen that the ROC curve scores high regardless of the size of the dataset. The average area under the curve is 0.95. The high class imbalance between the situations indicated a significant problem in developing a reliable model, which is a complicated task in general. Our deployed up-sampling and class weighting approach showed a significant improvement in the classifier models’ prediction abilities. Although the majority of diseases can be correctly classified, the AUC of drusens (DN), optic disc cupping (ODC), and others does not exceed 0.9, which is due to the lack of images for these 3 diseases and their identification characteristics are ambiguous. Figure 7 provides a detailed analytical comparison of the proposed model with the metrics in other literature sources. ML-CNN [35] reached $100\%$ on Acc and $81\%$ on Prec. Wang et al. [ 36] achieved an Acc reach of $90\%$, with Prec and Recall reaching $66\%$ and $58\%$ in the ODIR2019 dataset, respectively. With the exception of Prec and Sen, our model outperforms the model proposed by Wang et al. [ 36]. Neha Sengar [37] designed an automated deep learning-based non-invasive framework to diagnose multiple eye diseases using an RFMiD dataset called EyeDeep-Net; the accuracy, precision, recall, and F1-score are $82\%$, $77\%$, $76\%$, and $76\%$, respectively. Ling-Ping Cen [38] developed a deep learning platform (DLP) capable of detecting multiple common referable fundus diseases and conditions by collecting 3 fundus image datasets, 3 groups of CNNs, and a Mask-RCNN which were applied to construct a 2-level hierarchical system for the classification of the 39 types of diseases and conditions. The accuracy, recall, AUC, and F1-score are $92\%$, $97\%$, $99\%$, and $92\%$, respectively. The proposed model has better accuracy, precision, recall, and specificity and a better F1-score than other existing models. The accuracy, precision, recall, AUC, and F1-score are $97\%$, $92\%$, $81\%$, $96\%$, and $86\%$, respectively. ## 4.3.2. Module Comparison Experiment In order to explore the influence of the above method on the final result, several experiments were performed on the RFMiD dataset. The experimental results are shown in Table 2. Without using any ensemble learning techniques, the accuracy rates obtained using the VGG16 and ResNet50 network models are $90\%$ and $92\%$, respectively. The method of ensemble learning is used to improve the accuracy of the model. In addition, the model uses the CAM-amplified dataset as the training set to improve accuracy and precision. ## 4.3.3. Visual Analytics Grad-CAM was able to recognize and emphasize the target lesions on the fundus image and used the well-trained multi-label classification model, as shown in Figure 8. It can be seen that for fundus images with lesions, Grad-CAM can locate these areas well and use image cropping to obtain key areas of the image, which can achieve the effect of expanding the dataset. ## 5. Conclusions In this paper, a multi-label classification model with interpretable Grad-CAM is proposed. Due to the limitations of ophthalmologist resources, simplifying data annotation can greatly increase the amount of valuable data available. In the fundus image labeling stage, this paper developed an attention mechanism for fundus image lesions and performed multi-label classification, which improved the efficiency of labeling work. In order to complete lesion detection on fundus images using the multi-label classification model, Grad-CAM is used to automatically outline each specific lesion area. The experimental results prove the effectiveness and accuracy of this method for disease classification and lesion detection. Furthermore, when fundus images accumulate, deeper lesions or features may be added as independent categories to our multi-label classification algorithm to achieve more accurate lesion locations using Grad-CAM. 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--- title: Effects of Steam and Water Blanching on Drying Characteristics, Water Distribution, Microstructure, and Bioactive Components of Gastrodia Elata authors: - Yong-Kang Xie - Xing-Yi Li - Chang Chen - Wei-Peng Zhang - Xian-Long Yu - Hong-Wei Xiao - Feng-Yin Lu journal: Plants year: 2023 pmcid: PMC10054799 doi: 10.3390/plants12061372 license: CC BY 4.0 --- # Effects of Steam and Water Blanching on Drying Characteristics, Water Distribution, Microstructure, and Bioactive Components of Gastrodia Elata ## Abstract In the current work, the effects of steam and boiling water blanching on the drying characteristics, water distribution, microstructure, and contents of bioactive substances of *Gastrodia elata* (G. elata) were explored. Results showed that the degree of steaming and blanching was related to the core temperature of G. elata. The steaming and blanching pretreatment increased the drying time of the samples by more than $50\%$. The low-field nuclear magnetic resonance (LF-NMR) of treated samples showed that the relaxation time corresponded to water molecule states (bound, immobilized, and free) and G. elata became shorter, which indicated a reduction in free moisture and increased resistance of water diffusion in the solid structure during drying. Hydrolysis of polysaccharides and gelatinization of starch granules was observed in the microstructure of treated samples, which was consistent with changes in water status and drying rates. Steaming and blanching increased gastrodin and crude polysaccharide contents and decreased p-hydroxybenzyl alcohol content. These findings will contribute to a better understanding of the effect of steaming and blanching on the drying behavior and quality attributes of G. elata. ## 1. Introduction Gastrodia elata Blume (G. elata) is a plant in the Orchidaceae family. Its Chinese name is Tian-ma, and its underground tuber has been used as a herb for treating headache, epilepsy, tetanus, vertigo, convulsion, and other nervous disorders for thousands of years in many Asian countries [1]. Modern medical research shows that G. elata contains phenols (such as gastrodin, p-hydroxybenzyl alcohol, etc.), sterols (β-sitosterol, etc.), organic acids (citric acid, succinic acid, etc.), polysaccharides, and other bioactive compounds [2]. Phenols, in particular, have anticonvulsant, analgesic, hypnotic, sedative, neuroprotective, and other effects [3]. According to *Chinese pharmacopeia* [4], gastrodin is widely considered the primary phytochemical compound responsible for the medicinal functions of G. elata tubers. In recent years, gastrodin and p-hydroxybenzyl alcohol have become the focus of active research aiming to evaluate the therapeutic value of G. elata due to their significant pharmacological activities [5]. Liu [6] suggested that G. elata polysaccharide is another essential bioactive substance. Since then, G. elata polysaccharides have received extensive attention worldwide, with other studies reporting various pharmacological activities, such as anticancer, antivirus, and neuroprotective effects [7]. Because of its many reported uses, G. elata is a promising candidate for multiple applications in the fields of drugs, food, and health products. Traditionally, freshly harvested G. elata tubers are soaked in water and washed to remove the surface dirt, boiled in water or steamed, and then dried. Steaming or blanching is an essential operation in its processing and is vital for quality formation. In addition, steaming or blanching treatment increases the content of gastrodin and prevents the browning of G. elata during drying by inactivating the polyphenol oxidase enzymes, which often trigger enzymatic browning reactions [8]. Previous studies have shown that the content of gastrodin in steamed or blanched G. elata is significantly higher than that in fresh samples [9]. In the steaming or blanching process, the degree of steaming or blanching is the crucial factor affecting quality. If G. elata is not thoroughly steamed or blanched, the precursor substances of gastrodin (the main active component) cannot be adequately transformed, resulting in a low content of gastrodin [10]. On the other hand, if G. elata is over-steamed, the epidermis of the tuber is damaged and starch is liquefied, which result in bioactive substance loss, longer drying time, and lower processing efficiency. In addition, over-steamed or over-blanched G. elata products have a red color after drying, which seriously affects the appearance. Therefore, it is important to determine the optimal degree of steaming and blanching for G. elata for the best quality and processing efficiency. Previous research on the steaming of G. elata has mainly focused on the optimization of the steaming process and the mechanisms underlying changes to the active components during the steaming process. Ning et al. [ 11] compared the active components of G. elata after steaming and blanching. They found that the contents of gastrodin, p-hydroxybenzyl alcohol, and parishin in G. elata material after blanching were lower those in the steamed samples. Qin et al. [ 12] studied the difference in quality among traditional blanched, steamed, and directly dried G. elata. The results showed that the contents of gastrodin, alcohol extract, and G. elata polysaccharide were the highest in the steamed samples, followed by the traditionally blanched samples, and lowest in the directly dried samples. These previous findings suggest that only steaming or blanching fresh G. elata can promote the formation of bioactive compounds, and the steaming method is more conducive in improving the content of active components. Studies have shown that steaming temperature, time, and pressure are important factors affecting the content of bioactive compounds in G. elata [13,14]. Meanwhile, steaming is a complex process that changes the chemical composition of G. elata tubers. Wang et al. [ 15] studied changes in seven bioactive compounds in G. elata during the steaming process. Their results showed that the content of each component tended to be stable after 60 min of steaming. During the steaming process, the parishin glycosides were incompletely hydrolyzed to produce gastrodin, citric acid, and other parishin glycosides. Different researchers have found different mechanisms underlying these transformations [16,17], which has made it difficult to guide industrial production. The literature lacks a detailed study on the water migration within the G. elata during the steaming and blanching process and its effect on drying characteristics. Therefore, the study was undertaken to conduct quantitative research on the degree of steaming and blanching in G. elata, followed by an understanding of the influence of steaming and blanching on its drying characteristics. Further, the rule of water migration during G. elata steaming and blanching was examined; the effects of steaming and blanching on the microstructure and on the contents of gastrodin, p-hydroxybenzyl alcohol, and crude polysaccharide of G. elata were studied. ## 2.1.1. Gelatinization Temperature of G. elata Powder Gelatinization is one of the most important properties of starch, reflecting its capacity to absorb water and expand. In the processes of steaming and water blanching, gelatinization of starch is also affected by other components. Therefore, understanding the gelatinization characteristics of G. elata powder is of practical significance in exploring the degree of steaming and blanching of G. elata. The gelatinization temperature of G. elata powder was around 66.15 °C (viscosity value 73 cp), according to the viscosity (Figure 1), consistent with the gelatinization temperature of G. elata tissue solution (64–70 °C) found by Xie et al. [ 18]. The gelatinization temperature of G. elata powder was lower than the gelatinization temperatures of other agricultural products, which was possibly due to the particle size and morphology of the starch molecules. G. elata starch showed irregular polyhedron morphology and belonged to very small particle starch [18], which was consistent with a particle size distribution range of 615~1483 nm and the average particle size of 1185 nm found by Li et al. [ 19]. In addition, Goering et al. [ 20] found that small-granule starch generally had a lower gelatinization temperature than large-granule starch. Meanwhile, there were different opinions, which suggested that small starch granules were harder to break and the molecular arrangement order was more difficult to destroy, so they were not easy to gelatinize. This showed that the gelatinization temperature of starch might be the result of a combination of many factors, rather than simply depending on the size of starch granules. Furthermore, Li et al. [ 19] found that the amylose content of G. elata accounted for $7.25\%$, the amylopectin content accounts for $92.75\%$, and the branching degree was 3.72. The lower gelatinization temperature of G. elata starch might also depend on the content of amylose and the branching chain length of amylopectin. The long branching chain of amylopectin could also mimic amylose and stretch to support the integrity and stability of the whole particle structure, thereby inhibiting the gelatinization of starch [21]. Guan et al. [ 22] found that compared with non-steamed G. elata, the content of amylose in steamed G. elata increased by 1.08-times that of amylopectin, and the degree of molecular crosslinking was increased by steaming. These results might also indicate that G. elata amylopectin was starch with high branching degree but a short branching chain. Therefore, the low gelatinization temperature of G. elata was due to comprehensive factors. ## 2.1.2. Relationship between Steaming and Blanching Degree and G. elata Central Temperature of the Cross Section with the Largest Diameter In the process of steaming or blanching, a proportion of white center in the section was used as an indicator of complete steaming or blanching. The steaming or blanching degree could be divided into three levels, namely, under-steamed, well-steamed and completely steamed. If the cross-section of G. elata had a white color area, it meant that it was under-steamed; if there was no white area or a little part of a white area in the cross-section, it meant that it had been steamed well; if there was no white area in the cross-section, it meant that it had been completely steamed. The ratio of white-color areas significantly decreased with increasing core temperatures, as shown in Table 1. When the real-time core temperature of G. elata was 45 °C, the white area in the center was $30.82\%$ for steamed and $20.56\%$ for blanched G. elata. When the real-time core temperature exceeded 60 °C, G. elata was thoroughly steamed or blanched, and the white area disappeared (the proportion of white area at the center was 0). A change in starch color mainly caused the color change in G. elata during steaming or water blanching. The temperature at which the white core area of G. elata disappeared was related to the gelatinization temperature of G. elata starch. When the real-time core temperature was 60 °C and the final core temperature was more than 66.15 °C (Figure 2), G. elata starch was gelatinized, and the section was completely free of white, indicating that G. elata was entirely steamed or blanched. When G. elata was steamed until a target temperature of 60 °C was reached in the core region, the sample was immediately removed from the steaming chamber; afterwards, the core temperature continued to increase to 72.0 ± 1.0 °C (Figure 2a). The continuous temperature rise in the core region was known as thermal inertia, which was because the outer region of the tuber had higher temperatures when the sample was removed from the steaming chamber, from which the heat was transported to both the core region through conduction and the environment through convection. Similarly, after removal of the G. elata sample from the boiling water when the core region reached 60 °C, the internal temperature increased to 70.0 ± 1.5 °C (Figure 2b). Further, when the real-time target core temperatures of G. elata samples reached 45 °C, 75 °C, and 85 °C and then removed from the steaming chamber or boiling water, the final core temperatures were 59.5 ± 0.5 °C, 80.5 ± 1.5 °C, and 88.0 ± 0.5 °C, respectively, for steaming, and 61.0 ± 1.5 °C, 81.0 ± 1.0 °C, and 87.5 ± 1.0 °C, respectively, for boiling. The results showed that the longer the heating time (that is, higher core temperature), the smaller the difference between the core temperature of G. elata and the heating temperature, indicating that a thermal equilibrium was approached. At the same time, it could also be found that the steaming or blanched degree of G. elata in Table 1 has a great relationship with the central temperature. The steaming or blanched degree could be quantified by monitoring the material temperature. ## 2.2. Effects of Steaming and Boiling Water Blanching on Drying Characteristics The drying time of fresh G. elata was significantly lower than that of G. elata samples after steaming and water blanching (Figure 3). As the core temperature increased, G. elata drying time increased and peaked at 75 °C then decreased with a further increase in core temperature. The drying times were 3.5 ± 0.5 h for fresh G. elata and 7.0 ± 0.5 h, 9.0 ± 0.5 h, 12.0 ± 0.5 h, and 8.0 ± 1.0 h, respectively, for samples steamed to core temperatures of 45 °C, 60 °C, 75 °C, and 85 °C. The drying time of G. elata samples steamed at 45 °C, 60 °C, 75 °C, and 85 °C increased by $50.0\%$, $157.1\%$, $242.9\%$, and $128.6\%$, respectively. In comparison, the drying times of hot-water-blanched samples to 45 °C, 60 °C, 75 °C, and 85 °C core temperature were 7.0 ± 1.0 h, 10.0 ± 0.5 h, 12.0 ± 1.0 h, and 6.0 ± 0.5 h, respectively. The drying time of G. elata samples steamed at 45 °C, 60 °C, 75 °C, and 85 °C increased by $50.0\%$, $185.7\%$, $242.9\%$, and $71.4\%$, respectively, relative to fresh G. elata samples. The drying mainly occurred in the falling rate stages, which suggested the dominating moisture transport mechanism during the hot air drying of G. elata was internal moisture diffusion. Fresh G. elata was dried significantly more rapidly than steamed or water-blanched G. elata. These results are consistent with the research of Xie et al. [ 18], who used high-temperature and high-humidity gas jet impingement steaming technology to treat G. elata and showed that, although steaming increased the material temperature, it also slowed the drying. G. elata has a high content of starch and other viscous substances. Steaming and boiling water blanching could destroy the grain structure of starch, promote the release of starch chains, and then enter the cytoplasm and tissue fluid. On the one hand, the molecular chain of amylopectin broke and generated short amylose. The short amylose pulled the broken amylopectin molecules and the original amylose molecules together through hydrogen bonds, forming a complex dense network structure (as shown in Figure 6C,M), which increased the molecular cross-linking degree and, thus, hindered the flow of water [22]. In addition, the high-viscosity starch also covered the surface of the dry material, which was additional resistance. On the other hand, in the gelatinization process of starch, the combination of water molecules and starch particles would also reduce the degree of freedom of water molecules, and it was not easy to remove water during the drying process [23]. When the central temperature was higher than 75 °C, the drying time of G. elata was shortened, which may be due to the excessive steaming or blanching of G. elata, resulting in cell damage, the loss of G. elata internal solutes, such as polysaccharide and starch, and the easier flow of water out of cells during drying. ## 2.3. Effects of Steaming and Blanching on Internal Water Distribution of G. elata T2 relaxation time has often been used to study the distribution of and changes in water in cells. When the water molecules within the solid matrix have a higher degree of freedom, they usually have higher values of T2, corresponding to peaks on the right side of the T2 spectrum. On the other hand, when the water molecules have a lower degree of freedom, meaning that they had stronger binding force with the solid matrix, they have lower values of T2 and appear on the left side of the T2 spectrum. According to the different status of water molecules, T21, T22, and T23 represent the bound water, intracellular water, and intercellular water, respectively. Figure 4 shows the CPMG distribution of fresh, steamed, and boiled G. elata samples before drying. It was found that the free water molecules had the largest peak in the spectrum, suggesting that free water was the dominating status in G. elata. Since the free water had higher fluidity, it had the longest relaxation time. Hot water blanching and steaming led to decreases in peak height and a shift to lower relaxation times to the left side. Similarly, Chen et al. [ 24] found that after a block of G. elata was steamed, free water evaporated, and the relaxation time moved rapidly toward lower relaxation times. Table 2 shows changes in relaxation time and relative areas of T2 peaks corresponding to fresh, steamed, and blanched samples. Atotal is the water signal amplitude area of G. elata, representing the water content. The water content of G. elata decreased after steaming and blanching (Table 2), consistent with the finding by Xie et al. 2021 that the loss rate of G. elata increased after steaming. The relative areas A21, A22, and A23 represented the relative contents of bound water, intracellular water, and free water, respectively. A21, A22, and A23 changed significantly after steaming. A22 and A23, in total, contributed $90\%$ of the total water content in the samples. Pretreatment led to increases in the relative area of A23 and decreased the relative areas of A21 and A22, which showed that the internal tissue structure of G. elata was destroyed after blanching and steaming, and the water diffused to the outside due to the internal and external pressure difference. The free water content also increased significantly. For G. elata materials, T21, T22, and T23 changed significantly, and the peaks moved to the left, indicating that the degrees of freedom of bound water, intracellular water, and intercellular water decreased after steaming and blanching, and it was difficult for water to exit the cells, consistent with the conclusion that blanching and steaming prolonged the drying time. A proton density diagram of the cross-section of the G. elata sample subjected to different steaming and blanching degrees is shown in Figure 5 with pseudo color. The color from blue to red represents the proton density in the sample from low to high. Fresh G. elata presents a high signal-to-noise ratio, and its water distribution could be clearly observed (Figure 5). The internal water distribution of fresh G. elata was uneven, and the water content gradually increased from the center to the edge. With an increasing core temperature of G. elata, the density signal of the central part of G. elata gradually increased, indicating that steaming and blanching led to the destruction of G. elata tissue structure. The edge water slowly diffused to the external environment, resulting in the uniformity of G. elata water. Steaming resulted in a more uniform distribution of water than blanching. ## 2.4. Effects of Steaming and Blanching on Microstructures The microstructure photographs of fresh, steamed, and blanched G. elata samples at different magnification (150× and 2000×) are shown in Figure 6. In fresh G. elata samples, the cells had an ordered and regular arrangement, and the cell membrane structure was complete. Furthermore, elliptical polysaccharide granules (150×) (Figure 3a) and irregular starch granules (2000×) (Figure 3b) were also observed in fresh G. elata cells. The diameters of G. elata starch granules were smaller, while the diameters of G. elata polysaccharide granules were larger. The starch and polysaccharide granules in this study were similar in shape and size to those observed in a previous study [18]. After steaming and blanching, the cell walls of G. elata were damaged, and some cells collapsed. The degradation of pectin in the middle layer may have led to the rupture of the cell walls, the softening of the tissue, and the loss of water in cells [25]. This result was consistent with the decrease in moisture content in the NMR signal amplitude after steaming and blanching treatment. In the low-magnification microstructure photographs (150×), it was observed that the elliptical polysaccharide disappeared with an increased core temperature of G. elata, resulting in the formation of intracellular mucus. However, the mucus disappeared when the core temperature of G. elata reached 80 °C. The cells were severely damaged, resulting in the loss of G. elata polysaccharide [26]. In high-magnification microstructure photographs (2000×), G. elata starch particles appeared to gradually gather together with increasing central temperature as G. elata starch began to gelatinize. When the core temperature exceeded the gelatinization temperature range of G. elata starch, the occurrence of G. elata starch particles decreased. When steamed or blanched to 85 °C, G. elata starch in cells disappeared. This was due to the liquefaction of G. elata starch after excessive steaming and blanching. In addition, during the process of steaming and water blanching, massive stickies adhered to cells, and it became difficult for water in the cells to migrate out of the G. elata tuber, resulting in an extension in drying time. When steaming and blanching were excessive, the lumps became less frequent or disappeared, and the water in the cells could easily migrate out, resulting in shortened drying time. ## 2.5. Effects of Steaming and Blanching on the Gastrodin, P-hydroxybenzyl Alcohol, and Crude Polysaccharide Content of G. elata Compared to fresh G. elata, gastrodin and crude polysaccharide content increased after steaming and blanching (Table 3). In contrast, the content of p-hydroxybenzyl alcohol decreased, consistent with a previous study on G. elata steaming. Gastrodin content increased first and then decreased with increasing central temperature. When the core temperature of steamed and blanched G. elata reached 75 °C, the content of gastrodin was the highest, at 3.09 mg/g dry matter and 3.26 mg/g dry matter, respectively. The p-hydroxybenzyl alcohol content decreased with increasing core temperature. When the core temperature of steamed and blanched G. elata was 85 °C, the content of p-hydroxybenzyl alcohol was the lowest, at 0.44 mg/g and 0.53 mg/g, respectively. The maximum reduction in p-hydroxybenzyl alcohol was $58.14\%$. The crude polysaccharide content first increased and then decreased with increasing central temperature. With increasing core temperature, the content of crude polysaccharide reached its maximum when G. elata was blanched and steamed to a core temperature of 60 °C. During steaming and blanching, gastrodin was hydrolyzed to produce p-hydroxybenzyl alcohol and sugar through β-glycosidase, while p-hydroxybenzyl alcohol was condensed into gastrodin without enzyme participation. With increasing temperature at the center of G. elata, β-glycosidase enzyme activity gradually decreased, inhibiting the enzymatic hydrolysis reaction, but the condensation reaction was not affected. Therefore, the condensation of p-hydroxybenzyl alcohol to produce gastrodin resulted in increased gastrodin content and decreased p-hydroxybenzyl alcohol content. The increase in gastrodin was not equal to the decrease in p-hydroxyl, due to the degradation reaction of parishin during steaming and blanching, resulting in the increased content of gastrodin after steaming. It could be seen from Table 3 that the crude polysaccharide of G. elata increased after steaming or boiling water blanching. On the one hand, because the detection method is based on glucose as the standard, the starch, cellulose, and other substances in G. elata cells hydrolyze during steaming and boiling water blanching to produce reducing sugar, which increased the content after determination. On the other hand, with increasing central temperature, the cells were broken and the sugar flowed out of the cells, which improved the extraction rate of crude polysaccharides from G. elata [27]. ## 3.1. Materials The fresh, first-class G. elata root samples (weighing 200–250 g per individual, length was 94–113 mm, width was 50–62 mm, thickness was 37–52 mm) used in this study were collected at the plantation base of Bijie, Guizhou Province, China. All G. elata samples were stored at 4 ± 1 °C and $90\%$ relative humidity before use. The sample’s moisture content before and after treatment was determined after drying in an oven at 104 °C until it reached a constant weight [4]. ## 3.2. Steaming and Hot Water Blanching Treatment Fresh G. elata samples were taken from the refrigerator and placed at room temperature for 6 h to allow them to reach room temperature. Before steaming or blanching, G. elata tubers were washed, and the surface water was removed using absorbent paper. Because of substantial variation in the sizes of G. elata of equal grade, the treatment time used to characterize the steaming or blanching degree had to be adjusted. Therefore, in the experiments, the core temperature was recorded at the cross-section of the maximum diameter of G. elata samples and used to characterize the degree of steaming. The temperature was measured using a T-type thermocouple (OMEGA Engineering Inc., Stamford, CT, USA) with an accuracy of 0.5 °C. The water in the steamer was heated by the electromagnetic furnace, and then the steam generated by boiling was used to steam the tubers of G. elata, so as to reach the predetermined target core temperature of 45, 60, 75, and 85 °C. For the hot water blanching experiments, the G. elata tubers were immersed in a thermostat water bath operated at 100 °C. After steaming and hot water blanching, all samples were cooled to room temperature quickly. The temperature sensor continuously monitored the core temperature of G. elata. All experiments were conducted under normal atmospheric pressure. ## 3.3. Hot Air Drying Experiments The fresh, steamed, and blanched G. elata samples were cut into 5 mm-thick slices and transferred to the hot air dryer. The air temperature was 60 °C, and the air velocity was 0.5 m/s. Then, the effects of different degrees of steaming or blanching on drying were studied. Drying was stopped when the moisture content of G. elata was lower than the safe moisture content ($12\%$ wet basis). During drying, the drying data were recorded at predetermined time intervals, and moisture ratio (MR) was calculated. MR was calculated using Equation [1] [28,29]:[1]MR=MtM0 where Mt represents the moisture content at drying time t on a dry basis (kg·kg−1); M0 represents the initial moisture content on dry basis (kg·kg−1). The drying rate (DR) was calculated according to Equation [2] [30,31]:[2]DR=Mt1−Mt2t1−t2 where t1 and t2 are the drying time (h); Mt1 and Mt2 are the moisture contents at time t1 and t2 on a dry basis, respectively (kg·kg−1). ## 3.4. Color Evaluation of Treated G. elata At different core temperatures, the cross-sectional areas with white color in the core region of treated G. elata samples were assessed using a two-dimensional image based on the color difference. The white area of materials was analyzed and calculated by image segmentation and processing algorithm. The proportion of the white-colored area was calculated according to Equation [3]:L = S1/S0[3] where L represents the ratio of the white-colored area (%); S0 is the total cross-sectional area of G. elata (mm2); and S1 represents the white-colored area of the G. elata cross-section (mm2). ## 3.5. Determination of Gelatinization Temperature Sample Preparation The G. elata roots were cut into 5 mm-thin slices and transferred to the pre-cooling chamber (−40 °C) by maintaining a medium freezing rate for 2 h. The frozen G. elata slices were quickly moved to the freeze dryer kept in a vacuum drying room (LGJ-10E, Ningbo Xinyi ultrasonic equipment Co., Ltd., Ningbo, China). The drying room was vacuumed after sealing, and the temperature control switch was turned on when the pressure was lower than 30 Pa. The shelf temperature during the freeze-drying process was 30 °C, and drying was stopped when the moisture content was lowered below $12\%$ (wet basis). After freeze-drying, G. elata was crushed using a pulverizer (FW 135, Tianjin taist Instrument Co., Ltd., China) and screened using a 60-mesh screen. The pasting property of G. elata whole powder ($6\%$ solids) was evaluated in triplicate using a Rapid Visco Analyzer (RVA-3D, Newport Scientific, Narrabeen, Australia). A programmed heating and cooling cycle was used, where the samples were held at 50 °C for 1 min, heated to 95 °C at a rate of 12 °C/min, maintained at 95 °C for 2.5 min, cooled to 50 °C at a rate of 12 °C/min, and then held at 50 °C for 2 min. Pasting temperature, peak viscosity, hot viscosity, final viscosity, breakdown viscosity (peak-hot viscosity), and setback viscosity (final-hot viscosity) were recorded [32]. ## 3.6. Magnetic Resonance Measurements LF-1H NMR measurements were performed using an NMR Analyzer (MesoMR23-060H-I, Niumag Corp., Shanghai, China) equipped with a 0.5 T permanent magnet corresponding to a proton resonance frequency of 20 MHz at 32 °C [33,34]. The G. elata tuber samples were placed in an NMR tube with an outer diameter of 40 mm. The proton decay signals were collected using the Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence with a τ-value (time between 90° pulse and 180° pulse) of 200 µs and with 90° and 180° pulses of 7.5 and 15 µs, respectively. Parameters for NMR measurement were set as follows: echo time (TE), 0.35 ms; waiting time (TW), 2000 ms. Data from 18,000 echoes were acquired using 8 repeated scans [35]. Relaxation time analysis and distributed exponential curve fitting were performed using MultiExp Inv Analysis software (Niumag Corp., Shanghai, China). Multi-exponential fitting analysis was performed on the relaxation data using a modified inversion algorithm to obtain improved fitting. The relaxation time and its corresponding water population (area ratio) from this analysis were recorded. MRI was performed using an NMR Analyzer (MesoMR23-060H-I, Niumag Corp., Shanghai, China) equipped with a 25 mm radio frequency coil at 32 °C [36]. The parameters for MRI measurement were set as follows: slice width, 3 mm; slice gap, 1 mm; TR (time repetition), 2000; TE (time echo), 25 ms; average, 4. ## 3.7. Microstructure Analysis The microstructures of the fresh, steamed, and blanched samples were observed using a scanning electron microscopy (SEM, SU3500, Hitachi, Ltd., Tokyo, Japan). The pre-freezing and drying conditions of the sample were the same as those in Section 3.5. Samples were vacuum freeze-dried to a safe moisture content ($12\%$) and cut into 4 mm cubes. Each sample was sputter-coated for 90 s with gold and analyzed using SEM at an accelerating voltage of 3.0 kV [37,38]. ## 3.8. Measurement of Gastrodin Content and P-hydroxybenzyl Alcohol Content The contents of gastrodin and p-hydroxybenzyl alcohol in G. elata were determined using high-performance liquid chromatography on an Ultimate 3000 standard liquid chromatography system (DIONEX, USA). A C18 column (4.6 × 250 mm, 5 m, Shimadzu, Japan) was employed in the analysis. The column temperature was 25 °C, and the injection volume was 20 mL. The mobile phases were $0.05\%$ trifluoroacetic acid water (A) and $0.05\%$ trifluoroacetic acid acetonitrile (B). The flow velocity was set at 0.8 mL/min, with the following elution gradients: 0–60 min, $95\%$ A; 60–70 min, $70\%$ A. Ultimate3000 Photodiode array detector was used at a detection wavelength of 220 nm. The results were expressed as mg/g dry matter. The detailed methods are reported by Gong [39]. ## 3.9. Determination of Crude Polysaccharide Content of G. elata Dried G. elata was crushed in a pulverizer for 2 min, and the G. elata powder was sieved through a 60-mesh screen. Then, 0.5 g of the sieved sample was weighed (accurate to 0.001 g), placed in a 50 mL plugged centrifuge tube, and 25 mL of deionized water (material liquid ratio 1:50 g/mL) was added. The mixture was shaken in a vortex oscillator to mix the contents fully. The sample was then extracted in an ultrasonic extractor (100 W) for 30 min with an initial ultrasonic temperature of 60 °C. After extraction, it was cooled to 25 °C, filtered, and the filtrate was transferred to a 100 mL volumetric flask. The residue was washed 2–3 times with deionized water, and the total volume was made up to 100 mL with water. This solution was the sample determination solution. At the start, 0, 0.2, 0.4, 0.6, 0.8, and 1.0 mL of 100 mg/L standard glucose solution were added to 20 mL glass tubes with stoppers, and distilled water was added so that the final volume was 1 mL. Then, 1 mL $5\%$ v/v phenol solution, followed by 5.0 mL of $98.08\%$ sulfuric acid, was added, and the mixture was allowed to stand for 10 min. The solution was fully mixed using a vortex oscillator, then moved to a water bath at 30 °C for 20 min. The absorbance was then measured at 490 nm. The glucose mass was taken as the abscissa and the absorbance value as the ordinate, and a standard curve was drawn. The regression equation $y = 0.0567$x + 0.0339 with r2 = 0.9986 was obtained for drawing the standard curve. The solution to be tested (0.5 mL) was sampled, and absorbance was detected according to the method in “drawing standard curve ($y = 0.0567$x + 0.0339)”. The glucose mass fraction value of the sample was calculated according to the standard curve equation. ## 3.10. Data Analysis-Statical Analysis The experimental data’s mean and standard deviation (SD) were calculated from three independent replicates. Data were analyzed using ANOVA with post hoc Duncan’s multiple comparison tests using SPSS statistics 20.0 (International Business Machines Incorporation, USA) at the $95\%$ confidence level. ## 4. Conclusions The results of the present study showed that G. elata starch gelatinization could be confirmed from the internal color change. The relationship between the core temperature of the G. elata section and the proportion of white at the center showed that the real-time core temperature of G. elata without a white area was 60 °C. Steaming and blanching significantly decreased the drying rate of G. elata. After steaming and blanching, the degrees of freedom of binding water, intracellular water, and intercellular water of G. elata decreased, making it difficult for water to exit the cells. Further, cell wall collapse, starch gelatinization, polysaccharide denaturation, and hydrolysis could be observed in SEM. After steaming and blanching, the content of gastrodin and crude polysaccharide of G. elata increased, while the content of p-hydroxybenzyl alcohol decreased. When the core temperature was 75 °C, gastrodin content reached its maximum, and when the core temperature was 60 °C, the crude polysaccharide content of G. elata reached its maximum. Because the bioactive components were readily soluble in water, steaming was more suitable than blanching for processing, and the contents of the active ingredients were highest when the central temperature was 75 °C. 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--- title: SGLT2 Inhibitor—Dapagliflozin Attenuates Diabetes-Induced Renal Injury by Regulating Inflammation through a CYP4A/20-HETE Signaling Mechanism authors: - Batoul Dia - Sahar Alkhansa - Rachel Njeim - Sarah Al Moussawi - Theresa Farhat - Antony Haddad - Mansour E. Riachi - Rashad Nawfal - William S. Azar - Assaad A. Eid journal: Pharmaceutics year: 2023 pmcid: PMC10054805 doi: 10.3390/pharmaceutics15030965 license: CC BY 4.0 --- # SGLT2 Inhibitor—Dapagliflozin Attenuates Diabetes-Induced Renal Injury by Regulating Inflammation through a CYP4A/20-HETE Signaling Mechanism ## Abstract Diabetic kidney disease (DKD) is a serious complication of diabetes, affecting millions of people worldwide. Inflammation and oxidative stress are key contributors to the development and progression of DKD, making them potential targets for therapeutic interventions. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have emerged as a promising class of drugs, with evidence demonstrating that they can improve renal outcomes in people with diabetes. However, the exact mechanism by which SGLT2i exert their renoprotective effects is not yet fully understood. This study demonstrates that dapagliflozin treatment attenuates renal injury observed in type 2 diabetic mice. This is evidenced by the reduction in renal hypertrophy and proteinuria. Furthermore, dapagliflozin decreases tubulointerstitial fibrosis and glomerulosclerosis by mitigating the generation of reactive oxygen species and inflammation, which are activated through the production of CYP4A-induced 20-HETE. Our findings provide insights onto a novel mechanistic pathway by which SGLT2i exerts their renoprotective effects. Overall, and to our knowledge, the study provides critical insights into the pathophysiology of DKD and represents an important step towards improving outcomes for people with this devastating condition. ## 1. Introduction Diabetic kidney disease (DKD) is a debilitating complication and a major contributor to all-cause mortality in patients with diabetes. Several risk factors contribute to the development of DKD, including poor glycemic control, hypertension, smoking, dyslipidemia, as well as multiple genetic and environmental factors [1]. DKD is characterized by glomerular, vascular, tubular, and interstitial damage that initially develops in the absence of clinically measurable dysfunction. The current conventional therapies to prevent DKD and slow its progression include intensive blood glucose control [2,3,4,5], blood pressure regulation and renin-angiotensin-aldosterone system (RAAS) blockade [6,7,8]. Despite the importance of these treatment modalities, the risk of developing end-stage renal disease (ESRD) in patients with type 2 diabetes (T2DM) remains considerably high. In that regard, several studies have focused on identifying the signaling pathways indicating the onset of DKD as well as testing new potential biomarkers to achieve the earlier detection of diabetic kidney disease such as NETosis, a novel form of neutrophil-related cell death, and Neutrophil Gelatinase-Associated Lipocalin, to name a few [9,10,11]. Therefore, new therapeutic approaches are needed to reduce the onset of DKD and to curb its progression to ESRD. Among the new generation of glucose-lowering oral drugs, inhibitors of the sodium-glucose cotransporter 2 (SGLT2) have been identified to have a potential role in lowering the risk of renal complications in patients with diabetes [12,13,14,15,16]. The nephroprotective role of SGLT2 inhibitors (SGLT2i) is not only a consequence of correcting hyperglycemia by significantly decreasing HbA1c levels and reducing body weight [17,18,19], but is also a result of their anti-inflammatory, antifibrotic, and antioxidative stress effects in renal tissues [20,21,22]. Dapagliflozin is one of the SGLT2 inhibitors that has been demonstrated to have cardiac and renoprotective effects in clinical trials such as DECLARE-TIMI 58 [15]. Several reports have attributed the substantial benefits of dapagliflozin on renal function to the attenuation of oxidative stress, apoptosis, ER stress, and inflammation [23,24]. Despite these significant findings, the exact mechanisms by which dapagliflozin exerts its nephroprotective properties are yet to be elucidated. Arachidonic acid (AA) is metabolized to 20-hydroxyeicosatetraenoic acid (20-HETE) by the cytochrome P450 (CYP) 4A and 4F families of enzymes, with cytochrome P450 (CYP) of the 4A family being the most abundant in mice kidney tissue [25]. Additionally, CYP4A, particularly the CYP4A12a isoform, is the predominant 20-HETE synthase in the mouse kidney [26,27]. The exact contribution of CYP4F isoforms to 20-HETE production in mouse models is not well established. 20-HETE is a powerful vasoconstrictor involved in the regulation of hemodynamics and extracellular fluid volume through tubular and vascular mechanisms [28,29]. Moreover, CYPs are heme-containing monooxygenases. Therefore, the aberrant redox cycling of these enzymes leads to the formation of superoxide(O2−)/hydrogen peroxide(H2O2), rendering them a significant source of oxidative stress in different tissues, including renal tissue [30,31,32]. Published data by our group amongst other findings describes the contribution of AA-metabolizing CYP enzymes and their metabolites in inducing reactive oxygen species (ROS) production in the tubules and glomeruli of the kidneys, leading to proteinuria, cellular injury, and apoptosis [29,30,33,34,35,36,37]. CYPs-generated 20-HETE might therefore be involved in the overall decline in the renal function observed in DKD [38]. Amongst the pathophysiological changes caused by diabetes, inflammation has been demonstrated to play a key role contributing to the aberrant metabolism and oxidative stress in DKD [39]. The infiltration of immune cells into the renal tissue and the circulation of proinflammatory molecules have been demonstrated to be increased in both animal models and patients with DKD [40]. Several cytokines and chemokines are thought to play a crucial role in kidney diseases. The chemokine monocyte chemoattractant protein 1 (MCP1) [41] was found to be associated with a decline in the renal function of patients with DKD [42,43,44]. Several other proinflammatory cytokines are believed to contribute to DKD, including the tumor necrosis factor alpha (TNF-α) [45,46,47,48,49], interleukin 6 (IL-6) [50], interleukin 1-beta (IL-1β) [51,52] and interleukin 17 (IL-17) [53]. In this study, we determine the renoprotective effect of dapagliflozin in a high-fat diet (HFD) streptozotocin (STZ)-induced T2DM mouse model. We also highlight, for the first time, the interaction between the SGLT2i and the CYP4A/20-HETE axis that leads to a reduction in ROS production, oxidative stress, and inflammation in the renal cortices of mice. Our findings describe a new mechanistic pathway by which SGLT2i interacts with the CYP4A/20-HETE axis to mediate its renoprotective role in type 2 diabetes. ## 2.1. Animal Models All animal procedures were conducted in accordance with the American University of Beirut Animal Care and Use Committee guidelines (IACUC protocol number 19-04-523). Ten-week-old male C57BL/6 mice were divided into four groups of four animals each. Type 2 diabetes was induced by maintaining the mice on an HFD containing $60\%$ kcal from fat for four weeks, followed by 3 consecutives intraperitoneal (i.p.) injections of 55 mg/kg body weight of STZ (Sigma-Aldrich, St. Louis, MO, USA) dissolved in citrate buffer (pH 4.5). These mice were maintained on HFD throughout the study until sacrifice. Four weeks after diabetes onset, diabetic mice were divided into 3 different groups: [1] untreated type 2 diabetic group, [2] type 2 diabetic group treated with 1.5 mg/kg dapagliflozin (Farxiga) i.p. daily for 8 weeks and [3] type 2 diabetic group treated with 2 units of insulin (Actrapid) i.p. daily for 8 weeks. Age-matched male C75BL/6 mice maintained on a standard rodent chow ($10\%$ of kcal from fat) and injected with 3 consecutive doses of sodium citrate buffer after 4 weeks of the study initiation (0.01 M, pH 4.5) were used as a control group. In parallel experiments, 10-week-old male FVB/NJ mice were rendered type 2 diabetic, as described above. Four weeks after diabetes onset, diabetic mice were divided into the following groups of four animals each: [1] untreated type 2 diabetic group; [2] type 2 diabetic group treated daily with 5 mg/kg of HET0016 administered subcutaneously for 10 weeks. Age-matched male FVB/NJ mice labeled as the control group were maintained on a standard rodent chow containing $10\%$ of kcal from fat and injected with 3 consecutive doses of sodium citrate buffer after 4 weeks of the study initiation (0.01 M, pH 4.5). Animals had ad libitum access to food and water maintained at a temperature-controlled room with 12 h alternating light/dark cycles throughout the whole study period. Body weight and blood glucose were measured weekly. Before sacrifice, mice were placed in metabolic cages for urine collection. Urine albumin to creatinine ratio (UACR) was measured using a mouse albumin enzyme-linked immunosorbent assay (ELISA) quantification kit (Bethyl Laboratories) and expressed as micrograms of albumin/24 h. Animals were sacrificed by exsanguination under anesthesia. Both kidneys were removed and weighed. A slice of kidney cortex at the pole was fixed with $4\%$ formalin for immune-histochemical analysis or flash-frozen in liquid nitrogen and stored at −80 °C for Western blot, PCR, enzymatic assays, microscopy, and image analysis. ## 2.2. Immunohistochemical Analysis Renal cortical tissues from each group were fixed in a $4\%$ formalin solution and embedded in a paraffin block. Samples were cut into 4-µm-thick sections and placed on glass slides. The kidney sections were then stained with a periodic acid Schiff (PAS) reagent to assess glomerulosclerotic index and mesangial accumulation, as previously described [54], and Masson trichrome (MT) stain to evaluate collagen deposition. A quantitative measurement for 25 randomly sampled glomeruli was blindly performed on each group using Image J software (1.53 e, U.S. National Institutes of Health, Bethesda, MD, USA). ## 2.3. Detection of Intracellular Superoxide The ROS generation was assessed by a high-performance liquid chromatography (HPLC) analysis of dihydroethidium (DHE)-derived oxidation products as previously described [55]. ## 2.4. NADPH Oxidase Activity NADPH oxidase activity was measured in the isolated kidney cortex, as previously described [36,37,55,56,57]. Briefly, kidney tissues were homogenized in lysis buffer (20 mM KH2PO4 [pH 7.0], 1 mM EGTA, 1 mM phenylmethylsulfonyl fluoride, 10 μg/mL aprotinin, and 0.5 μg/mL leupeptin) with 100 strokes in a dounce homogenizer on ice. Total protein concentration was determined using Bio-rad protein assay reagents. To start the assay, 25 μg of homogenates were added to a 50 mM phosphate buffer (pH 7.0) containing 1 mM EGTA, 150 mM sucrose, 5 μM lucigenin, and 100 μM NADPH. Photon emission expressed as relative light units was measured every 30 s for 5 min in a luminometer. A buffer blank (<$5\%$ of the cell signal) was subtracted from each reading. Superoxide production was expressed as relative light units (RLU) per minute and per milligrams (mg) of protein. ## 2.5. Inflammatory Markers Levels of MCP-1, IL-1β, IL-6, IL-17, and TNFα were measured using Elisa kits for each marker (Detroit R & D, Inc., Detroit, MI, USA) according to the manufacturer’s protocol. ## 2.6. 20-HETE Formation Levels of 20-HETE were measured using the 20-HETE Elisa kit (Detroit R & D, Inc., USA) according to the manufacturer’s protocol. ## 2.7. mRNA Analysis mRNA was analyzed by real-time RT-PCR using the ΔΔCt method. Total RNA was extracted from the mice kidney cortices using TRIZOL reagent (Sigma-Aldrich, St. Louis, MO, USA) and converted into cDNA using the Revert First Strand cDNA Synthesis Kit (Qiagen) according to the manufacturer’s protocol. cDNA expression was quantified using the CFX96 Touch (Bio-Rad, Hercules, CA, USA) with SYBR Green dye and predesigned mouse RT2-quantitative PCR primers. Primers for Fibronectin: Forward 5′-GATGGAATCCGGGAGCTTTT-3′ and Reverse: 5′-TGCAAGGCAACCACACTGAC-3′; Collagen IV: Forward: 5′-GGCGGTACACAGTCAGACCAT-3′ and Reverse: 5′-TGGTGTGCATCACGAAGGA-3′. Primers for YWHAZ: Forward: 5′-GGTGATGACAAGAAAGGAATTGTG-3′ and Reverse: 5′-GCATCTCCTTTTTGCTGATTTCA-3′ or 26s: Forward: 5′-AGGAGAAACAACGGTCGTGCCAAAA-3′ and Reverse: 5′-GCGCAAGCAGGTCTGAATCGTG-3′ was used as an internal reference gene. ## 2.8. Western Blot Analysis Homogenates from the frozen renal cortex were prepared in 500 µL lysis buffer containing $0.1\%$ sodium dodecyl sulfate (SDS), $0.5\%$ sodium deoxycholate, 150 mM sodium chloride, 50 mM Tris-hydrochloride, 100 mM EDTA, $1\%$ Tergitol (NP40), 100 mM PMSF, 1× of protease inhibitor cocktail containing aprotinin and leupeptin and phosphatase inhibitors cocktail (Bio-world). Homogenates were incubated for 1 h at 4 °C and centrifuged at 10,000× g for 30 min at 4 °C. Proteins concentrations in the supernatants were measured using the Lowry quantification method (Bio-rad Laboratory, Hercules, CA, USA). For immunoblotting, proteins (40 μg) were separated on $12.5\%$ polyacrylamide SDS-gel electrophoresis and transferred to nitrocellulose membranes. Blots were incubated with rabbit anti-CYP4A (1:500; Abcam, Cambridge, UK), and Mouse HSC-70 (1:1000; Santa Cruz Biotechnology, Dallas, TX, USA) was used as a loading control. The primary antibodies were detected using horseradish peroxidase-conjugated IgG. Enhanced chemiluminescence helped in visualizing the bands. Densitometric analysis was performed using Image J software (1.53 e, U.S. National Institutes of Health, Bethesda, MD, USA). ## 2.9. Statistical Analysis Results are expressed as mean ± SD. Statistical significance was assessed by one-way Anova with Prism 9 software (GraphPad Software, San Diego, CA, USA). Significance was determined as a probability (p-value) of <0.05. ## 3.1. Dapagliflozin Treatment Attenuates Functional and Structural Renal Damage in T2DM Mice First, we confirmed the renoprotective role of dapagliflozin in our animal model. As anticipated, both dapagliflozin and insulin treatments lowered hyperglycemia in the treated diabetic mice groups when compared to the untreated diabetic mice (Table 1). No significant difference was observed in the body weight of the different groups of mice except for the group treated with insulin, which showed reduced body weights when compared to any of the other groups. Furthermore, a significant increase in kidney weight to body weight ratio, which reflects renal hypertrophy, proteinuria (mg/24 h), and elevated urine albumin to creatinine ratio (UACR; µg/mg), was noted in the untreated diabetic mice as compared to control mice. Dapagliflozin as well as insulin treatments markedly reduced the observed kidney failure (Table 1). These results were paralleled by glomerular and tubular injury in the T2DM mice, in which mesangial expansion, glomerulosclerotic index (GSI), collagen deposition, and fibrosis were all increased when compared to their non-diabetic counterparts. Treatment with dapagliflozin or with insulin showed a significant reduction in these same histopathological parameters (Figure 1A–D). Consistent with the GSI and mesangial expansion findings, glomerular collagen deposition was increased in the untreated diabetic mice (Figure 1A,D). Renal injury was further validated by measuring the gene expression of classical extracellular matrix (ECM) molecules. Our results demonstrate an evident increase in the renal expression of Fibronectin (Figure 1E) and Collagen IV (Figure 1F) in the untreated T2DM group. The treatment with dapagliflozin and insulin significantly reversed the observed increase in the fibrotic markers (Figure 1E,F). ## 3.2. Dapagliflozin Inhibits CYP4A-Induced 20-HETE Production and Attenuates Oxidative Stress in the Kidneys of T2DM Mice We have previously demonstrated that CYP4A-induced 20-HETE production is implicated in the pathogenesis of DKD by inducing ROS production and NADPH oxidase activity [35,36,37]. In this study, we demonstrate that dapagliflozin mitigates the diabetes-increased CYP4A protein expression and 20-HETE production, which coincided with a decrease in ROS production and NADPH oxidase activity (Figure 2A–D). ## 3.3. Treatment with Dapagliflozin Reduces the Systemic and Renal Inflammation Observed in the T2DM Mice Inflammation has been described to play a role in the development of DKD through the increased cytokine production and exacerbation of oxidative stress [39]. The expression profiles of the essential proinflammatory cytokines and chemokines, MCP-1, IL-1β, IL-6, IL-17, and TNFα, were significantly increased in plasma and kidney cortices of the untreated diabetic mice when compared to their control littermates (Figure 3A,B). Interestingly, the observed increase in the inflammatory mediators was attenuated when the diabetic mice were treated with dapagliflozin or insulin (Figure 3A,B). ## 3.4. CYP4A/20-HETE Inhibition by HET0016 Attenuates Renal Injury in T2DM In these set of experiments, we used control and type 2 diabetic FVB/NJ mice to assess whether the observed diabetes-induced renal changes are reproducible across strains. Furthermore, these experiments will allow us to determine whether the inhibition of 20-HETE plays a central role in the pathogenesis of diabetes-induced renal damage. By utilizing multiple strains of mice and examining the impact of 20-HETE inhibition on renal function and structure, this study will allow us to gain a more comprehensive understanding of the mechanisms underlying diabetic kidney disease. As expected, the 20-HETE production was significantly higher in the plasma and kidneys of untreated type 2 diabetic mice as compared to the controls. This was prevented or reduced in the diabetic animals treated with HET0016, a potent inhibitor of CYP4A and therefore of 20-HETE production (Figure 4A,B). The elevated 20-HETE levels correlated with an overproduction of ROS as determined by HPLC, which was paralleled by an increase in NADPH oxidase enzymatic activity in the untreated diabetic mice compared to control mice. This increase was inhibited in the diabetic mice after HET0016 treatment (Figure 4C,D). Moreover, our results demonstrate that HET0016 decreases renal hypertrophy as assessed by kidney weight to body weight ratio and restores the levels of UACR and proteinuria to near control levels. Of interest, HET0016 did not affect the glycemia of the treated T2DM mice, suggesting that 20-HETE production plays a central role in diabetes-induced renal injury, and its inhibition is renoprotective independently of hyperglycemia (Table 2). In parallel, the histopathological assessment of renal tissues of the different groups of mice shows that HET0016 treatment attenuates diabetes-induced glomerular and tubular injury as assessed by the decrease in glomerular hypertrophy (Figure 5A,B) glomerulosclorosis (Figure 5A,C), and mesangial expansion (Figure 5A,D). These results were paralleled by a decrease in tubulointerstitial fibrosis and collagen IV deposition in the diabetic mice after HET0016 treatment (Figure 5E,F). ## 3.5. CYP4A-Induced 20-HETE Production Prompts the Increase in Reactive Oxygen Species Production and the Rise in Proinflamatory Markers The anti-inflammatory effect of inhibiting CYP4A/20-HETE in DKD was assessed by measuring MCP-1, IL-1β, IL-6, IL-17, and TNF⍺ in the plasma (Figure 6A) and the kidney cortices (Figure 6B) of the different groups of mice. Our results demonstrate that the inhibition of 20-HETE production by HET0016 results in a significant reduction in the measured proinflammatory markers observed in the T2DM mice (Figure 6A,B). Collectively, our findings strongly support the notion that the activation of CYP4A/20-HETE plays a pivotal role in the pathogenesis of diabetic kidney disease (DKD), and that the renoprotective effects of dapagliflozin, an SGLT2 inhibitor, are mediated via the inhibition of CYP4A/20-HETE. This inhibition effectively reduces both systemic and renal inflammation, as well as reactive oxygen species (ROS) production, thus highlighting a novel therapeutic target for DKD. ## 4. Discussion SGLT2i are a class of antihyperglycemic medication proposed to play a renoprotective role in patients with diabetes through both glucose-lowering dependent and independent mechanisms [12,13,14,15,16]. The American Diabetes Association (ADA) recommends using an SGLT2i for patients with T2DM and DKD when eGFR ≥ 20 mL/min/1.73 m2 since its glucose-lowering efficacy is directly proportional to the glomerular filtration. However, the post hoc analysis of Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial suggests that the SGLT2i canagliflozin reduces the progression of kidney disease even in patients with low eGFR [58]. Moreover, results from the DAPA-HF (Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure) trial demonstrate that dapagliflozin improves cardiovascular outcomes regardless of the presence or absence of diabetes [59]. Thus, a growing series of observations suggest that the renal and cardiovascular benefits of SGLT2i are also mediated through glucose-independent mechanisms. In the current study, we intended to investigate the mechanism behind the renoprotective effects of the SGLT2i in the context of diabetes. To our knowledge, this is the first study to suggest that the downregulation of CYP4A/20-HETE contributes at least partially to the nephroprotective actions exerted by SGLT2i. We used a HFD/STZ-induced T2DM mouse model for our experiment. The combination of HFD followed by the low dose STZ treatment can mimic the natural history and metabolic characteristics of T2DM in humans, including impaired glucose tolerance, obesity, insulin resistance, and hyperglycemia [60,61]. Consistent with the earlier observations from the literature, SGLT2 inhibition by dapagliflozin prevents some of the major hallmarks of renal dysfunction and DKD, including hypertrophy, as revealed by the increased kidney weight to body weight ratio, proteinuria, and elevated urinary ACR in our diabetic mice. Moreover, DKD is accompanied by phenotypic changes at the level of kidney glomeruli, such as mesangial expansion and ECM accumulation leading to fibrosis [62]. As anticipated, inhibiting SGLT2 in our T2DM mouse model protected the renal tissue from these histopathological changes as shown by the decreased GSI, glomerular area, and expression levels of the markers of fibrosis, fibronectin, and collagen IV. However, whether the renoprotective effects of SGLT2i are solely due to glucose control or are related to glucose-independent pathways remains to be determined. To further delineate the contribution of the CYP4A/20-HETE axis to our proposed mechanism of renoprotection in T2DM, the HFD/STZ-induced diabetic mice were treated with HET0016. HET0016 is a potent and selective inhibitor of the CYP enzymes which catalyze the synthesis of 20-HETE from AA [63]. Growing evidence has implicated the role of 20-HETE, an endogenous CYP4A/F metabolite of AA, in vascular and kidney injury. Nevertheless, depending on its site of production, different levels of 20-HETE can have various and even opposing functions [35,36]. Previously published works by our group demonstrated that HET0016 decreases CYP4A protein expression [36,64] and thus CYP4A protein levels were not measured in animals treated with HET0016. Thus, measuring the decrease in 20-HETE was sufficient to confirm the effectiveness of the treatment. Albeit the central role of 20-HETE in the regulation of renal function, its impact on DKD needs further clarification. Gangadhariah et al. suggested that 20-HETE exacerbates renal injury in STZ-induced diabetic mice [65]. In addition, in a kidney ischemia/reperfusion injury rat model, the inhibition of CYP4A/F by HETE0016 or treatment with a 20-HETE antagonist (6,15,20-HED) offered a renoprotective effect [66,67]. Furthermore, in an STZ-induced diabetic rat model, the increased production of 20-HETE was associated with the overexpression of fibronectin and transforming growth factor-β1 (TGF-β1) in the kidneys of the experimental rodents [68], where these molecules are proven to be a profibrotic factor in DKD [69]. Our group has previously mirrored these conclusions, with prior studies demonstrating that hyperglycemia/diabetes induces renal CYP4A expression and consequently increases 20-HETE production; these changes are proposed to be implicated in the pathogenesis of DKD [35,36,37]. On the other hand, Luo et al. demonstrated that in diabetic rats, DKD can induce excessive production of TGF-β1 in the glomerulus, paralleled with a reduction in 20-HETE levels [70]. It is established that CYP450 is a significant source of cellular ROS in different tissues, including the renal tissue [30,31,32,37]. On the other hand, CYP450 eicosanoids have wide range of biological effects, including vascular tone regulation, cellular proliferation, renal tubular transport, and inflammation [28]. Former clinical studies have established an association between urinary 20-HETE excretion, oxidative stress, and endothelial dysfunction in human subjects [32,71]. Another recent finding indicated that upregulated endothelial CYP4A-derived 20-HETE contributes to enhanced superoxide production and vascular oxidative stress in an insulin-resistant obese rat model [72]. We have also reported earlier that diabetes-induced oxidative stress was associated with CYP4A upregulation and 20-HETE overproduction in the kidneys of a type 1 diabetes animal model [35,37]. In fact, 20-HETE is a well-known proinflammatory mediator and its overexpression induces NF-κB activation and cytokine expression in endothelial cells. Ishizuka et al. demonstrated that the treatment of endothelial cells with 20-HETE triggers the NF-κB activation and ROS production leading to elevated IL-8 levels and intracellular adhesion molecules, as well as subsequent endothelial cell dysfunction [73]. Together, these studies establish 20-HETE as a key mediator of vascular and renal inflammation and oxidative stress. Although ROS play an important role in cell signaling, their overproduction in the kidneys under pathological conditions including diabetes is associated with renal inflammation. Diabetes-induced ROS production stimulates the recruitment of numerous inflammatory cells, where the infiltration of macrophages and T cells plays a crucial role in initiating renal damage in DKD [74]. Immune cell recruitment and activity are usually modulated by MCP-1 [75]. Of importance, MCP-1 is found to be predominantly expressed in renal monocytes, endothelial cells, tubular epithelial cells, and mesangial cells [43,76,77,78,79,80] and is highly regulated by proinflammatory cytokines, namely TNFα and IL-1 [81]. Upregulation of MCP-1 levels was described in patients with DKD [43], and elevations were also noted in the glomeruli [82] and tubulointerstitium [83] of experimental models of type 1 diabetes. Interestingly, NF-κB was the main transcriptional factor reported to be implicated in initiating the inflammatory response in diabetes [84]. NF-κB activation induces the expression of proinflammatory genes, including MCP-1, IL-6, and TNFα [85,86,87,88] which are all key contributors to the development of DKD. In fact, TNFα and IL-6 levels were demonstrated to be strongly linked to renal disease progression. Several studies demonstrated the significant role of TNFα in ROS production [87,89], while IL-6 has been demonstrated to promote mesangial cell proliferation, ECM accumulation, and enhance endothelial cell permeability [88,90]. Another relevant cytokine found to be involved in renal inflammation is IL-17. Interestingly, IL-17 has been demonstrated to induce the expression of MCP-1, IL-1β, IL-6, and TNFα in tubular and mesangial cells leading to local macrophage recruitment [91,92]. A recent study has established the upregulation of TNFα, IL-6, and IL-1β upon treating podocytes or tubular epithelial cells with recombinant IL-17 under hyperglycemic conditions in vitro [53]. These observations were supported by their in vivo findings, where the IL-17−/− diabetic mice demonstrated a reduction in albuminuria, renal fibrosis, and glomerular injury [53]. In congruence with the aforementioned observations, we demonstrate that in our experimental model of T2DM, inhibiting CYP4A-derived 20-HETE by HET0016 reverses the diabetes-associated NADPH-dependent superoxide generation and ROS overproduction. Consequently, the HET0016 treatment prevents renal inflammation in diabetic mice, as suggested by the decreased circulatory and renal levels of the proinflammatory markers measured. Thus, while we acknowledge that investigating the combined effect of HET0016 and dapagliflozin is important and promising for future studies, this goes beyond the scope of our manuscript aiming at elucidating the individual mechanisms of the action of dapagliflozin as a renoprotective agent. SGLT2i have been demonstrated to be involved in reversing molecular processes related to inflammation, fibrosis, and ECM turnover [93]. In animal models of DKD, SGLT2i have been reported to decrease markers of inflammation and oxidative stress [94]. Indeed, our results are consistent with the former findings, demonstrating that inhibiting SGLT2 in the T2DM animal model averted the increase in inflammatory mediators and ROS production, eventually preventing diabetes-induced renal injury. Notably, our data demonstrate that treatment with SGLT2i attenuated the increase in the renal CYP4A expression and 20-HETE production observed in T2DM mice. This could be explained by the changes in glomerular function evoked during tubuloglomerular feedback (TGF) and the angiotensin II (AngII) actions. AngII plays a key role in modulating the vascular tone of the afferent arteriole [95]. Reduction in the delivery of sodium chloride (NaCl) to the macula densa cells of the juxtaglomerular apparatus (JGA) leads to an increased GFR and intraglomerular pressure through TGF [96]. In diabetes, hyperglycemia leads to increased sodium-coupled glucose reabsorption by the proximal tubules and decreased sodium delivery to the macula densa [94]. Consequently, the conversion of ATP into adenosine is inhibited, which reduces the levels of this potent vasoconstrictor leading to vasodilation of the afferent arteriole and causing increased renal plasma flow (RPF), intraglomerular pressure, and eventually hyperfiltration [94]. SGLT2i will enhance the sodium delivery to the macula densa, thus generating signals that provoke the afferent arteriole vasoconstriction, reducing RPF, improving the intraglomerular pressure, and ultimately curbing the progression of DKD [94]. On the other hand, 20-HETE is also a key modulator in the TGF response in the kidneys. In the thick ascending limb of Henle (TALH), 20-HETE has been demonstrated to inhibit the apical Na+-K+-2Cl− (NKCC2) cotransporter [97,98]. Moreover, it is essential for TGF response, as the major uptake mechanism of NaCl in the macula densa cells of TALH is mediated by NKCC2 [99,100], and the inhibition of this critical transporter can lead to a complete blockade of the TGF response [101]. Wang et al. demonstrate a marked effect exerted by NKCC inhibitors on reducing the reactivity of the afferent arteriole, the principal effector limb of TGF, to elevated pressure and AngII, which heavily affects the arteriolar vascular tone [99]. More importantly, several studies have previously reported that augmented AngII levels increase the renal synthesis of 20-HETE [102,103,104,105]. Another significant association was made between intrarenal RAAS and SGLT2 expression in humans and mice. Treatment with SGLT2i has been demonstrated to attenuate the AngII-induced hypertensive renal injury in mice [106]. Similarly, the urinary AngII levels were significantly decreased in the T2DM rat model when treated with dapagliflozin [107]. Thus, the influence of SGLT2i on 20-HETE could be mediated by AngII. In short, SGLT2i could exert their renoprotective effects in a two-way mechanism mediated in both cases by a RAAS-dependent decrease in the levels of 20-HETE (Figure 7). On one hand, decreased levels of 20-HETE enhance the sodium transport in the TALH, hence improving TGF. On the other hand, low levels of 20-HETE attenuate oxidative stress and renal inflammation induced by the diabetic milieu. Moreover, several randomized controlled trials have suggested that SGLT2 inhibitors can decrease the daily dose of insulin [108], which can be explained, to a certain extent, by the lower 20-HETE levels caused by SGLT2 inhibition, allowing a better utilization of the administered insulin. This mechanism is likely related to the observed reduction in oxidative stress and inflammation, as well as the amelioration of renal fibrosis and sclerosis, which were demonstrated in our study. The potential interaction between dapagliflozin and insulin warrants further investigation to fully elucidate the mechanism of action of SGLT2 inhibitors in diabetic kidney disease. Although our findings were based on animal models, further investigations using cultured cells could help validate our results. We acknowledge that this could be considered a minor limitation of our study. Of importance, our study adds to previous research, by our group and others [35,36], that have also demonstrated the renoprotective effects of inhibiting the 20-HETE production in cultured glomerular and renal tubular cells. 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--- title: Development of Dipeptide N–acetyl–L–cysteine Loaded Nanostructured Carriers Based on Inorganic Layered Hydroxides authors: - Denise Eulálio - Mariana Pires Figueiredo - Christine Taviot-Gueho - Fabrice Leroux - Cristina Helena dos Reis Serra - Dalva Lúcia Araújo de Faria - Vera Regina Leopoldo Constantino journal: Pharmaceutics year: 2023 pmcid: PMC10054814 doi: 10.3390/pharmaceutics15030955 license: CC BY 4.0 --- # Development of Dipeptide N–acetyl–L–cysteine Loaded Nanostructured Carriers Based on Inorganic Layered Hydroxides ## Abstract N–acetyl–L–cysteine (NAC), a derivative of the L–cysteine amino acid, presents antioxidant and mucolytic properties of pharmaceutical interest. This work reports the preparation of organic-inorganic nanophases aiming for the development of drug delivery systems based on NAC intercalation into layered double hydroxides (LDH) of zinc–aluminum (Zn2Al–NAC) and magnesium–aluminum (Mg2Al–NAC) compositions. A detailed characterization of the synthesized hybrid materials was performed, including X-ray diffraction (XRD) and pair distribution function (PDF) analysis, infrared and Raman spectroscopies, solid-state 13carbon and 27aluminum nuclear magnetic resonance (NMR), simultaneous thermogravimetric and differential scanning calorimetry coupled to mass spectrometry (TG/DSC–MS), scanning electron microscopy (SEM), and elemental chemical analysis to assess both chemical composition and structure of the samples. The experimental conditions allowed to isolate Zn2Al–NAC nanomaterial with good crystallinity and a loading capacity of 27.3 (m/m)%. On the other hand, NAC intercalation was not successful into Mg2Al–LDH, being oxidized instead. In vitro drug delivery kinetic studies were performed using cylindrical tablets of Zn2Al–NAC in a simulated physiological solution (extracellular matrix) to investigate the release profile. After 96 h, the tablet was analyzed by micro-Raman spectroscopy. NAC was replaced by anions such as hydrogen phosphate by a slow diffusion-controlled ion exchange process. Zn2Al–NAC fulfil basic requirements to be employed as a drug delivery system with a defined microscopic structure, appreciable loading capacity, and allowing a controlled release of NAC. ## 1. Introduction N–acetyl–L–cysteine (NAC) or 2-acetamido-3-sulfanylpropanoic acid, with the chemical structure is shown in Figure 1a, is a derivative of the amino acid L–cysteine that has been used in therapeutic practices for several decades. In recent years, NAC has shown numerous biological properties, which have been studied by in vitro and in vivo preclinical trials, along with clinical data [1]. Firstly, it was used as a mucolytic agent in a study developed by Hurst et al. [ 2] in patients with cystic fibrosis showing that NAC can break disulphide bonds of mucus. Years later, the potential of NAC for the treatment of acetaminophen poisoning, paracetamol overdose [3], paracetamol-induced acute kidney injury [4], and to decrease hepatic injury [5] was reported. NAC has effective antioxidant properties and, consequently, a strong capability to be used in treatments related to the generation of free radicals and as a food supplement. This drug has therapeutic potential for the treatment of other diseases such as Alzheimer’s [6], type-2 diabetes [7], type-1 diabetes [8], gestational diabetes mellitus [9], diseases related to psychiatric disorders [10], neurodegenerative diseases [11], inhibition and induced death of lung cancer cells [12], HIV-associated tuberculosis [13], and bone regeneration approaches [14,15]. NAC is considered helpful in the nutraceutical control of RNA viruses such as influenza and coronavirus and has been investigated as an adjuvant to the prevention and therapy of COVID-19 [16,17,18] and post-COVID-19 pulmonary fibrosis [19]. As a source of thiol groups (-SH), NAC is an excellent precursor for the biosynthesis of the tripeptide γ–glutamyl–L–cysteinyl-glycine (GSH, glutathione) inside cells, increasing the levels of this peptide which acts in the elimination of free radicals [7,20,21,22,23]. Although NAC oral bioavailability is higher than that of GSH, it is very low (4 to $10\%$), possibly due to the fact that plasma is a pro-oxidant medium, thus favoring the oxidation of NAC to symmetrical (NAC-NAC) or asymmetric disulphides (Cyst-NAC) [21,24,25]. NAC can be administered orally, intravenously, or by inhalation, and its terminal half-life (t$\frac{1}{2}$) is approximately 6 h [26,27]. When administered orally, the maximum plasma concentration (Cmax) is reached after 1–2 h [27]. NAC is classified as a biopharmaceutics classification system (BCS) I drug and shows high solubility of 100 mg mL−1 [28,29]. The confinement of NAC species into inorganic nanoparticles as layered double hydroxides (LDH) can be an interesting approach because the architecture of these materials has improved the physical–chemical stability, biocompatibility, and bioavailability of several bioactive species intercalated between the layers and also possess release properties, as reported in several review articles [31,32,33]. LDH are 3D structures formed by 2D layers [34], as shown in Figure 1b. LDH layers are held by electrostatic interactions and hydrogen bonds; each layer is formed by hydroxide ions coordinated to bivalent and trivalent cations in an octahedral geometry. The [M(OH)6] units are joined by the edges forming a positively charged layer, which grows along the ab plan [35]. *The* general formula [M1−x2+Mx3+(OH)2]Am−x/m·nH2O is associated with LDH, wherein M2+ and M3+ denote bivalent and trivalent cations, respectively, and Am− represents an intercalated anion with negative charge m. LDH composition is abbreviated in this work as M2+RM3+-A, where R is the M2+/M3+ cation molar ratio. By varying the M2+ ions (Zn, Mg, Ni, Cu, Co, Mn, or Fe, for instance), the M3+ ions (Al, Fe, Cr, Co, Mn, Ga, or Ni, for example), and the intercalated anion, a wide variety of these layered matrices can be synthesized in a controlled way [36]. The LDH composition, size, morphology, surface charge, and functionality can be tuned to load active principles of biomedical interest for therapeutic use, diagnosis, or theranostic applications [37]. The hydroxide layers give the pH-responsive property to this class of inorganic materials, allowing the bioactive species release not only by anion exchange reaction but also by the carrier solubilization in acidic sites originating from inflammatory processes or malignant diseases, for instance. The LDH is not an inert material in the live organism; it can be decomposed by slow acid-base reaction and/or complexation reaction with biomolecules. The nature of the chemical elements that comprise the layers is also very relevant because LDH solubility depends on the cations as well as the body’s response to such delivered cations. Actually, LDH shows intrinsic biological properties related to Mn+ ions that can modulate the repair of injured tissues [38], cause apoptosis of cancer cells by regulation of gene expression [39], present immunomodulating activity [40] or osteogenic differentiation [41], or promote the induction of neovascularization and angiogenesis [42,43], among other activities. The intercalated species studied cover a wide range of properties such as anti-inflammatory, antibiotic, antitumor, anticoagulant, antimicrobial, antidepressant, and antioxidant properties [44,45]. We have worked on the development of LDH host matrices for use as carriers of anionic species derived, for instance, from ibuprofen [46], sulindac [47], mefenamic acid [48], coumaric acid [49,50], pravastatin [51], naproxen [43], norbixin [52], and ciprofloxacin [53]. For some LDH materials, in vivo tests for phases intercalated with chloride ions (Mg2Al–Cl and Zn2Al–Cl [42], Mg4FeAl–Cl and Zn4FeAl–Cl [43]), or coumarate (Mg2Al–Cou and Zn2Al–Cou) [49] were performed to assess their biocompatibility by intramuscular implants, while in vitro assays of intercalated sulindac (Mg2Al–Sul and Zn2Al–Sul) [47] and mefenamate (Mg2Al–Mef) [48] materials were also studied. Furthermore, the release of sulindac from Zn2Al-Sul was evaluated in vivo by Raman spectroscopy from intramuscular implants [54]. The amazing results obtained in these in vivo tests concerning LDH composed by Mg, Zn, Fe, and Al ions open the possibility to evaluate them for implantable delivery systems because the formation of a fibrotic capsule was not observed. When the LDH intercalated with active species were prepared as nanofibrous membranes by poly(lactic acid) electrospun and electrosprayed LDH at the same time, the drug release extended for up to 66 days [55]. Hence, LDH is a potential material for the development of implantable multi-functional composites [56]. To the best of our knowledge, the intercalation of NAC into LDH was never reported before. Some studies showed the intercalation of L–cysteine, an analogue amino acid. Wei et al. [ 57] studied the intercalation of L–cysteine in matrices of Mg2Al composition as a reactor for the transformation of chemical substances. The authors observed that L–cysteine was oxidized within the LDH environment. Stimpfling et al. [ 58] intercalated L–cysteine into LDH of composition LiAl2, Mg2Al, and MgZnAl to assess the ability of the synthesized materials to prevent corrosion of the AA2024 aluminum alloy. Silva [59] explored the intercalation of L–cysteine into LDH matrices of composition Mg3Al and Mg3Fe to investigate how LDH type-structure minerals present on the planet in ancient times could have interacted with species of biological interest. The main aim of this work was to investigate experimental parameters to obtain nanodelivery drug systems (DDS) based on LDH (with compositions Zn2Al and Mg2Al) intercalated with the dipeptide NAC as well as to perform their detailed physicochemical characterization and the drug release kinetic models. Well structurally organized Zn2Al–NAC hybrid material was isolated with high NAC loading capacity while, in the presence of the Mg2Al–LDH composition, the partial oxidation of NAC was observed, i.e., its chemical integrity was not preserved. In vitro drug delivery tests were performed in two conditions in which the release medium was constantly agitated in a dissolution tester (basket method, here abbreviated S1) or not agitated (abbreviated S2) during the kinetic studies. Agitation of the release medium can impact the diffusion of water and ionic species into a tablet and the successive drug release. Such a simple method is also known as sample and separate (SS) method. Powdered samples were made in the form of cylindrical tablets, avoiding the presence of nanoparticles in the drug analysis medium, which cannot be sedimented by centrifugation or retained by membrane filtration; the simulated physiological solution used in the released assays aimed to mimic the extracellular matrix solution, as reported in the literature [60], considering the previously mentioned works about in vivo implantation of tablets to evaluate the DDS biocompatibility. ## 2.1. General N–acetyl–L–cysteine (C5H9NO3S), zinc chloride (ZnCl2), magnesium chloride hexahydrate (MgCl2·6H2O), and aluminum chloride hexahydrate (AlCl3·6H2O) were supplied by Sigma-Aldrich (St. Louis, MO, USA), while sodium hydroxide (NaOH) was provided by Merck (Darmstadt, Germany). NaCl and MgCl2∙6H2O were provided by Merck (Darmstadt, Germany). NaHCO3, KCl, K2HPO4, HCl, CaCl2, Na2SO4, and Tris hydroxymethyl aminomethane were provided by Synth (Diadema, SP, Brasil). All chemicals were used without further purification. ## 2.2. Synthesis of Layered Double Hydroxides M2Al–NAC (M = Zn or Mg) samples were prepared by the co-precipitation method at constant pH. A 0.1 mol L−1 solution of metal cations with M/Al molar ratio equal to 2 (14.0 mmol of M2+ and 7.0 mmol of Al3+) was prepared employing MgCl2·6H2O and ZnCl2 salts dissolved with deionized water (from Millipore, model Direct-Q 8 UV Smart (Jaffrey, EUA). Then, the aqueous solution was slowly added under stirring, using a magnetic stirrer (model 752A by Fisaton, Perdizes, Brazil), to a 0.1 mol L−1 solution of NAC (NAC/Al3+ molar ratio equal 1) at room temperature or at 55 °C and under nitrogen gas flow. The pH value was kept constant at 7.5 for Zn2Al–LDH and at 9.5 for Mg2Al–LDH by the addition of a 0.2 mol L−1 solution of NaOH. After the complete addition of the metal cations, the suspension formed from metal hydroxide co-precipitation was kept under stirring for 1 h under nitrogen gas flow. The solid materials were separated by centrifugation using an equipment model Z36 HK by Hermle (Wehingen, Germany) for 10 min at 10 krpm, washed several times with deionized water, washed a final time with ethanol, and dried under reduced pressure (vacuum pump, Fanem LTDA, São Paulo, Brazil). The samples synthesized at room temperature or at 55 °C were abbreviated respectively as M2Al–NAC or M2Al–NAC55. Another condition was evaluated for the preparation of the zinc hybrid material keeping the same experimental conditions but using an NAC/Al3+ molar ratio equal to 1.3 (sample named Zn2Al–1.3NAC55). The same experimental conditions mentioned to synthesize LDH–NAC phases were applied to obtain LDH samples intercalated with chloride ions: the solution of metal cations was under stirring slowly added to 50 mL of deionized water. According to the results of metal and water analyses, the proposed composition for Zn2Al–Cl55 and Mg2Al–Cl was, respectively, [Zn2.0Al(OH)6.0]Cl0.90(CO3)0.05·1.42H2O and [Mg1.8Al(OH)5.6]Cl0.95(CO3)0.025·1.83H2O. ## 2.3. Preparation of NAC Salts in the Sodium Form First, 0.2 mol L−1 solution of NaOH was added to 0.1 mol L−1 solution of NAC under vigorous stirring and N2 atmosphere at room temperature. The NaOH solution was added to NAC solution up to reach the pH values 7.5, 8.5, 9.5, or 11. Posteriorly, the four solutions were frozen, freeze-dried (in a Thermo Savant Modulyo D equipment, Madrid, Spain), and kept under reduced pressure. The isolated NAC salt samples were abbreviated NAC-pH = X, where X is the pH value of the freeze-dried solution. ## 2.4. In Vitro NAC Release Kinetics Experiments Briefly, 40 mg of powdered Zn2Al–NAC55 samples containing 11 mg of NAC were compressed into tablets of 5 mm in diameter and 1 mm in thickness using a manual hydraulic tablet press employing 0.25 tons for 5 min. The release of NAC from the tablets was performed in simulated body fluid (SBF) at pH 7.4, prepared by dissolving NaCl (137.5 mmol), NaHCO3 (4.2 mmol), KCl (3.0 mmol), K2HPO4 (1.0 mmol), MgCl2∙6H2O (1.6 mmol), HCl (39 mL of 1 mol L−1 solution), CaCl2 (2.6 mmol), Na2SO4 (0.5 mmol), and tris hydroxymethyl aminomethane (50.5 mmol) in 1 L of deionized water, according to the literature [60]. The drug release experiments using the method with agitation (S1 method) were achieved in a dissolution instrument using the USP Apparatus 1, in which the basket rotated at 50 rpm [61]. Zn2Al–NAC55 tablets were immersed in 50 mL of SBF solution at 37 °C and stirred for 96 h. At predetermined intervals, 3 mL of SBF solution was removed from the apparatus and replenished with an equal volume of fresh SBF medium. The experiments were made in triplicate. In the release tests performed at static conditions without agitation (S2 method), the Zn2Al–NAC55 tablets were placed in Eppendorf microtubes to which were added 2 mL of SBF solution at 37 °C. At predetermined time intervals, 2 mL of the release medium was removed and replaced by equivalent volumes of fresh SBF medium. The release assays were performed in triplicate. The NAC concentration in both release conditions (S1 and S2 static methods) was determined by UV-visible absorption spectrophotometry at the wavelength of maximum absorbance (λmax) equal to 208 nm, while the metal cations amount in the release medium was quantified by inductively coupled plasma optical emission spectrometry (ICP OES). The stratigraphic analyses of the Zn2Al–NAC55 tablets after the release tests were conducted by micro-Raman spectroscopy. The suitable mathematical models [62,63,64,65] employed to verify the NAC release kinetics from Zn2Al–NAC55 tablets are indicated in Table 1. The statistical analysis of variance (ANOVA) considered a significance level of 0.05 [65]. ## 2.5. Equipment X-ray diffraction (XRD) patterns of powdered samples were recorded in a D8 Discover Bruker diffractometer (Karlsruhe, Germany) using Cu Kα radiation (1.5406 Å), 40 kV, 30 mA and Lynxeye detector (192 segments). Data were collected in the (2θ) 3.0–70° range and using a scan step of 0.02° (2θ)/0.5 s. The atomic PDF was obtained from X-ray total scattering data collected on a PANalytical Empyrean diffractometer equipped with a solid-state GaliPIX3D detector, a focusing X-ray multilayer mirror, and an Ag anticathode (Kα1 = 0.5594 Å, Kα2 = 0.5638 Å). Powder samples were mounted in glass capillaries of 0.7 mm diameter. An empty capillary of the same type was measured in the same way for background subtraction. Data were recorded over the range 1 < 2θ < 145°, which corresponds to an accessible maximum value for the scattering vector Qmax of 21.4 Å−1. Scanning electron microscopy (SEM) images were obtained in an electron microscope Jeol-JSM 6610LV equipment (Tokyo, Japan) with 7 kV voltage at secondary electrons (SE) mode. Sampling was performed by spreading the powder directly on the carbon tape and posteriorly coating it with a gold film using a sputter Denton Vacuum, model DESK V (Moorestown, NJ, USA). Fourier transform infrared (FTIR) spectra of powdered samples were recorded in a Bruker spectrophotometer (Ettlingen, Germany), Alpha model, in the attenuated total reflectance (ATR) accessory (Platinum) with diamond crystal, in the 400–4000 cm−1 range, with a spectral resolution of 4 cm−1; 256 scans were co-added. Fourier transform Raman (FT–Raman) spectra of powdered samples were recorded in an FT–Raman Bruker RFS-100/S device (Ettlingen, Germany) using 1064 nm exciting radiation from Nd:YAG laser Coherent Compass 1064–500 N (Lübeck, Germany), liquid N2 cooled Ge detector, laser power of 140 mW at the sample, 1024 scans, a spectral resolution of 4 cm−1, and in the 100–3500 cm−1 range. Raman spectra of Zn2Al–NAC55 tablets after the drug delivery experiments were recorded on a Renishaw in Via Reflex microscope (Wotton-under-Edge, Gloucestershire, UK), equipped with a thermoelectrically cooled CCD camera (Renishaw, 600 × 400 pixels) coupled to a Leica microscope model DM2500M; the laser line at 785 nm (diode laser, Renishaw) was focused on the sample by a Leica x50 objective (numerical aperture 0.75). Thermogravimetric and differential scanning calorimetry coupled to mass spectrometry (TG/DSC–MS) curves were registered with a Netzsch device, model TGA/DSC 490 PC Luxx (Spectro Analytical Instruments GmbH, Selb, Germany), coupled to an Aëlos 403C mass spectrometer (Germany). Analysis was performed under a synthetic air flow of 50 mL min−1 employing alumina crucibles and a heating rate of 10 °C min−1. Chemical analyses of Mg, Zn, and Al metals were performed in triplicate by inductively coupled plasma optical emission spectrometry (ICP AES) on a spectra Arcos spectrometer (Kleve, Germany) with axial plasma observation at the Central Analítica of the Instituto de Química of USP (CA–IQUSP). Samples were solubilized in a 4 mol L−1 solution of nitric acid and diluted before the measurements. Carbon, nitrogen, and hydrogen elemental analysis were recorded with a Perkin Elmer–CHN device (Waltham, MA, USA), model 2400, at CA–IQUSP. Solid-state nuclear magnetic resonance spectroscopy (ss-NMR) spectra were recorded in a 300 Bruker Advance spectrometer (Rheinstetten, Germany). It employed magic-angle spinning (MAS) at 10 kHz using a 4 mm diameter size zirconia rotor. 13C ($I = 1$/2) spectra were recorded at 75.47 MHz by proton enhanced cross-polarization method (CP, contact time 1 ms, recycling time of 5 s) and referenced to the carbonyl of glycine calibrated at 176.03 ppm and 2000 to 10,000 scans. 27Al ($I = 5$/2) spectra were recorded at 72.30 MHz, applying an accumulation of π/6 single-pulse, recycling time of 10 s, and calibration with a 1 mol L−1 aqueous solution of AlCl3 at 0 ppm. Tablets of powdered samples were prepared using a manual hydraulic tableting press (Marconi MA 098, Wabash, IN, USA). NAP delivery experiments were conducted in a Pharma Test Dissolution Instrument type PTWS 610 (Hainburg, Germany). UV-VIS electronic spectra of NAC released in the kinect experiments were recorded on a Shimadzu UV-1650PC spectrophotometer (Kyoto, Japan) using quartz cuvette of 10 mm. ## 2.6. X-ray Diffraction Data Processing The unit cell parameters for Zn2Al–NAC55 were determined from the full pattern matching refinement (Le Bail method) of X-ray diffraction patterns assuming R-3m space group and using Fullprof suite program [66]. The Patterson map was calculated using GFourier program [67] by employing the observed structure factors Fobs extracted from profile matching and plotted in the form of contour plots summed from 0 to 1 along the a/b-axis. The program HighScore Plus software provided by PANalytical Corporation was used for converting total X-ray scattering data to an atomic pair distribution function PDF of G(r). Fourier transforms of the reduced structure functions S(Q) were truncated at 21 Å−1. The bulk chemical composition [Zn2.04Al(OH)6.08](C5H7NO3S)0.5]·1.1H2O was used for the normalization of S(Q). ## 2.7. Simulation of NAC Vibrational Spectrum Spartan 18 (Wavefunction Inc., Irvine, CA, USA) version 1.2.Ø [68] was employed in geometry optimization and vibrational frequencies calculation. Equilibrium geometry was calculated using the PM3 semi-empirical method [69] with molecular mechanics amide correction to obtain vibrational frequencies. Density functional theory (DFT) calculation was performed using the B3LYP density functional [70] and 6–31 G* as basis set. ## 3.1. XRD, SEM, and Vibrational Spectroscopic Characterization of Zn2Al–NAC Sample Preliminary experiments were conducted by varying the temperature of synthesis and the NAC/Al molar ratio to isolate single and well-crystallized phases of NAC intercalated into LDH. XRD patterns of Zn2Al–NAC and Zn2Al–NAC55 samples (see Supplementary Material, Figure S1) indicated that aging at 55 °C increased the crystallinity of the materials as evidenced by the better signal-to-noise ratio for (00ℓ) Bragg peaks when compared to the sample prepared at room temperature. Furthermore, the presence of additional harmonic basal peaks ([0012] and [0015] reflections) for the heated sample was also indicative of a better stacking of the layers. As seen in Figure S1, a molar excess of $30\%$ of NAC did not improve its crystallinity, and a similar final composition was obtained for both samples with an NAC/Al molar ratio equal to 0.65 (Zn2Al-1.3NAC55) and 0.68 (Zn2Al–NAC.55). Therefore, the Zn2Al–NAC55 sample was selected to perform this study. XRD patterns of Zn2Al–NAC55 and Zn2Al–Cl55 samples are characteristic of layered materials (Figure 2): the position of the 00ℓ reflections below about 2θ = 30° associated with the interlayer distances shows an increase in the basal spacing from 0.75 nm for Zn2Al–Cl to 1.63 nm for Zn2Al–NAC55, indicating the successful intercalation of the organic species. Furthermore, the shift of the [113] reflection to a lower angle almost coinciding with the [110] as expected with the increase of the interlayer distance was also in favor of the formation of a single LDH–NAC phase, i.e., the absence of LDH–Cl or LDH–CO3 phases. XRD peaks of NAC polymorphs, shown in Figure S2, were also not observed in the pattern of Zn2Al–NAC55, precluding the presence of crystalline-free NAC salt in the hybrid material. The good crystallinity of the Zn2Al–NAC55 sample, as well as the absence of crystalline impurities, allowed us to perform a whole diffraction pattern profile refinement (Figure 3). The obtained data were consistent with R-3m space group which is often reported for LDH materials [35]. An interlayer distance of $d = 16.38$ Å was deduced from the value of the c parameter of the hexagonal cell. Additionally, the value obtained for the cell parameter $a = 3.066$ Å indicated a Zn/Al molar ratio of 2.1 Å [71], i.e., a very close value to that one applied during the synthesis (a nominal Zn/Al value equal to 2). The Patterson map was also calculated by considering all the integrated intensities extracted from the Le Bail fitting. The electron density in the interlayer space of Zn2Al–NAC55 sample is quite low (Figure 4) but nevertheless shows a distribution in different planes perpendicular to the c-stacking direction. The quasi-absence of electron density in the middle of the interlayer space confirms the bilayer arrangement. Carboxylate groups together with water molecules are likely to be located at the outer part of the interlayer space near the hydroxide layer at a distance around 3 Å from the centre of it, thus indicating the formation of rather strong hydrogen bonding with the OH groups of the layers. As one moves along the c-stacking direction, a pronounced local maximum detected at about 2 Å from the carboxylate groups may be attributed to the presence of heavy atoms such sulfur. Then, the amide group is observed. The PDF curves were extracted from total X-ray scattering data and, to facilitate interpretation, and the same analysis was performed on Zn2Al–Cl55 sample and NAC salt. As reported elsewhere [72], the first peak observed on the PDF for LDH materials refers to the hydroxide layers. Thus, in the present case, the first peak around 2.0 Å is due to the closest OH shell around Zn, Al atoms while the peaks observed at about 3.07 Å (a), 5.3 Å (√3a), and 6.2 Å (2a) are attributed to the M−M bond distances The other peaks are due to multiple pairs of atoms. Due to the high X-ray scattering power of the Zn atom, the PDF signal of [Zn2Al(OH)6] hydroxide layers is very intense, making it difficult to observe the signal from the interlayer space. The PDF curve of Zn2Al–NAC55 sample shows no change in the M-OH/M-M distances within the hydroxide layers. A shoulder around 2.4 Å is, however, noted on the first peak (Figure 5a), which is not observed in the PDF of Zn2Al–Cl55 (Figure 5b). The PDF curve of NAC (polymorph I) displays interatomic distances in this range (Figure 5c) corresponding to both intra and inter molecular distances as indicated by single-crystal XRD of NAC (Figure S3) [73]. Indeed, NAC molecules can interact by intermolecular and intramolecular hydrogen bonds, as, for instance, the intermolecular interactions between NH•••S (2.82 Å), CH•••OCOH (2.72 Å), and the intramolecular interaction between NH•••OCOH (2.26 Å). Calculations by DFT indicated that the more stable conformers for NAC (neutral compound) in a gas phase show main intramolecular bond lengths in the 2.24–2.32 Å range [74]. Hence, this additional distance observed at about 2.4 Å in Zn2Al–NAC55 may be attributed to the repetition of the drug array within the interlayer region. The interlayer space of LDH is a constrained environment and the distances among intercalated NAC anions can be distinct from those ones of the molecules in the crystal (Figure S3). Hence, the interatomic distance at 2.4 Å should involve a heavy atom such as sulfur because of its high X-ray scattering power compared to that of other NAC atoms. SEM images of Zn2Al–NAC55 and Zn2Al–Cl55 materials in two distinct magnifications showed platelet-shaped particles (Figure 6). The influence of NAC is evident in the aggregation pattern of the platelets with the observation of a more open arrangement (like a foamy sponge) and is associated with flexible particles. ## 3.2. Vibrational Spectroscopic Characterization of Zn2Al–NAC and NAC Salt Samples According to the curves of distribution of NAC chemical species in the pH range 0–14 (Figure S4) [75], at pH values between 5 (pKa1 = 3.24) and 8 (pKa2 = 9.52), the species with the deprotonated carboxylate group, the mono-anion (NAC)−, is predominant. At pH values higher than the pKa2, NAC presents both carboxylic and thiol groups deprotonated and the contribution of the dianion (NAC)2− increases strongly. The vibrational spectroscopy should be sensitive to such structural modifications and, for this reason, NAC in NaOH aqueous solutions at four different pH values (7.5, 8.5, 9.5, and 11) were prepared and freeze-dried to record their vibrational spectra. FTIR and *Raman spectra* of NAC and their associated sodium salts were shown in Figures S5 and S6, respectively, and also the NAC after solubilization in water (without the pH value adjusting) and freeze-drying. Deprotonation of NAC promoted the disappearing of the band at about 1713 cm−1, assigned to the C=O stretching of the carboxylic group, and the emerging of bands related to the carboxylate group at about 1580–1585 cm−1 (antisymmetric stretching of -COO−) and about 1390–1400 cm−1 (symmetric stretching of -COO−) (Figure S5). A decrease in the intensity of the band at ca. 2550–2545 cm−1, assigned to the S-H stretching, was observed when the pH value was increased. Similarly, the band related to the C-S stretching was shifted from 695 to 685 cm−1 (Figure S6). The FTIR and FT–*Raman spectra* of LDH intercalated with NAC and chloride anions are presented in Figure 7 and Figure 8, respectively. For comparison, the spectra of NAC and NAC-pH11 sample are also shown. The FTIR spectrum of Zn2Al–Cl55 showed bands in the 3500–3400 cm−1 and 1620 cm−1 regions attributed to the O-H (from the layers and water) stretching and to the deformation of H2O, respectively (Figure 7). In the low-energy region, the Zn2Al–Cl55 spectrum presented bands at 422 and 549 cm−1 related to Al–O–H and Zn–O–H translations modes, respectively [54]. The *Raman spectrum* of Zn2Al–Cl55 sample (Figure 8) presented bands at 488 and 548 cm−1 attributed to Al–O–Al and Zn–O–Al stretching, respectively [54]. The vibrational spectroscopic profiles of Zn2Al–NAC55 were rather similar to the spectra of NAC–pH = 11 sample, strongly suggesting that the drug was intercalated in its dianion form (NAC)2− despite the pH of 7.5 applied during the synthesis, probably as a consequence of the highly alkaline character of the interlayer region (see Figure S4). ## 3.3. 13C–NMR Characterization of Zn2Al–NAC55 Sample The solid-state 13C–NMR spectrum of Zn2Al–NAC55 is exhibited in Figure 9a. The chemical integrity of the intercalated species was confirmed by the presence of the five resonance peaks characteristic of the NAC molecule [73]. Chemical shifts for free NAC powder compared to NAC inserted into LDH are as follows: C1 ($\frac{174.7}{177.8}$), C2 ($\frac{55.8}{57.1}$), C3 ($\frac{28.1}{28.6}$), C4 ($\frac{171.4}{173.5}$), and C5 ($\frac{23.2}{22.7}$). Most significant shifts are related to C1 and C4 and both peaks shift to a higher frequency when NAC is intercalated with deprotonated carboxylic group C1 (Δδ = 3.1 ppm) [47,76], corroborating FTIR data, while for C4, the shift suggests that NAC amide group is involved in hydrogen bonds when interleaved compared to the free NAC. The peaks for C3 and C5 atoms of intercalated NAC were broader, but they did not shift when compared to the free NAC (Figure 9a). Deprotonation of the thiol group could result in a chemical shift of the C3 atom, but it was not observed. A chemical shift (Δδ) of about 3–8 ppm for C3 was noticed when the sulfur atom is coordinated to soft Lewis acid such as Pt(II), Au(I), or Ag(I) [77,78,79]. When NAC is coordinated to Zn2+ (an intermediated Lewis acid) by the deprotonated thiol group, the shift Δδ of C3 atom (in D2O at pD equal 6.4) compared to NAC in the same conditions was of 2.1 ppm [80]. Hence, the NAC coordination to Zn2+ was not supported by NMR data because the C3 peak did not shift after the drug intercalation. No peak was observed at approximately 170 ppm, a region for intercalated carbonate ions [81], indicating that the Zn2Al–NAC55 material was not contaminated with carbonate, as also noticed by Raman spectroscopy with the absence of its characteristic stretching band at about 1055 cm−1. The 27Al-NMR spectrum of the Zn2Al–NAC55 was recorded to evaluate the Al coordination sphere (Figure 9b). The chemical displacement value of 9.5 ppm indicated the presence of aluminum with six coordination number, Al(VI), because the chemical shift values for octahedral aluminum range from −10 to 15 ppm [82]. The full width at half maximum (FWHM) of the peak was equal to 15.9 ppm and its shape was slightly asymmetrical (a shoulder was observed in the lower frequency part). This peak broadening could be explained by the fact that MAS is not averaging the second order quadrupolar interaction of 27Al ($I = 7$/2) and/or indicating a slight distortion of the metal site. For the latter, the distortion may occur from a strong tethering/bonding with an interleaved species or a disordered cation distribution within the LDH sheets. In the first hypothesis, a strong bonding should correspond to a weakening in the 6-coordination as explained by a grafting process turning a 6-coordinate to a 5 + 1, thus shifting the contribution towards lower-field values. As the opposite shift was observed (from about 13 to 9 ppm if chloride is replaced by NAC), this hypothesis can be discarded. A perfectly ordered LDH layer comprises 6 surrounding Zn2+cations for each Al3+ cation, as expressed by [Al(OZn)6]. According to the literature [83,84], if a structural disorder occurs in the cation distribution within the LDH layers, some local sites should appear such as [Al(OZn)5(OAl)] or [Al(OZn)4(OAl)2]. The deconvolution of the peak at 9.5 ppm of Zn2Al–NAC55 suggested that Al(VI) ions were in distorted sites, most probably as [Al(OM)5(OAl)] and [Al(OM)4(OAl)2)], identified as Al-1 (peak area = $31.5\%$), Al-2 (peak area = $40.6\%$), and Al-3 (peak area = $27.9\%$), respectively, in Figure 9b. The deconvolution of the peak at 13.1 ppm of Zn2Al–Cl55 sample suggested the existence of a smaller number of Al sites, identified as Al-1 (peak area = $75.3\%$) and Al-2 (peak area $24.7\%$), when compared to the LDH–NAC sample. Therefore, the chloride intercalation promotes a smaller distortion in the metal cation sites than the NAC presence in the interlayer region. ## 3.4. Thermal Analysis Data of Zn2Al-NAC55 Sample For comparison purposes, TGA/DSC and DTG–MS curves of NAC and NAC–pH = 11 samples are shown in Figure S7; the interpretation of the thermal profiles is in the Supporting Materials file. The total weight loss observed after heating NAC–pH = 11 up to 1000 °C is $53.1\%$, indicating that part of sulfur from the organic drug was lost as SO2 at about 250 °C (as observed in the MS curve of NAC in Figure S7) and part was in the calcination residue as sulfate salt (the thermal decomposition of Na2SO4 is over 1000 °C) [85]. Considering the proposed formula Na2(C5H7NO3S)0.45H2O for the NAC–pH = 11 salt (exp.: $3.8\%$ H2O; calc.: $3.8\%$ H2O), a residue consisting of $11.5\%$ of Na2O and $39.6\%$ of Na2SO4 was expected considering the decomposition reaction (Equation [1]): Na2(C5H7NO3S)0.45H2O + 8.5O2 → 0.6Na2SO4 + 0.4Na2O + 5CO2 + 0.4SO2 + NO2 + 3.95H2O[1] The thermal composition of the NAC dianion was modified when intercalated into LDH, resulting in four thermal events for the Zn2Al-NAC55 sample, as shown in Figure 10. The first event (Tinitial = 53 °C, DTG peak at 85 °C), an endothermic process, was associated with the sample dehydration, while the second one (Tinitial = 180 °C, DTG peak at 223 °C) was related to the dehydroxylation of LDH layers with the release of water molecules, as reported for other zinc-based LDH [42,47]. The third event (Tinitial = 291 °C, DTG peak at 371 °C) was assigned to the beginning of NAC thermal decomposition, evidenced by the loss of CO2 molecules. In the fourth step (Tinitial = 646 °C, DTG peaks at 658 and 674 °C), the release of CO2 and SO2 molecules was detected, as shown by the MS curves (Figure 10). For comparison purposes, the TGA/DSC and DTG–MS curves of Zn2Al–Cl55 are shown in Figure S8, while the data discussion was reported in previous work [42]. The residue formed in the Zn2Al–NAC55 decomposition was a mixture of ZnO and spinel (ZnAl2O4) phases, attested by the XRD pattern of the residue. The presence of a non-crystalline sulfate phase in the residue was discarded because its FTIR spectrum did not show bands assigned to this anion, indicating that the sulfur element in the NAC structure was completely converted into a volatile compound. However, the release of SO2 at about 700 °C showed that the metal cations from the layers stabilize sulfur species (probably the sulfate ion). Aluminum and zinc sulfates are decomposed at temperatures higher than 500 °C [85]. ## 3.5. Composition of Zn2Al–NAC55 Sample The chemical elemental analysis (carbon, hydrogen, nitrogen, and metal cations) and the water percentage obtained from TGA for Zn2Al–NAC55 were the following: Zn/Al molar ratio = 2.04, $10.20\%$ C, $2.30\%$ N, and $5.0\%$ H2O. Considering the carbon amount in the sample, the loading capacity of Zn2Al–NAC55 DDS was equal to $27.3\%$ in mass. Considering vibrational spectroscopy and XRD data, NAC was intercalated as the dianion species (i.e., with deprotonated carboxylic and thiol groups). As mentioned in item 3.1, the two samples prepared in this work had an NAC/Al molar ratio equal to 0.65 (Zn2Al–1.3NAC55) and 0.68 (Zn2Al–NAC55). The excess electric charge of LDH layers is related to the presence of Al3+ and it is equal to the number of the trivalent ions. Hence, an NAC/Al molar ratio equal to 0.5 was expected since NAC is present as divalent anion in Zn2Al–NAC55 samples. XRD data suggested that Zn2Al–NAC55 is a single crystalline phase. Hence, the small excess of NAC can be an amorphous material such as Na2NAC adsorbed in the crystalline hybrid material. The proposed composition [Zn2.04Al(OH)6.08](C5H7NO3S)0.5]·1.1H2O plus 0.18 Na2NAC gives an R value equal to 2.04, 10.16 %C, 2.37 %N, and 4.9 %H2O, values very close to those ones obtained experimentally. In this case, the synthesized sample could have $9.3\%$ in mass or $15\%$ in mol of the drug salt of sodium or $7.2\%$ in mass of non-intercalated NAC2−. The presence of the NAC dianion in the sample, as indicated by vibrational spectroscopy, is intricate. At the beginning of the Zn2Al–NAC55 synthesis, the amount of NAC was higher than the amount of metal cations and a reaction of complexation should occur. Complexes of Zn:NAC equal to 1:1 and 1:2 proportions can be formed [86]. Zinc is an intermediate Lewis acid and can coordinate with the NAC sulfur atom (S-coordination) or form a bidentate ligand (S,O-coordination), preferentially in 4-fold coordination. The speciation diagram for Zn-NAC complexes obtained by the pH−potentiometric technique indicated that the major species at pH 7.5 is [Zn(NAC)2]2− (logβ is about 12) [86]. As the synthetic reaction for LDH formation progresses, metal hydrolysis reactions also occur; [Zn(NAC)x(OH)n]2−2x−n species can be formed, involving two kinds of ligands coordinated to a four-fold zinc cation. Therefore, several metal complex species should co-exist in solution at pH around 7.5. As the time of synthesis advances, the precipitation of Zn2Al–NAC55 material resulted from olation reactions among octahedral hydroxide complexes of Zn2+ and Al3+; the positive charge of layers is neutralized by NAC dianions. Despite the pH value of the medium, the stability of the intercalated drug could be enhanced by hydrogen bonding among the confined (NAC)2− ions. ## 3.6. Characterization of Mg2Al–NAC Sample Synthetic parameters were varied aiming for the NAC intercalation into LDH of magnesium and aluminum composition. XRD patterns recorded for materials prepared as described in the Experimental section and isolated using an NAC/Al3+ molar ratio equal to 0.5 or 2, applying or not a post-synthesis thermal treatment for 24 h at 90 °C, produced materials with d[003] basal spacing around 7.53 Å (Figure S9). These data indicated that NAC was not intercalated into LDH. The FTIR spectrum of Mg2Al–NAC sample showed the bands related to the carboxylate group at 1574 cm−1 and 1370 cm−1, denoting the presence of NAC in the sample (Figure S10). The main remark about the spectral profile of Mg2Al–NAC was the identification of a Raman band at 508 cm−1 (Figure S10), assigned to the S-S stretching mode [57]. This result implied that NAC was oxidized in the Mg2Al–NAC sample. At first glance, this fact could be associated with the pH value of the LDH synthesis, but neither NAC–pH = 9.5 nor NAC–pH = 11 samples presented the band at about 508 cm−1. The oxidation of the thiol group of an organic compound (mercaptosuccinate) during LDH synthesis has already been reported [87,88]. The solid-state 13C–CPMAS NMR spectrum of Mg2Al–NAC showed the expected five peaks and other ones. C2 and C3 peaks assigned to thiol group oxidation were observed at 53.9 and 36.9 ppm, respectively (Figure S11). ## 3.7. In Vitro NAC Release Kinectics Experiments The cumulative amounts of NAC released from Zn2Al–NAC55 versus time using the method with agitation (S1 method) and without agitation (S2 method) in SBF medium at 37 °C are shown in Figure 11. After 96 h, 35.6 ± $0.7\%$ of NAC was released under agitation (S1 method), while 20.3 ± $0.1\%$ was observed without agitation (S2 method). The ions tend to migrate from a region of high concentration (simulated physiological solution) to a region of low concentration (the tablet environment and the interlayer region). The diffusion from a site of high to a low concentration, as occurs at the beginning of the release experiment, is more pronounced than the opposite, which occurs mainly in situations of static conditions. However, the solution agitation nearby the tablet can enhance the ions flux with time, which was observed in this work (Figure 11). Considering that NAC is readily soluble in water in its neutral form (solubility equal to 100 mg mL−1) [28], the obtained data suggest a modified release profile by intercalation process in a layered structure. The S1 method agitation process favors sink conditions and allows a higher release when compared to S2 method. Mathematical models were applied to the release data to shed light on the delivery mechanism and evaluate the role of the medium agitation. The concentrations of cations in the solutions after the end of the experiment were quantified to verify if there was leaching of the metal cations from the DDS material. After 96 h of testing applying S1 and S2 methods, the concentrations of zinc cations were 0.45 mg L−1 ($0.17\%$ of the metal in the tablet) and 1.57 mg L−1 ($0.025\%$), respectively. In both conditions, the aluminum cation was not detected because its amount was lower than the limit detection (LD < 0.01 mg L−1). Therefore, the leaching of the metal cations of the layers was minimal, indicating that the drug release mechanism was not related to the carrier solubilization in the SBF medium. The release process studied in this work can be classified as ion exchange, similar to the DDS materials based on ion exchange resins, in which the drug is delivered by the replacement of physiological ions in the medium [89]. The application of mathematical models to fit experimental release data allows understanding the mechanisms involved in the release of a particular drug from a formulation, as well as obtaining parameters about the process rate and maximum amount of drug released, among other information. The kinetics of drug release from drug delivery systems can follow different behaviors, such as the first-order model, which corresponds to a high dose release in a quick and immediate form or a slow, constant and controlled release behavior, defined by zero-order, Higuchi, Hixson–Crowell, and other models [62,63,64,65,89]. The graphics related to the mathematical models acceptable to DDS studied in this work are shown in Figure S12. The release of the drug can occur in a controlled way by different processes, such as diffusion through an inert carrier, diffusion through a membrane or a hydrophilic gel, osmosis, and ion exchange [89,90]. According to the results shown in Table 2, the dependent models that best define the NAC release process from the drug delivery system developed in this work were Hixson–Crowell (R2 = 0.9786) when using the S1 method (basket, 50 rpm) and Higuchi (R2 = 0.9766) with S2 (without agitation). Both the Hixson–Crowell and Higuchi models are applied to controlled release systems. However, in the Hixson–Crowell model, the drug release rate is limited by drug dissolution and not by diffusion. Considering the experimental data about the insignificant amount of zinc and aluminum ions leached from the tablets after 96 h, the release of NAC occurs by anion exchange, as discussed above. The release phenomena should be different when using S1 or S2 methods because agitation favors sink conditions. The Hixson–Crowell and Higuchi equations kinetic models were used to determine T50 (time to release $50\%$ of the drug in the DDS) and T90 (time to release $90\%$ of the drug in the DDS) values for the S1 and S2 methods, respectively. T50 is about 154 and 565 h for the S1 and S2 methods, respectively, while T90 is approximately 453 and 1854 h. According to the values of T50 and T90, the DDS allows a prolonged release, with even NAC showing high solubility. Then, the kinetics data indicated a controlled, constant, and slow-release behavior of the drug from LDH–based DDS that can provide dose maintenance, allowing the achievement of the desired drug concentration in a target tissue. Figure 12 shows the *Raman spectra* of the stratigraphic analysis obtained from the points (R1) to (R3) of the tablets after 96 h. To verify the changes in the internal regions of the tablet after the release experiment, spectra were obtained in regions of its meridional section. In the external region, the spectra of the tablets showed an intensification of the band around 973 cm−1 in relation to the other ones. This band is assigned to the νs(P-O) mode of the HPO42− anion [91,92]. After 96 h, the internal region of the tablets was unmodified, suggesting that the NAC anion exchange by hydrogen phosphate did not reach the interior region of the tablet yet, as indicated by the release profile (Figure 11). The SBF solution has other anions that can promote the NAC release by ion exchange such as chloride which is in higher concentration in the simulated physiological medium than HPO42− anion, which cannot be identified by Raman spectroscopy. Figure 13 presents a simple schematic representation of the NAC release process from LDH: initially, the SBF solution moistens the LDH carrier system promoting an intra-aggregate ion diffusion; next, ion diffusion reaches an inter-particle region; finally, ions from the SBF solution migrate into a diffusion film coating the primary particles and ion exchange of NAC by anions such as HPO42− takes place by intra-particle or interlayer diffusion. ## 4. Conclusions LDH–NAC hybrid material composed of Zn/Al cations was successfully synthesized by co-precipitation method and an improved crystallinity was observed when the temperature of synthesis was raised to 55 °C. XRD data confirmed the formation of a crystalline layered material with an interlayer distance of 16.38 Å, resulting from a confined/constrained NAC bilayer arrangement, indicated by the calculated Patterson electrons density map. FTIR, Raman, and 13C–NMR spectroscopic data confirmed the integrity of NAC after intercalation, and vibrational spectroscopy also showed that NAC had two negative charges when confined into LDH. On the other hand, the composition Mg/Al did not stabilize the drug but promoted its partial oxidation. The 27Al-NMR spectrum of Zn2Al–NAC55 showed peaks associated with distinct aluminum sites with a coordination number of six but did not indicate the coordination of NAC to the hydroxylated layers. These results, together with chemical and thermal analysis, allowed the proposition of the chemical formula of the Zn2Al–NAC55 DDS, whose loading capacity was equal to $27.3\%$ in mass. The in vitro release of NAC from the Zn2Al–LDH carrier with and without agitation was 35.6 ± $0.7\%$ and 20.3 ± $0.1\%$, respectively, after 96 h in SBF medium. The release profile fits the Hixson–Crowell and Higuchi kinetic models for the S1 and S2 methods, respectively. Kinetics data indicated that NAC is released from the Zn2Al LDH in a controlled, mostly constant, and slow mode, contrasting with the free drug, which has high solubility in water. Raman spectra along the cross section of the Zn2Al–NAC tablets recorded after the release assays allowed the elucidation of the release process, driven by ion diffusion and preservation of LDH structural integrity The LDH carrier containing the antioxidant NAC may be of interest in the pharmaceutical and medical fields as an implantable DDS material for tissue engineering because of its controlled and slow-release properties highlighted in this work, as well as the biological activity of NAC and zinc ions in tissue repair. ## References 1. Rind L., Ahmad M., Khan M.I., Badruddeen J., Akhtar U., Ahmad C., Yadav M.. **An Insight on Safety, Efficacy, and Molecular Docking Study Reports of N-Acetylcysteine and Its Compound Formulations**. *J. Basic Clin. Physiol. Pharmacol.* (2022.0) **33** 223-233. 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--- title: 'Wild Artichoke (Cynara cardunculus subsp. sylvestris, Asteraceae) Leaf Extract: Phenolic Profile and Oxidative Stress Inhibitory Effects on HepG2 Cells' authors: - Rosaria Acquaviva - Giuseppe Antonio Malfa - Rosa Santangelo - Simone Bianchi - Francesco Pappalardo - Maria Fernanda Taviano - Natalizia Miceli - Claudia Di Giacomo - Barbara Tomasello journal: Molecules year: 2023 pmcid: PMC10054820 doi: 10.3390/molecules28062475 license: CC BY 4.0 --- # Wild Artichoke (Cynara cardunculus subsp. sylvestris, Asteraceae) Leaf Extract: Phenolic Profile and Oxidative Stress Inhibitory Effects on HepG2 Cells ## Abstract Cynara cardunculus subsp. sylvestris (wild artichoke) is widespread in Sicily, where it has been used for food and medicinal purposes since ancient times; decoctions of the aerial parts of this plant have been traditionally employed as a remedy for different hepatic diseases. In this study, the phenolic profile and cell-free antioxidant properties of the leaf aqueous extract of wild artichokes grown in Sicily (Italy) were investigated. The crude extract was also tested in cells for its antioxidant characteristics and potential oxidative stress inhibitory effects. To resemble the features of the early stage of mild steatosis in humans, human HepG2 cells treated with free fatty acids at the concentration of 1.5 mM were used. HPLC-DAD analysis revealed the presence of several phenolic acids (caffeoylquinic acids) and flavonoids (luteolin and apigenin derivatives). At the same time, DPPH assay showed a promising antioxidant power (IC50 = 20.04 ± 2.52 µg/mL). Biological investigations showed the safety of the crude extract and its capacity to counteract the injury induced by FFA exposure by restoring cell viability and counteracting oxidative stress through inhibiting reactive oxygen species and lipid peroxidation and increasing thiol-group levels. In addition, the extract increased mRNA expression of some proteins implicated in the antioxidant defense (Nrf2, Gpx, and SOD1) and decreased mRNA levels of inflammatory cytokines (IL-6, TNF-α, and IL-1β), which were modified by FFA treatment. Results suggest that the total phytocomplex contained in wild artichoke leaves effectively modulates FFA-induced hepatic oxidative stress. ## 1. Introduction Cynara L. (Asteraceae) is a small genus native to the Mediterranean area. Only a few taxa comprise this genus, including wild artichoke (*Cynara cardunculus* (L.) subsp. sylvestris Lam.), which is considered the wild progenitor of the globe artichoke (*Cynara cardunculus* (L.) subsp. scolymus (L.) Hegi) and of the leafy or cultivated cardoon (*Cynara cardunculus* (L.) var. altilis DC.) [ 1,2]. Artichoke is an edible and medicinal plant with a long tradition of use, which dates to the ancient Egyptians, Greeks, and Romans [3]. The edible part of both wild and cultivated species consists of the immature inflorescences (capitula or heads), which are consumed as a vegetable worldwide [4], whereas the leaves are traditionally used as a herbal remedy against liver complaints as hepatoprotective, choleretic, diuretic, and lipid-lowering agents [1,5,6,7]. Recently, the Committee on Herbal Medicinal Products (HMPC) of the European Medicines Agency (EMA) recognized preparations from C. cardunculus leaves as herbal remedies for the symptomatic relief of digestive disorders [8]. Cynara cardunculus subsp. sylvestris (C. sylvestris) is a robust perennial plant with wide, spiny leaves that form a large characteristic rosette in winter, showing a branched flowering stem in late spring and blue-violet flowers [9,10]. It is native to the Mediterranean Basin, and it is also found in south Portugal, in the Canary Islands, and in the Azores Islands [2]. In post-Columbian times, wild artichoke colonized parts of the New World, and it is now a weed in some areas of Argentina, Chile, and California [10]. Wild artichoke is widely present in Sicily (Italy), where it has been used for food and medicinal purposes since ancient times. Despite of this, the potential of wild Sicilian artichoke as a source of biologically active compounds is still underexplored; indeed, only few studies about the phenolic composition of different plant parts have been carried out [11,12]. Cynara cardunculus taxa have been shown to be a rich source of a large variety of active phytochemicals; most of the biological activities reported are ascribed to the phenolic compounds contained in the different plant organs, represented by various classes, namely hydroxycinnamic acid derivatives and flavonoid derivatives [5,13,14]. Among them, C. cardunculus subsp. scolymus, the globe artichoke, has been studied extensively due to its economic importance; indeed, in addition to its nutritional and phytochemical interest, this species is utilized for several industrial applications [4,5,13,15]. Due to their long-standing medicinal uses, artichoke leaves have been the subject of several investigations; many of these have focused on the potential of artichoke leaf extracts for liver protection [13,14,16]. Recently, the positive benefits on liver steatosis (NAFLD) have been demonstrated both in preclinical studies and in clinical trials for artichoke extracts, alone or in combination with nutraceuticals; a few of these studies highlighted the beneficial effects of wild artichoke on liver [17,18,19,20,21]. Both the two-hit and the newer multiple parallel hits theory on NAFLD inflammatory and fibrotic progression hypothesize the involvement of oxidative stress in free fatty acid (FFA)-induced lipotoxic liver injuries [22,23]. In this context, the present work aimed at deepening the knowledge of wild artichoke leaves as valuable sources of bioactive compounds helpful in counteracting oxidative stress conditions in an in vitro model of early stages of liver steatosis. For the current study, the leaves of C. cardunculus subsp. sylvestris grown in Sicily were utilized; an aqueous extract was prepared, with water being the solvent commonly utilized for traditionally used artichoke herbal preparations [8]. The phenolic compounds contained in the extract were characterized via HPLC-DAD analysis. The antioxidant ability was established in vitro via the DPPH test, and the antioxidant effects were evaluated in steatotic HepG2 cells via the determination of ROS thiol groups (RSH), of lipid peroxides (LOOH), of mRNA expression levels of antioxidant defense markers (Nrf2, Gpx, and SOD1), and of inflammatory cytokines (TNF-α, IL-1β, and IL-6). The potential cytotoxicity of the extract was defined by an MTT test on HepG2 cells and by the *Artemia salina* lethality assay. ## 2.1. Phytochemical Analysis The total flavonoid content (TFC) and the total phenolic content (TPC) of C. sylvestris extract were equal to 50.32 ± 1.62 mg catechin equivalent (CE)/g extract and 185.21 ± 1.97 mg gallic acid equivalent (GAE)/g extract, respectively (Table 1). The phytochemical profile obtained via HPLC-DAD revealed the presence of several phenolic acids (caffeoylquinic acids) and flavonoids such as luteolin and apigenin derivatives (Figure 1, Table 2). ## 2.2. Cell Viability The MTT assay demonstrated that treatment for 24 h of C. sylvestris leaf extract at different concentrations (10–50 μg/mL) is not cytotoxic for HepG2 cells (data not reported); in contrast, treatment of HepG2 cells for 12 h with FFAs [1.5 mM oleic acid and palmitic acid (2:1)], which reproduces an in vitro model of early stages of liver steatosis, reduces viability by approximately $40\%$. Pre-treatment, on the other hand, with the extract for 24 h can counteract the damage caused by FFA exposure. Particularly, the cells pre-treated with 50 µg/mL of extract showed a cell viability value comparable to that recorded in control cells (Figure 2). ## 2.3. Cell-Free Antioxidant Properties The antioxidant activity of C. sylvestris was assessed via the DPPH test. As reported in Table 1, the extract exhibited a concentration-dependent quenching effect with an IC50 value of 20.04 ± 2.52 µg/mL, which is equivalent to 15 μM ± 0.62 of Trolox. ## 2.4.1. Cynara sylvestris Extract Reduced Reactive Oxygen Species Levels Figure 3 shows that FFA treatment significantly increased ROS levels, while the pre-treatment with the extract significantly counteracted ROS production only at the concentration of 50 μg/mL. ## 2.4.2. Cynara sylvestris Extract Reduced Lipid Hydroperoxide Levels The exposure of HepG2 cells with FFAs for 12 h induced an increment in LOOH levels compared to untreated controls; pre-treatment with extract exerted a protective effect only at the concentration of 50 μg/mL (Figure 4). ## 2.4.3. Cynara sylvestris Extract Preserved Total Thiol Group Levels The exposure of HepG2 cells to FFAs slightly reduced RSH levels compared to untreated cells, and interestingly, RSH content was improved only by the pre-treatment with the extract at 50 μg/mL; at this concentration, RSH levels were higher than in control cells (Figure 5). ## 2.4.4. Effect of Cynara sylvestris Extract on Nrf2, Gpx, SOD1 mRNA Expression Levels As depicted in Figure 6A–C, exposure to FFAs markedly reduced mRNA expression levels of Nrf2 and Gpx, while the pre-treatment with C. sylvestris extract dose-dependently increased all examined genes, including SOD1, which was not affected by FFAs exposure. ## 2.4.5. Effect of Cynara sylvestris Extract on TNF-α, IL-6, and IL-1β mRNA Expression Figure 7 shows that the increased mRNA expression of inflammatory cytokines (IL-6, TNF-α, and IL-1β), which was induced by FFAs exposure, was partially counteracted by the pre-treatment with the extract. ## 2.4.6. Artemia salina Lethality Bioassay The evaluation of the toxic action of plant extracts is essential to consider a treatment safe; *Artemia salina* *Leach is* a small aquatic crustacean routinely used to perform different tests for preliminary toxicity estimation. Brine shrimp lethality is a short-term biological assay widely utilized for plant extracts in order to determine their potential toxicity [24]. The main advantages of using A. salina are the possibility of continuous supply and long storage of the cysts, the ease of keeping samples in laboratory conditions, and the inexpensive culture requirements [25]. After treatment with C. sylvestris leaf extract for 24 h, the A. salina larvae were all alive, even at the highest tested concentration of 1000 µg/mL. The results of this assay indicate the potential safety of the extract according to Clarkson’s toxicity criterion, which classifies plant extracts with an LC50 (median lethal concentration) above 1000 μg/mL as non-toxic [24]. ## 3. Discussion ROS production is an indirect result of aerobic metabolism; however, an increase in prooxidant products, when associated with an impairment in the endogenous antioxidant system, leads to a condition of oxidative stress. This harmful state is frequently observed during the inflammatory process of tissues and is involved in the etiology of most non-communicable diseases, including NAFLD and NASH [26,27,28]. The latest multiple parallel hits theory on NAFLD pathogenesis confirmed the role of oxidative stress in the lipotoxic liver injuries caused by FFAs, which was first hypothesized in the two hits theory [23]. Several studies have demonstrated that different classes of plant secondary metabolites can prevent and ameliorate oxidative stress in both physiological and pathological conditions and have highlighted that a polyphenol-rich diet exerts protective effects against the initiation and progression of different non-communicable and infectious diseases [29,30,31]. The beneficial effects of polyphenols are mainly attributable to their antioxidant activities, which are responsible for reducing chronic inflammation of tissues and preventing cell damage, even at the molecular level. Cynara cardunculus taxa contain considerable quantities of polyphenols, mainly caffeoylquinic acid, apigenin, and luteolin derivatives. In this study, the crude aqueous extract from leaves of C. sylvestris grown in the wild in Sicily showed a significant amount of phenolic compounds (185.21 ± 1.97 mg GAE/g), as determined spectrophotometrically, of which slightly less than $30\%$ is represented by flavonoids (50.32 ± 1.62 mg QE/g) (Table 1). The above results comply with a previous study in which a higher amount of polyphenols was found in the leaves of wild artichoke than in cultivated varieties [32]. Moreover, the highest content of phenolic compounds in that study was found in a leaf sample of wild artichoke from the same area of Sicily (Syracuse, Italy), where the leaves of this study were collected. The phytochemical profile determined via HPLC-DAD showed the presence of several phenolic acids, such as caffeoylquinic acid derivatives, including cynarine, and flavonoids, such as luteolin and apigenin derivatives (Figure 1), which are characteristic secondary metabolites of C. cardunculus spp. with broad antioxidant properties, as confirmed by the good free radical scavenging properties highlighted in the DPPH assay (IC50 20.04 ± 2.52 µg/mL). These results confirmed the higher radical scavenger activity of wild artichoke with respect to the cultivated forms (globe artichoke) [33,34]. Starting from these extract characteristics and the absence of toxicity at the employed concentrations (Figure 2), the current study aimed to deepen existing knowledge of the protective effects of C. sylvestris extract on the redox state of human hepatoma cells in an in vitro model resembling the early stages of liver steatosis. In this model, HepG2 cells exposed for 12 h to FFAs at a total concentration of 1.5 mM exhibited a significant increase in ROS and LOOH levels and a slight decrease in RSH content. As previously reported, hepatocyte mitochondria increase beta-oxidation as a protective response to the presence of FFAs, with consequent enhancement of ROS production responsible for lipid peroxidation and depletion of intracellular glutathione [22,23]. In subjects with metabolic syndrome (type 2 diabetes or obesity), these cellular events add to ROS generated in the gut and adipose tissue, setting up a severe oxidative stress condition that leads to mitochondrial dysfunction and a gain in triglyceride (TG) accumulation in hepatocyte cytoplasm [22,23]. FFA-induced steatosis in HepG2 cells is associated with ROS production and consequent lipid peroxidation, which is also strictly related to the decrease in some antioxidant enzymes such as SOD1 and a concomitant increase in proinflammatory mediators including TNF-α [35,36]. The pre-treatment with the crude extract at 50 µg/mL significantly counteracted ROS production, shielding lipids from peroxidation and the intracellular RSH amount (Figure 3, Figure 4 and Figure 5). These results conform with previous studies carried out in different experimental models on the antioxidant effects of extracts from cultivated varieties of C. scolymus [37,38]. The antioxidative effects of plant secondary metabolites can be exerted via direct reaction with free radicals or indirectly at the molecular level by modulating the activity or expression of the intracellular enzymes involved in promoting or counteracting oxidative stress [39]. Particularly, phenolic compounds are capable of inducing the activation of the Nrf2-antioxidant response element signaling pathway by increasing both activities and expressions of several antioxidant enzymes, including the superoxide dismutase (SOD) to convert O2• into H2O2 and the glutathione peroxidase (GPX) to remove it [40]. Even at the molecular level, the pre-treatment for 24 h with the phytocomplex contained in the C. sylvestris leaf extract at all tested concentrations exerted its antioxidant effects in HepG2 cells exposed to FFAs by increasing the mRNA expression levels of the transcription factor Nrf2 (nuclear factor E2-related factor 2) in a dose-dependent way and the mRNA expression levels of the endogenous antioxidant enzymes SOD1 and GPX markedly. These results highlight that C. sylvestris extract exerts its protective effects both by its direct scavenger activity and indirectly by the regulation at molecular levels of the antioxidant cellular defenses. High levels of ROS such as H2O2 in hepatocytes that have been exposed to FFAs are directly correlated with a promotion of an inflammatory response mediated by pro-inflammatory mediators such as TNF-α, IL-1β, and IL-6, particularly TNF-α and ROS, which are positively promoted by each other [41] and are capable of inducing apoptotic cell death in steatotic hepatocytes [42]. In our experimental model, the exposure of HepG2 cells to FFAs significantly promoted mRNA expression levels by about three-fold with respect to the control cells for all the examined pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6), but only the pre-treatment with the C. sylvestris extract at 50 µg/mL partially counteracted the deleterious consequence to FFA treatment (Figure 7). The protective effects on the cellular oxidative state and the inflammatory response in FFA-exposed HepG2 cells were clearly shown in the MTT assay, in which the pre-treatments with the different concentrations of C. sylvestris extract dose-dependently preserved cell viability; in particular, the highest concentration of 50 µg/mL definitely protected the mitochondrial functionality, which was compromised by the subsequent FFA exposure at about the level of control cells (Figure 2). In conclusion, results obtained in these in vitro experiments showed that C. sylvestris aqueous leaf extract could act with different mechanisms of action, effectively counteracting oxidative stress induced by FFA, especially at the highest concentration of 50 µg/mL, both by increasing RSH levels and turning off ROS production and lipid peroxidation and also by beneficially modulating cytoprotective Nrf2/ARE-regulated genes, thus mitigating the inflammatory response. Our findings are supported by previous studies reporting significant antioxidant and hepatoprotective activities exerted by several polyphenols present in Cynara spp. such as chlorogenic acid, dicaffeoylquinic acid, luteolin, and apigenin derivatives [43,44,45,46,47]. These results suggest that the total phytocomplex contained in C. sylvestris leaf is a valuable source of bioactive compounds that are effective in counteracting transient or mild conditions of hepatic oxidative stress, adding new evidence to the previous studies on the hepatoprotective properties of taxa belonging to the Cynara genus. Thanks to the ease of growing this species in poor and stony soils without adding water, this species, which is not fully exploited, may constitute a sustainable economic resource for the natural health product industry. ## 4.1. Chemicals and Reagents Analytic-grade organic solvents were purchased from VWR (Milan, Italy). UHPLC-grade water (18 mW), UHPLC-grade MeOH, and formic acid were obtained from Carlo Erba (Milan, Italy). 2,2-diphenyl-1-picrylhydrazyl (DPPH); xylenol orange; 2′,7-dichlorofluorescein diacetate (DCFH-DA); 2,2-dithio-bis-nitrobenzoic acid; tetrazolium salt; free fatty acids; oleic acid; and palmitic acid (purity ≥ $99\%$) were purchased from Sigma-Aldrich (Milano, Italy), except as otherwise specified. ## 4.2. Plant Collection and Extraction Procedure Cynara sylvestris was harvested in the seacoast area of Syracuse (Sicily, Italy) in May 2022 (Figure 8) and authenticated by botanist F.M. Raimondo. A voucher specimen (No. $\frac{05}{22}$) was deposited in the herbarium of the Department of Drug and Health Sciences, Section of Biochemistry. After harvesting, fresh leaves were stored at −80 °C. An amount of 100 g of crushed plant material was extracted at 90 °C in water for 1 h (ratio 1:10). The extraction was repeated three times; then, the pooled solutions were filtered and evaporated to dryness with a rotatory evaporator, obtaining about 5.6 g of dry extract. ## 4.3. Determination of Total Flavonoid and Total Phenolic Content In the extract, the content of TFC, which was analyzed spectrophotometrically, was compared with a calibration curve of a known quantity of catechin and expressed as mg of CE/g extract [48]. TPC was evaluated using the Folin–Ciocâlteu method [49]. The value obtained, compared with a calibration curve of a known quantity of gallic acid, was expressed as mg of GAE/g extract. Data were obtained from three independent determinations. ## 4.4. HPLC-DAD Analysis High-pressure liquid chromatography (HPLC) was used to evaluate the polyphenolic fingerprinting of the extract as described above [50]. HPLC-DAD analyses were performed using a Shimadzu LC 20 (Kyoto, Japan), which was equipped with a diode array detector (DAD) and with a 150 × 4.6 mm i.d., 2.7 μm Ascentis Express C 18 column. The mobile phases were as follows: H2O/H3PO4 (99:1, solvent A), MeOH/CAN/H3PO4 (49,5:49,5:1, solvent B). The gradient used was as follows: concentration of the solvent A of $95\%$ going to $77\%$ (34 min), maintained at $77\%$ (3 min), $74\%$ (60 min), $60\%$ (85 min), $20\%$ (90 min), and $0\%$ (92 min). The total time was 105 min. The column temperature was maintained at 25 °C. The flow was 1 mL/min, and the injection volume was 5 μL. The chromatogram profiles were recorded from 190 to 500 nm and monitored at 280 and 330 nm ± 2 nm. ## 4.5. DPPH Test The DPPH test measures the quenching capacity of the extract spectrophotometrically at λ = 517 nm, as previously reported by Salerno [51]. The results, which were compared with Trolox (30 µM), were expressed as IC50 of the decrease in absorbance and represent the average ± S.D. of three independent experiments in triplicate. ## 4.6. Cell Culture and Treatments The human hepatoma cell line (HepG2), which was obtained from ATCC® HB-8065 (Rockville, MD, USA), was maintained in modified Eagle’s medium (MEM) supplemented with $10\%$ v/v fetal bovine serum (FBS), 100 U/mL penicillin, and 100 µg/mL streptomycin. HepG2 cells were cultured in a humidified atmosphere in $5\%$ CO2 at 37 °C, and at sub-confluent conditions, they were plated at a constant density to obtain identical experimental conditions in the different tests. ## 4.7. MTT Assay To evaluate cell viability, we used the MTT test, which measures the conversion of tetrazolium salt to yield colored formazan in the presence of metabolic activity. The amount of formazan is proportional to the number of living cells. The absorbance of the converted formazan was measured using a microplate spectrophotometer reader (Titertek Multiskan, Flow Laboratories, Helsinki, Finland) at λ = 570 nm. The results were presented as a percent of the control data [52]. HepG2 cells were treated for 12 h with FFAs (OA:PA at 2:1) at the total concentration of 1.5 mM, thereby resembling the features of mild steatosis in humans. To evaluate the protective effects of the extract, 24 h prior to the addition of FFAs, cells were pre-treated with C. sylvestris extract (10–25-50 µg/mL). The results are presented as a percentage of cell viability with respect to untreated control cells ($100\%$). ## 4.8. Reactive Oxygen Species Assay ROS levels were determined by using the 2′,7-dichlorofluorescein diacetate (DCFH-DA) fluorescent probe [53]. Briefly, differently treated and untreated HepG2 cells (1.5 × 105 cells/mL) seeded in 6-well plates were incubated for 30 min with DCFH-DA (5 µM) at 37 °C. After cells were washed three times with PBS and treated with 1 mL of digitonin (2.5 mg/mL) at room temperature for 1 h and finally scraped, the obtained suspensions were centrifuged at 4 °C, 13,000× g for 10 min. Supernatants were used to determine ROS levels. Fluorescence (corresponding to oxidized radical species 2′,7′-dichlorofluorescein, DCF) was monitored spectrofluorimetrically (excitation, λ = 488 nm; emission, λ = 525 nm). Total protein content was evaluated for each sample, and the results are reported as a percentage of fluorescence intensity/mg of protein relative to the control. The protein content was determined using the Sinergy HTBiotech instrument by measuring the difference in absorbance at λ = 280 and λ = 260. ## 4.9. Lipid Peroxidation Determination LOOH levels were evaluated via the oxidation of Fe+2 to Fe+3, which, in the presence of xylenol orange, produces the Fe(3+)-xylenol orange complex [53]. Differently treated and untreated HepG2 cells (1.5 × 105 cells/mL) seeded in 6-well plates were scraped and washed three times with PBS. After centrifugation at 4 °C, 900× g for 10 min, the cellular pellet was resuspended in 500 μL of PBS and used to determine LOOH levels. The test was performed in a total volume of 1 mL; in particular, 200 μL of cellular suspension was added to 800 μL of a working solution of 100 μM xylenol orange, 250 μM ammonium ferrous sulfate, 4 mM butylated hydroxytoluene, and 25 mM H2SO4 in $90\%$ methanol (V/V). After 30 min of incubation at room temperature, the absorbance at λ = 560 nm was measured using a U2000 Hitachi spectrophotometer (Tokyo, Japan). Calibration was obtained using hydrogen peroxide (0.2–20 μM). The results are expressed as a percentage of the increase with respect to the control (untreated cells). ## 4.10. Determination of Total Thiol Groups Non-protein total thiol groups were determined using a spectrophotometric assay based on the reaction of thiol groups with 2,2-dithio-bisnitrobenzoic acid (DTNB) at λ = 412 nm [53]. In total, 200 μL of differently treated and untreated HepG2 cell suspension was added to 600 μL of TRIS base (0.25 M pH 8.2), followed by 400 μL of DTNB (10 mM) in absolute ethanol. After samples were incubated at room temperature for 20 min and centrifuged at 3000× g for 10 min at room temperature, the supernatants were used to determine total thiol group levels. Results are expressed as a percentage of the increase compared to the control (untreated cells). ## 4.11. RNA Extraction and Reverse Transcription-Quantitative Polymerase Chain Reaction HepG2 cells (1.5 × 105 cells/mL) seeded in 6-well plates were pretreated with C. sylvestris extract (10–25–50 mg/mL) for 24 h, followed by FFA exposure for 12 h. Total RNA was recovered by using TRIzol (Invitrogen, Carlsbad, CA, USA) and following the manufacturer’s instructions. Reverse transcription of 1 µg of total RNA was performed with a QuantiTect Reverse Transcription Kit (Qiagen Inc., Valencia, MD, USA). The cDNA obtained subsequently amplified by qPCR using the QuantiNova SYBR Green RT-PCR Kit according to the manufacturer’s instructions on Rotor-Gene Q5PLEX. Specific predesigned and bioinformatically validated primer sequences (QuantiTect Primer Assays, Qiagen Inc., Valencia, MD, USA) for inflammation genes TNFα (QT00029162), IL1β (QT00021385), and IL6 (QT00083720) and oxidative-stress-responsive genes Nrf2 (QT), SOD1 (QT01671551), and GPX (QT00203392) were used, according to previously described methods [54]. The expression levels of targets were normalized with RPLP0 (Ribosomal Protein Lateral Stalk Subunit P0) mRNA levels. Relative fold changes in gene expression were calculated using the 2−ΔΔCt method. ## 4.12. Artemia Salina Lethality Bioassay The toxicity of C. sylvestris leaf extract was also investigated in a living organism, i.e., *Artemia salina* Leach, by performing the lethality bioassay according to the protocol previously reported by Meyer et al. [ 55], with some modifications. Artemia salina cysts were placed in a hatchery dish containing artificial seawater (32 g sea salt/L) and incubated for hatching under a 60 W lamp, at a temperature of 24–26 °C. Twenty-four hours after hatching, ten brine shrimp larvae were placed in plates containing 5 mL of artificial seawater mixed with different volumes of the extract solution to obtain final concentrations in the range 10–1000 µg/mL, and the larvae were incubated at 24–26 °C for 24 h. At this time point, the surviving larvae were counted; then, LC50 (median lethal concentration) was estimated. Three replicates of each sample concentration were tested. 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--- title: Acetylcholine Esterase Inhibitory Effect, Antimicrobial, Antioxidant, Metabolomic Profiling, and an In Silico Study of Non-Polar Extract of The Halotolerant Marine Fungus Penicillium chrysogenum MZ945518 authors: - Heba El-Sayed - Marwa A. Hamada - Ahmed A. Elhenawy - Hana Sonbol - Asmaa Abdelsalam journal: Microorganisms year: 2023 pmcid: PMC10054823 doi: 10.3390/microorganisms11030769 license: CC BY 4.0 --- # Acetylcholine Esterase Inhibitory Effect, Antimicrobial, Antioxidant, Metabolomic Profiling, and an In Silico Study of Non-Polar Extract of The Halotolerant Marine Fungus Penicillium chrysogenum MZ945518 ## Abstract Major health issues, such as the rise in oxidative stress, incidences of Alzheimer’s disease, and infections caused by antibiotic-resistant microbes, have prompted researchers to look for new therapeutics. Microbial extracts are still a good source of novel compounds for biotechnological use. The objective of the current work was to investigate marine fungal bioactive compounds with potential antibacterial, antioxidant, and acetylcholinesterase inhibitory effects. Penicillium chrysogenum strain MZ945518 was isolated from the Mediterranean Sea in Egypt. The fungus was halotolerant with a salt tolerance index of 1.3. The mycelial extract showed antifungal properties against Fusarium solani with an inhibitory percentage of 77.5 ± 0.3, followed by Rhizoctonia solani and *Fusarium oxysporum* with percentages of 52 ± 0.0 and 40 ± 0.5, respectively. The extract also showed antibacterial activity against both Gram-negative and Gram-positive bacterial strains using the agar diffusion technique. The fungal extract was significantly more effective with *Proteus mirabilis* ATCC 29906 and *Micrococcus luteus* ATCC 9341; inhibition zones recorded 20 and 12 mm, respectively, compared with the antibiotic gentamycin, which recorded 12 and 10 mm, respectively. The antioxidant activity of the fungus extract revealed that it successfully scavenged DPPH free radicals and recorded an IC50 of 542.5 µg/mL. Additionally, it was capable of reducing Fe3+ to Fe2+ and exhibiting chelating ability in the metal ion-chelating test. The fungal extract was identified as a crucial inhibitor of acetylcholinesterase with an inhibition percentage of $63\%$ and an IC50 value of 60.87 µg/mL. Using gas chromatography–mass spectrometry (GC/MS), 20 metabolites were detected. The most prevalent ones were (Z)-18-octadec-9-enolide and 1,2-Benzenedicarboxylic acid, with ratios of 36.28 and $26.73\%$, respectively. An in silico study using molecular docking demonstrated interactions between the major metabolites and the target proteins, including: DNA Gyrase, glutathione S-transferase, and Acetylcholinesterase, confirming the extract’s antimicrobial and antioxidant activity. Penicillium chrysogenum MZ945518, a halotolerant strain, has promising bioactive compounds with antibacterial, antioxidant, and acetylcholinesterase inhibitory activities ## 1. Introduction Antibiotic resistance has become a problem for our society and public health because it has made it possible for infectious diseases to come back and pose a threat to people’s health [1]. Many chronic conditions, including cancer, diabetes, arteriosclerosis, neurological illnesses, and heart illnesses, are believed to result from the oxidative damage that free radicals inflict [2]. Therefore, finding secondary metabolites having biological effects against cancer, microbes, tropical diseases, and other conditions has been the focus of extensive research [3]. Marine microorganisms are a possible sustainable source of novel physiologically active compounds because the biodiversity of the oceans makes up $50\%$ of the total biodiversity of the world [4]. Marine microbes are a source of intriguing secondary metabolites because they thrive in challenging environments, including cold, dark, and high pressures, or in conjunction with other species [5]. To survive in such diverse environments, they have developed a variety of adaptation methods, including the development of specific metabolites [4]. Furthermore, marine organisms are able to produce a broad variety of novel molecules due to the sea’s harsh chemical and physical circumstances; these molecules are unique in diversity, structural properties, and functional aspects compared to compounds isolated from terrestrial plants [6]. These extra molecules are a source of possible new pharmaceutically active drugs [7]. Cladosporium, Aspergillus, Chaetomium, Penicillium, and Trichoderma species possess a combination of morphological and physiological adaptations that make them well suited to life in the sea. This group of organisms is classified as “facultative marine fungi” [8]. The most prevalent fungi found in both indoor and outdoor habitats, including marine substrates, such as sponges, corals, algae, and sand, are Penicillium species [9]. Penicillium species that are derived from marine habitats are possible sources of distinctive substances with biological activity that are generated as a result of the natural circumstances of marine environments [8]. There are numerous species within the genus, some of which are commercially important in nutrition, biomedical, and pharmaceutical production [10]. Due to the abundance of bioactive components, such as flavonoids, alkaloids, minerals, proteins, phenols, tannins, vitamins, and antioxidant characteristics, these organisms were able to biosynthesize a diverse array of primary and secondary metabolites [11]. Anticancer, antibacterial, and antioxidant effects are demonstrated by many species of this genus [12]. Penicillium chrysogenum is a well-known and excellent example of useful fungi. The fungus piqued biologists’ interests, especially in the realm of drug development, because it produces the antibiotic penicillin [13]. *The* genetic variations among and within the varieties of the species have been studied. James Scott [14] categorized the indoor isolates from *Penicillium chrysogenum* into four clades, and Bank et al. [ 15] investigated the genetic variance between different types and isolates from P. chrysogenum. The metabolites isolated from different varieties of the species showed antioxidant, antimicrobial, and anticancer activities [10,16]. The current study set out to investigate the gas chromatography–mass spectrometry (GC/MS) -based metabolic profiling, and the antimicrobial, antioxidant, and acetylcholinesterase inhibition activities of the non-polar ethyl acetate extract of *Penicillium chrysogenum* MZ945518 mycelia isolated from the Mediterranean Sea with a docking study of the major bioactive metabolites. ## 2.1. The Fungal Culture Used Penicillium chrysogenum MZ945518 was isolated from the Mediterranean coast of Alexandria, Egypt and identified using molecular techniques, as we previously described [17]. After 7 days of cultivation on potato dextrose agar medium, morphological characteristics were examined, and the developed colony was examined under light microscope. ## 2.2. Halotolerance Test Frisvad’s modified procedure was used to conduct the halotolerance test [18]. Potato dextrose agar (PDA) was employed as the growth medium in this study and supplemented with 0, 2.5, 5, 10, 15, 20, 25, and $30\%$ NaCl concentrations. The fungus was seeded in the plate center and cultured at 28 °C for 10 days, after which the growth diameter was measured. The salt tolerance index (Ti) was determined by dividing the diameters of colonies grown in PDA and colonies grown in PDA plus NaCl. Ti values were found to be oppositely related to halophily. This means that the more halophily there is, the lower the Ti value. Fungi with index values less than one were deemed halophilic, whereas those with index values greater than one were deemed halotolerant. ## 2.3. Extraction of Fungal Metabolites The P. chrysogenum discs (6 mm) were placed in flasks with potato dextrose broth and cultured for 7 days at 25 °C in a static incubator. Thereafter, mycelia were harvested by ultracentrifugation (Sigma, 3–16 PK, Osterode am Harz, Germany) for 10 min at 4 °C and 10,000 rpm, and the culture supernatant was discarded. The obtained mycelia were extracted with ethyl acetate (Sigma-Aldrich, Burlington, MA, United States) solvent (EtOAc) (1:2). At 40 °C, the resulting extract was concentrated using a rotary evaporator (IKA, Germany). ## 2.4.1. The Reference Pathogens The antibacterial effect of the fungal ethyl acetate extract was evaluated in vitro against six different reference bacterial strains belonging to both Gram-negative and Gram-positive (*Pseudomonas aeruginosa* ATCC 7853, *Proteus mirabilis* ATCC 29906, *Escherichia coli* ATCC 25922, *Staphylococcus aureus* ATCC 25923, *Streptococcus pneumoniae* ATCC 49619, and *Micrococcus luteus* ATCC 9341). Additionally, the extract’s anticandidal properties have been evaluated against the pathogenic yeast Candida albicans ATCC 20231. The extract’s antifungal activity was evaluated using three different phytopathogenic fungi (Rhizoctonia solani, Fusarium oxysporum, and Fusarium solani). The tested fungus was maintained on PDA medium at 25 °C for 3–5 days. ## 2.4.2. Agar–Diffusion Technique According to Hamad et al. [ 19], the antibacterial and anticandidal activities of the crude extract were evaluated as follows: 100 μL of the previously cultured bacterial and Candida albicans suspensions, each containing 1 × 108 CFU/mL (OD600~0.1) were distributed onto the surfaces of nutrient agar and PDA media, respectively. A 6-mm sterile cork borer was used to produce wells in the agar plates. By using an independent sterile micropipette, 100 µL of the non-polar mycelium extract at a concentration of 20 mg/mL was placed into each well. Then, the plates were kept in the refrigerator at 4 °C for 8 h, followed by incubation at 37 °C for 24 h. Both antibacterial (gentamycin at 10 g/disc) and antifungal (amphotericin B at 100 units/disc) drugs, as well as ethyl acetate were utilized as positive and negative controls, respectively. A ruler was used to measure the diameter of the inhibition zones formed around the wells to determine the antimicrobial efficacy. ## 2.4.3. Screening of Antifungal Effect The antifungal activity was determined based on the inhibitory percentage effect on radial mycelial growth (PIMG) of the fungi under investigation, according to Naglah et al. [ 20], as follows: At first, before pouring the plates, the ethyl acetate extract at a concentration of 20 mg/mL was added to the cooled potato dextrose agar medium (PDA). Then, the media was poured into the plates and left to solidify, and the centers of the plates were then inoculated with fungus discs measuring 5 mm in diameter. A negative control was created by inoculating sterile PDA medium with agar plugs of the same diameter from the investigated fungi. At 25 °C, all cultures were grown for 7 days. Radius of mycelium growth on PDA medium supplemented with mycelium crude extract (R2) was compared to that of mycelium growth on PDA medium (R1) to determine the efficacy of the antifungal properties of the extract. The PIMG was calculated by the formula below:PIMG = {(R1 − R2)/R1} × 100. ## 2.5. Antioxidant Activity Numerous procedures were employed in order to evaluate the extract’s antioxidant capacity. ## 2.5.1. Measurement of Free Radical Scavenging Activity The 2, 2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) free radical test was performed as follows by Boly et al. [ 21]: 100 µL of newly made DPPH reagent was combined with 100 µL of different concentrations of the fungal extract (800, 600, 400, 200, and 100 µg/mL in ethanol); for each concentration, six replicates have been performed. For 30 min, the experiment was conducted at room temperature in the dark. At 540 nm, we observed a decrease in DPPH color intensity. As a positive standard, trolox was dissolved in methanol and prepared at 50, 40, 30, 20, 15, 10, and 5 μM concentrations. According to the following formula, data has been measured as means ± SD:% of inhibition=Average absorbance of blank−average absorbance of the sampleAverage absorbance of blank×100 *The data* was recorded using a FluoStar Omega microplate reader. Microsoft Excel® was utilized in the process of data analysis. Half-maximal inhibitory concentration (IC50) was calculated using GraphPad Prism 6® by first logarithmizing the concentrations and then selecting the non-linear inhibitor regression equation (log (inhibitor) vs. normalized response—variable slope equation). ## 2.5.2. Ferric Reducing Antioxidant Power (FRAP) Assay With slight adjustments, the FRAP assay was performed in accordance with [22]. The 2,4,6-Tris(2-pyridyl)-s-triazine (TPTZ) reagent was initially freshly prepared using the following ingredients: (300 mM acetate buffer (PH = 3.6), 10 mM TPTZ in 40 mM HCl, and 20 mM FeCl3, in a ratio of 10:1:1 v/v/v, respectively). Then, the reaction was performed in 96 wells plate by mixing 190 µL of the reagent with 10 µL of the sample (at a concentration of 2 mg/mL in methanol), and the reaction was kept at room temperature for 30 min in the dark. The obtained blue color was measured at 593 nm. The data are shown as means ± SD. A 1 mM stock solution of trolox in methanol was used as a positive control. Next, seven serial dilutions were made, decreasing the initial concentration from 800 µM to 600 µM, then 400 µM, 200 µM, 100 µM, and finally 25 µM. ## 2.5.3. Metal Ion Chelating Activity The metal ion chelating test of the fungal non-polar extract has been performed in accordance with the procedure described by [23], with a few minor adjustments made. Briefly, 20 µL of the freshly made ferrous sulphate (0.3 mM) was combined with 50 µL of the fungal extract (1 mg/mL in methanol) in a 96-well plate (with six replicates). Following that, 30 µL of ferrozine at a concentration of 0.8 mM was supplemented to each well. The reaction mixture was ready to measure the change in color intensity at a wavelength of 562 nm after 10 min of room temperature incubation. Using a stock solution of 0.1 mM EDTA in water, five serial dilutions were carried out, resulting in final concentrations of 5, 10, 20, 30, 40, and 50 µM. According to the following equation, data are shown as means ± SD:% of inhibition=Average absorbance of blank−average absorbance of the sampleAverage absorbance of blank×100 ## 2.6. Acetylcholine Esterase Inhibitory Effect The acetylcholine esterase (AChE) inhibitory effect was performed with only a few adjustments to the method described by [24] as the following steps: Following the addition of 10 μL of an indicator solution containing 0.4 mM in buffer [1]: 100 mM tris buffer pH = 7.5, 20 μL of an enzyme solution containing acetylcholine esterase enzyme (Sigma Aldrich, Inc. St. Louis, MO, USA), 0.02 U/mL in buffer [2]: 50 mM tris buffer pH = 7.5 with $0.1\%$ bovine serum albumin were added. The sample solution was then mixed with 140 µL of buffer [1], yielding final concentrations of 0.1 mg/mL and 0.01 mg/mL, respectively. The mixture was allowed to incubate for fifteen minutes at room temperature. After that, 10 μL of the substrate (0.4 mM acetylcholine iodide in buffer 1) was immediately added. The mixture was kept at room temperature in darkness for a period of 20 min. Once incubation was complete, the color was measured at 412 nm. The sample attained an inhibition percentage greater than fifty percent, was subjected to additional testing to establish an IC50 value and was prepared with the following final concentrations: 100, 50, 25, 10, and 5 μg/mL. Donepezil was used as a positive standard in methanol at concentrations ranging from 1.0 to 7.0 μg/mL. The data are shown with a mean and a standard deviation. ## 2.7.1. Determination of Total Phenolics and Flavinoids The quantity of phenolic metabolites in the ethyl acetate extract of the fungus was determined by using Folin reagent Ciocalteu’s method, described by [25]. Briefly, a mixture of 2.5 mL of Ciocalteu’s Folin reagent, 2 mL of Na2CO3 ($7.5\%$), and 0.5 mL of fungal extract was prepared and incubated at 25 °C for fifteen minutes. The sample’s absorbance was measured at 765 nm. The total phenolic content was evaluated in terms of milligrams of gallic acid equivalent (GAE) per gram of dry extract using the gallic acid standard curve. Total flavonoid amount was determined using a method described in [26]. Briefly, 0.1 mL of a $10\%$ aluminum chloride solution and 0.1 mL solution of 1 M potassium hydroxide were added to 2 mL of methanol that contained 0.1 mg/mL of a fungal extract. The absorbance of the mixture was measured at 415 nm after it had been incubated at 25 °C for 30 min. Quercetin equivalents (QE) were used to quantify the flavonoids found; the results were calculated in milligrams of quercetin per gram of dry extract. ## 2.7.2. Gas chromatography–Mass Spectrometry (GC–MS) Analysis A TRACE GC Ultra Gas Chromatograph (Thermal Scientific Corp., USA) was employed for GC–MS analysis. It was connected to an ISQ Single Quadrupole Mass Spectrometer and a TR-5 MS column (30 m × 0.32 mm i.d., 0.25 m film thick-ness). Helium was used as the carrier gas with a flow rate of 1.0 mL/min and a split ratio of 1:10. The temperature was set to 60 °C for 1 min, then to 240 °C at a rate of 4.0 °C/min per minute for 1 min. The injector and the detector were held at 210 °C. In the injection, 1 µL of the mixtures were diluted (1:10 hexane, v/v). Mass spectra with m/z ranges of 40–450 were determined using electron ionization (EI) at 70 eV. Metabolites were identified using AMDIS software (www.amdis.net, accessed on 20 December 2022), which relied on retention indices (relative to n-alkanes C8-C22), mass spectra corresponding to authentic standards (when available), the Wiley spectral library collection, and the NSIT library database (accessed on 20 December 2022). ## 2.8.1. Small Molecule Preparation The 3D-structures of compounds were optimized using the PM3 (RHF spin state) semi-empirical Hamiltonian molecular orbital computation MO-PAC16 software, which was used in the MOE.2015 package [27]. ## 2.8.2. Protein Structure Selection In order to fix the active site problems brought on by the structure preparation procedure in MOE, docking experiments were performed using MOE 2015. After the adjustment, hydrogens were added, and the partial charges (Amber12: EHT) were estimated. The energy was minimized (AMBER12: EHT, root-mean-square gradient: 0.100) for targeting proteins including: DNA Gyrase (PDB; 6M1J), glutathione S-transferase (13GS), and Acetylcholinesterase (PDB ID: 1ACJ). ## 2.8.3. Analysis of Binding Sites The binding site for the receptor was found using the MOE Site Finder program, which uses a geometric technique to determine potential binding sites in a protein based on its tridimensional structure. Instead of using energy models, this method makes use of alpha spheres, a generalization of convex hulls. The predictions of the MOE Site Finder module were in agreement with the binding sites defined by the co-crystallized ligands in the holo forms of the proteins under investigation. ## 2.8.4. The Stepwise Docking Method of MOE The enzymes’ crystal structure was determined. They applied an MMFF94x force field to the parameters and charges. The triangular matcher placement method, which generates poses by aligning ligand triplets of atoms on triplets of alpha spheres represented in the receptor site points, was applied to the optimized 3D structure of the molecule. During each iteration, a random triplet of alpha sphere center was used to determine the pose. The position created was once more assessed using the London dG. approach. Using the MMFF94x force field, the poses were improved, and solvation effects were taken into account. The Born solvation model (GB/VI) was used to calculate the final energy, and the free energy in Kcal/mol was used to assign a grade to each final position. ## 2.8.5. ADMET Profile Swiss ADME (http://www.swissadme.ch/, accessed on 6 January 2023) provided the ADMET (absorption, distribution, metabolism, elimination, and toxicity) profile for compounds. The Lipinski rule of five (Molecular weight, logarithms of partial coefficient, hydrogen bond donor (HBD), and hydrogen bond acceptor (HBA)) was used to first screen the profiled compounds for their physicochemical properties to find the Pharmaceutical Active Ingredients (PAIs). From PubChem (https://pub-chem.ncbi.nlm.nih.gov, accessed on 6 January 2023), the canonical SMILES for the molecular structures of each of the metabolites were retrieved. Pharmacokinetic properties were further selected out of the compounds with desirable physicochemical characteristics. ## 2.9. Statistical Analysis Every test was conducted three times, with each run including three independent replicates. The data were subjected to analysis of variance (ANOVA), and group averages were compared using Fisher’s exact test (p ≤ 0.05). The software Minitab® was utilized to carry out the statistical analysis. ## 3.1. Morphological Macroscopic and Microscopic Characters of the Isolated Fungus After seven days of colony development at 25 °C on PDA (potato dextrose agar) medium, colonies were 30–45 mm in diameter, had heavy sporulation, were mostly deep green in the middle and surrounded by a white border with an irregular edge, and the back was mostly a pale yellowish color and clear exudate droplets were observed (Figure 1A,B). A branched conidiophore with chains of conidia was observed under a light microscope (Figure 1C). ## 3.2. Halotolerance Test Based on its salt tolerance levels, P. chrysogenum MZ945518 was classified as halotolerant or halophilic using the salt tolerance index (Ti). P. chrysogenum was grown on PDA and PDA supplemented with 2.5, 5, 10, 20, 25 and $30\%$ NaCl plates. Ti value was 1.3 at NaCL $5\%$, which indicated the studied fungus was halotolerant. The fungal growth on the PDA plates with $2.5\%$ NaCl after two, four, and six days of incubation were similar to the fungal growth of the control plates (Figure 2). Growth diameter was reduced by 5 and $10\%$ NaCl and completely inhibited by higher concentrations. ## 3.3. Antimicrobial Activity P. chrysogenum MZ945518 ethyl acetate extract was studied for its antimicrobial effect against six bacterial reference strains, including Gram-negative and Gram-positive bacteria, as well as one yeast strain. The diameter of the fungal extract’s inhibitory zone (mm) against the tested bacteria and yeast was compared to that of the commercial antibiotics, gentamycin and amphotericin B, as shown in Table 1. The fungal extract presented significantly higher activity against the two bacterial strains, *Micrococcus luteus* ATCC 9341 and *Proteus mirabilis* ATCC 29,906, by producing zones with diameters of 20 and 12 mm, respectively, compared with the antibiotic gentamycin. Moreover, the extract killed *Streptococcus pneumoniae* ATCC49619 in a way that was almost the same as gentamycin. Additionally, the extract demonstrated efficacy against the remaining investigated bacteria and the yeast; however, its effects were moderate or negligible in comparison to those of gentamycin and amphotericin B. For fungi, PIMG was evaluated to test the antifungal activity of ethyl acetate extract versus three plant pathogenic fungal species, and the results showed that the mycelial growth of Fusarium solani was the most affected by the P. chrysogenum MZ945518 extract with an inhibitory percentage of 77.5 ± 0.3. ( Table 2). ## 3.4. Antioxidant Activity The antioxidant capacity of the ethyl acetate extract of the studied fungus was measured with the DPPH-free radical scavenging method, the ferric reducing antioxidant power (FRAP) assay, and metal ion chelating activity. The findings of DPPH scavenger activity on fungal ethyl acetate extracts revealed that the IC50 value against DPPH radicals was 542.5 ± 69.1 μg/mL (Table 3). Moreover, the results of the FRAP test demonstrated that the fungal extract was converted from Fe3+ to Fe2+, although the values were less impressive than those obtained with the Trolox compound. Moreover, the results of the metal ion chelating activity revealed that the extract had a lower chelating ability when compared to conventional EDTA solutions with 12.7 ± 0.9 μM EDTA eq/mg extract. ## 3.5. Acetylcholine Esterase Inhibitory Effect The effectiveness of the fungus extract in inhibiting the acetylcholinesterase enzyme (AChE) exhibited a clear suppression of enzyme activity ($63\%$ inhibition percentage) and a recorded IC50 value of 60.87 3.8 µg/mL (Table 4). ## 3.6.1. Total Phenolics and Flavonoids Using the Folin–Ciocalteau and aluminum chloride techniques, respectively, the total phenolic and flavonoid content in the ethyl acetate extract of the P. chrysogenum MZ945518 was determined. Flavonoids and phenolics were present in totals of 133.4 and 373.5 mg/g, respectively. ## 3.6.2. GC/MS Profiling The chemical profiling of the P. chrysogenum MZ945518 extract was performed using a GC/MS instrument (Figure 3). By matching the retention time and mass spectra to either authentic data standards or data from the Wiley spectral library and the NSIT library database, twenty metabolites were detected in the ethyl acetate extract (Table 5). With a ratio of $36.28\%$, (Z)-18-octadec-9-enolide was the most abundant metabolite, followed by 1, 2- Benzenedicarboxylic acid with a ratio of $26.73\%$. n- Hexadecanoic acid ($7.8\%$), 2, 3-dihydroxypropyl acetate ($5.3\%$), 9, 12-octadecadienoic acid (Z, Z)-, methyl ester ($4.8\%$), and butyl 9, 12, and 15-octadecatrienoate ($3.2\%$) were also major metabolites. ## 3.7. Molecular Docking Study To investigate the in silico antimicrobial inhibition action of isolated compounds from fungus ethyl acetate extract, the docking study was applied against DNA Gyrase proteins. The different docking energies were listed in (Table 6). The metabolites two, six and eight showed the highest binding energy in (Kcal/mol.), as they were −7.78, −7.33, and −7.76 against the DNA Gyrase (PDB; 6M1J; [28]). The isolated compounds 3–5, 7, and 9–20 showed moderate binding efficiency against 6M1J enzymes. All compounds stabilized in the active binding site (ASP75, ARG78 & ARG138) in a similar way to the reference inhibitor (Figure 4). Molecular docking was performed to examine which isolated compounds displayed antioxidant activity. Compounds two, eight, and sixteen exhibited the highest binding energy against 13GA (−6.19, −6.51, and −6.13 Kcal/mol, respectively). These compounds stabilized in the binding pocket by forming a strong H-bond with the essential amino acid Asp98 (Figure 4). All isolated compounds occupied the binding pocket (ASP98, GLN64, LEU52, ARG13, SER65, PRO53) with the same type of reference inhibitor. Furthermore, the molecular docking performed against Acetylcholinesterase’s active site, “AChE” (PDB ID: 1ACJ), post-docking results showed that all docked identified molecules revealed a binding efficacy ΔG in the range of −4.95 to −8.72 Kcal/mol. The isolated pa2, 3-dihydroxypropyl acetate [5] has the highest binding efficacy (ΔG = −8.72 kcal/mol) among all isolated components, while the glyceryl acetate [1] showed the lowest binding efficiency (−5.82 kcal/mol). The validity of the docking experiment was confirmed by the low RMSD value (0.86 to 1.92), as represented in Table 6. ## 3.8. ADMET Profile The pharmacological and pharmacokinetic features of the molecule must reach the action point in a timely manner, in an adequate concentration, and be able to be cleared from the body after their action 17. As a result, the in silico ADME properties of the compounds are crucial in drug discovery. Using the Swiss ADME profile, in silico ADME computational investigations were carried out. The hydrogen bond acceptor/donor (HBA/HBD), solubility, lipophilicity, topological surface area (TPSA), and percentage of absorption (%ABS) of all the drug-like properties have been identified. The %ABS was achieved by the following formula: %ABS = 109 – (0.345 × TPSA). Table 7 illustrates the data that were attained. Lipinski’s rule of five states that molecules with the following characteristics—hydrogen bond donors fewer than five and hydrogen bond acceptors fewer than ten—can have greater in vivo absorption and bioavailability. These criteria include molecular weight below 500 and estimated log P less than five. Substances that break more than one of the aforementioned rules may have bioavailability issues. According to the computational ADME results, all of the detected compounds showed Log P values between 3.20 and 4.05, which indicates good cell permeability. With the exception of compounds 18 and 19 (MW = 728 and 537), all of the compounds have molecular weights under 500, indicating simple delivery and absorption. ## 4. Discussion Microorganisms that can live and thrive in harsh environments are thought to be a bountiful origin of various naturally occurring bioactive and novel molecules. One of the challenging environmental factors that microorganisms must adapt to in order to thrive is high salt. Adaptation involves the overproduction of bioactive metabolites and, at times, the synthesis of novel biochemicals which can be utilized as new antioxidants and antimicrobial sources [29]. This study relied on P. chrysogenum MZ945518 isolated from the Mediterranean Sea in Egypt. The fungus was identified genetically in a previous study [17]. In our findings, additional morphological studies were conducted on the fungus, and the results revealed that in the front view it had heavy sporulation, was mostly deep green in the middle, and was surrounded by a white border with an irregular edge. In the back view, it was mostly a pale yellowish color, and clear exudate droplets were observed on PDA plates. Additionally, under a light microscope, it showed a branched conidiophore with chains of conidia. Previous studies [30] reported that on PDA media, *Penicillium chrysogenum* displayed modest development, with the colony’s backside being colored yellow and its core being green. Finding the halotolerance index of P. chrysogenum MZ945518, which was isolated from the Egyptian Mediterranean shore, was one of the goals of this study. The results of the test revealed that the growth pattern of the fungus and calculations of the medium tolerance index demonstrated that the fungus is thought to be permanently halophilic. Genus Penicillium compressed many members, which are classified as extremophiles [31]. Various strains of the fungus P. chrysogenum have reportedly been isolated and survive in excessively salty habitats [32,33]. *In* general, many Penicillium species produce various chemical types of secondary metabolites, some of which are significant in the field of medicine, others of which are used to produce mycotoxins, significant drugs, and some of which are used in industry, particularly in the production of penicillin [32,33]. Our findings involved studying the different activities (the antimicrobial, antioxidant, and acetylcholine esterase inhibitory effect) of the *Penicillium chrysogenum* MZ945518 crude extract. According to a report published by the World Health Organization in 2022, antimicrobial resistance is one of the top ten global public health concerns facing humanity (https://amrcountryprogress.org/#/visualization-view, accessed on 6 January 2023). Many antimicrobial drugs have lost their potency in recent years. This highlights the critical need for further research into novel antimicrobial sources and metabolites. The fungal non-polar extract showed antibacterial action against all of the pathogenic organisms that were tested, whereas, in comparison to the commercial antibiotic gentamycin, the activity was most powerful against *Micrococcus luteus* and Proteus mirabilis. Proteus mirabilis is considered a human pathogen which infects the urinary tract, especially in people who have long-term hospitalization [34,35]. Previous research [36] found that P. chrysogenum has the superior antibacterial activity against nine bacterial species, including Escherichia coli, Acinetobacter baumannii, and Staphylococcus aureus, when compared to *Aspergillus oryzae* and Aspergillus niger. Furthermore, the fungus inhibited *Pseudomonas aeruginosa* growth significantly [37]. Additionally, [38] reported that on cheap mediums, such as grape waste and cheese whey, the strain P. chrysogenum IFL1 developed active metabolites with antibacterial, antifungal, and amoebicidal properties. The metabolite xanthocillin isolated from P. chrysogenum demonstrated strong inhibitory activities against Klebsiella pneumoniae, Acinetobacter baumannii, and *Pseudomonas aeruginosa* [39]. Moreover, a compound called citrinin, which is made from the fungus *Penicillium chrysogenum* FF001 and originally found in the sponge Melophlus sp., is effective against drug-resistant strains of *Staphylococcus aureus* and *Enterococcus faecium* [40]. Our results suggest that the P. chrysogenum extract can be used to combat the human pathogen Candida albicans. Several human diseases, such as cancer and inflammatory disorders, have been related to C. albicans [41]. According to research that was published in [37], P. chrysogenum makes a protein that can stop C. albicans from growing. Al-Saleem et al. [ 42] showed that *Penicillium chrysogenum* extract was highly effective in killing both Candida albicans and Staphylococcus aureus. Halotolerance fungi are known to have a biologically active substance which possesses antimicrobial activities [29]. Antifungal activity of the fungal ethyl acetate extract showed that the fungal possesses antifungal bioactivity against Fusarium oxysporum, Rhizoctonia solani, and Fusarium solani. Both plants and animals are susceptible to infection by these pathogenic fungi. Fusarium oxysporum is one of the most harmful plant pathogens around; it can also infect humans and is increasingly being recognized as a major health threat because of its capacity to cause severe illness in those with impaired immune systems [43]. Rhizoctonia solani is a devastating fungus that attacks economically significant crops all around the world [44]. Fusarium solani causes rot in a wide variety of crops, including citrus, rice, peas, beans and potatos. Pathogenic fungi can be combated with biocontrol strategies rather than fungicide, which is less harmful to ecosystems [45,46,47]. The antifungal activity of the *Penicillium chrysogenum* protein has been stated by [48,49]. P. chrysogenum IFL1 metabolites could inhibit Fusarium spp. and other phytopathogenic fungi [12]. Biological control of *Fusarium oxysporum* using *Bacillus velezensis* [50] and Streptomyces sp. [ 51] has been reported. Streptomyces and *Bacillus spp* was found to be effective for biological control of Rhizoctonia solani [52,53]. In the current investigation, a non-polar extract from P. chrysogenum showed antioxidant activity based on the DPPH free radicals, FRAP test and metal ion chelating activity. Antioxidants play an important role in cell protection by blocking free radicals at their active site and trapping free radicals that cause degenerative processes [54,55]. Previous research has demonstrated that *Penicillium chrysogenum* has a strong antioxidant capacity [11,42]. The antioxidant activity of P. chrysogenum MZ945518 has an IC50 of 542.5 µg/mL in the DPPH test. According to results from DPPH in [56], the whole extract of P. chrysogenum has an antioxidant activity IC50 of 1086.2 µg/mL. The GC/MS analyzer was used to determine the fungus’s chemical profile, which resulted in the identification of twenty metabolites, the majority of which have biological functions. For example, metabolites biformen has anti-inflammatory activity [57]. Palmitic acid showed potent inhibitory activity against both Gram-positive and Gram-negative bacteria [58,59]. Methyl palmitate has a nematocidal effect, antifibrotic, and anti-inflammatory activities [60,61,62]. 9,12-Octadecadienoic acid (Z, Z)-, methyl ester has analgesic, anti-inflammatory, and ulcerogenic properties [63]. 11-Octadecenoic acid, methyl ester has antidiarrhoeal activity [64]. Methyl palmitate and methyl stearate have been shown to be nematicidal against Meloidogyne incognita, an insect pest of bananas [61]. 1,2- Benzenedicarboxylic acid has antimicrobial activity [65]. The fungal extract in this investigation was capable of inhibiting the acetylcholinesterase enzyme (AChE) at a rate of $63\%$. Our findings contradict the findings of [66], who reported that after testing fifteen compounds isolated from *Penicillium chrysogenum* for their ability to inhibit AChE, the results revealed that none of them had any effect on the enzyme’s activity. [ 67] reported that Penicillium sp. metabolites significantly decreased acetylcholinesterase activity in *Culex quinquefasciatus* and Aedes aegypti larvae, compared to Aspergillus sp. and Rhizopus sp. We obtained better results than [56], which said that *Penicillium janthinellum* extract only blocked AChE by $36.62\%$. Acetylcholine is considered one of the best-studied neurotransmitters and has been linked to Alzheimer’s disease pathogenesis (neurodegenerative disease and the leading cause for dementia), and its hydrolysis is catalyzed by AChE. From this vantage point, blocking the enzyme responsible for producing AChE has proven to be an efficient Alzheimer’s disease treatment [68,69]. Natural products have been shown to have anti-AD efficacy and AChE inhibition in a variety of preclinical and clinical studies [70]. Several sources, including [71], have reported that marine species play a role as a source of AChE inhibitor metabolites. A docking study revealed that the compositions of glycerol 1,2-diacetate, 2,3-bis (Acetyloxy)-1-[(acetyloxy)methyl] propylacetate, and palmitic acid are most commonly shared in antimicrobial activity via the inhibition of DNA gyrase and interaction with essential amino acid residues, such as Arg78, Glu79, and Thr167, for DNA gyrase. The assumption that the inhibitory efficiency for the studied compositions increased with increasing hydrophilicity resulted from the variance in the interaction mode between compositions and hydrophilic amino acid backbones. In addition, glycerol 1, 2-diacetate, palmitic acid, [1, 1’-Bicyclopropyl]-2-octanoic acid, 2’-hexyl, and methyl ester are among the most identified antioxidant substances. According to its crystallographic structure, the AChE (PDB [72] has two major binding sites: the catalytic active site (CAS) and the gorge-connected peripheral anionic site (PAS) [73]. The PAS is composed of (Tyr70, Asp72, Tyr121, Trp279, and Phe290), whereas the CAS is composed of (Ser200, Glu327, and His440), the anionic substrate (Trp84, Glu199, and Phe330), and the acyl binding pocket (Phe288 and Phe299) [72]. All substances interacted with the essential amino acid residue Trp84 at the binding site in the same way as the reference inhibitor. When applied to the AChE domain, the notable substances two, three, four, eight, ten, eleven, thirteen, and sixteen caused biological inhibition potency. These substances have the highest binding activities. According to the Swiss ADME’s (http://www.swissadme.ch/, accessed on 6 January 2023) ADMET results, all hybrids except for seven and eighteen and nineteen conform to the Lipinski requirements because the number of hydrogen bond acceptors and donors present in the hybrids was fewer than ten. Compounds 1–5, 7–17, and 19–20 should be easily absorbed by the human body, with the exception of compounds 6 and 18. All conjugates, with the exception of six and eighteen, had percentage absorption values more than $74\%$. These findings show that, with the exception of 7–18, compounds 3–12 have favorable pharmacokinetic characteristics and minimal toxicity. ## 5. Conclusions Mycelium extract from the halotolerant *Penicillium chrysogenum* strain MZ945518 was antimicrobial potent. 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--- title: 'Green Tea Consumption and the COVID-19 Omicron Pandemic Era: Pharmacology and Epidemiology' authors: - Maksim Storozhuk - Siyun Lee - Jin I. Lee - Junsoo Park journal: Life year: 2023 pmcid: PMC10054848 doi: 10.3390/life13030852 license: CC BY 4.0 --- # Green Tea Consumption and the COVID-19 Omicron Pandemic Era: Pharmacology and Epidemiology ## Abstract In spite of the development of numerous vaccines for the prevention of COVID-19 and the approval of several drugs for its treatment, there is still a great need for effective and inexpensive therapies against this disease. Previously, we showed that green tea and tea catechins interfere with coronavirus replication as well as coronavirus 3CL protease activity, and also showed lower COVID-19 morbidity and mortality in countries with higher green tea consumption. However, it is not clear whether green tea is still effective against the newer SARS-CoV-2 variants including omicron. It is also not known whether higher green tea consumption continues to contribute to lower COVID-19 morbidity and mortality now that vaccination rates in many countries are high. Here, we attempted to update the information regarding green tea in relation to COVID-19. Using pharmacological and ecological approaches, we found that EGCG as well as green tea inhibit the activity of the omicron variant 3CL protease efficiently, and there continues to be pronounced differences in COVID-19 morbidity and mortality between groups of countries with high and low green tea consumption as of December 6, 2022. These results collectively suggest that green tea continues to be effective against COVID-19 despite the new omicron variants and increased vaccination. ## 1. Introduction The coronavirus pandemic caused by the SARS-CoV-2 virus led to hundreds of millions of infections and millions of deaths within the first year and is the deadliest pandemic of the 21st century [1,2]. At that time, without any vaccine available, many groups sought to identify effective and inexpensive therapies against COVID-19 [3,4,5,6,7,8,9]. Among these, there was mounting evidence suggesting the therapeutic potential of green tea catechins in the prevention/treatment of COVID-19. We and other groups identified green tea extract and the active ingredients of green tea, EGCG and theaflavin, as inhibitors of the SARS-CoV-2 3CL protease necessary for viral reproduction [10,11,12,13,14]. Furthermore, EGCG or green tea extract treatment reduced infection of SARS-CoV-2 as well as other human beta coronaviruses in human and primate cells [14,15,16,17,18], and reduced the viral load in the lung tissue of mice [17]. With a plethora of evidence that green tea extracts can counteract SARS-CoV-2 infection, the use of green tea as a therapy against COVID-19 is a distinct possibility. Still, it appears that there are only a few epidemiological studies assessing the therapeutic potential of green tea catechins: (i) an observational study reporting that people who consumed ≥4 cups/day of green tea had a lower, albeit statistically not significant, odds of SARS-CoV-2 infection [19]; and (ii) ecological studies reporting lower COVID-19 morbidity and mortality in countries with higher per capita green tea consumption [20,21]. However, the abovementioned ecological studies reflect the epidemiological situation globally before January 2021 [21]. Since then, two major changes in the coronavirus pandemic have occurred, namely a global mass vaccination campaign and the appearance of omicron SARS-CoV-2 variants [22,23]. How these two changes may alter the reported morbidity and mortality rates in countries with high green tea consumption is unknown, and whether green tea extract or EGCG is still effective in inhibiting SARS-CoV-2 omicron variants has yet to be tested. A recent work, however, reports that EGCG from green tea effectively blocks infection of SARS-CoV-2 and variants of the virus [15]. The latter is in line with the observation that the neutralizing activity of concentrated green tea extract is independent of the strain of SARS-CoV-2 [24]. These studies point to the possibility that green tea extracts and EGCG may be just as effective in inhibiting SARS-CoV-2 omicron 3CL protease activity. The omicron variants contain one amino acid change (P132H) in the 3CL protease sequence, and Paxlovid, a coronavirus drug, is reported to also inhibit the 3CL protease variant (P132H) [25]. In this report, we sought to update the effect of green tea and green tea catechins upon SARS-CoV-2 and COVID-19. We used a two-prong approach utilizing both biochemical and epidemiological approaches. *We* generated the SARS-CoV-2 omicron 3CL protease (P132H) and examined whether green tea extract or EGCG are effective in inhibiting the activity of the omicron variant 3CL protease. We also asked whether we could still observe lower COVID-19 morbidity and mortality in countries with higher per capita green tea consumption in spite of growing vaccination rates and the appearance of new omicron variants of SARS-CoV-2. ## 2.1. Generation of SARS-CoV-2 3CL Protease Mutant (P132H) The plasmid encoding His-tagged 3CL protease was described previously [11] and the point mutation of the 3CL protease (P132H) was generated using a Quickchange PCR mutagenesis with the enzyme nPFU forte (Enzynomics, Daejeon, Republic of Korea) using forward primer 5′-CCAATGTGCTATGAGGCACAATTTCACTATTAAGGG-3’ and reverse primer 5’-CCCTTAATAGTGAAATTGTGCCTCATAGCACATTGG-3’. The new plasmid containing the 3CL protease (P132H) was completely sequenced to verify the presence of the intended mutation only. His-tagged 3CL protease protein was prepared and purified as described previously [11]. The 3D structure of 3CL protease was generated using Pymol software (DeLano Scientific, Palo Alto, CA, USA). ## 2.2. Protease Assay for 3CL Protease Assay A FRET-based protease assay was used to examine the protease activity of 3CL protease [26]. Briefly, Dabcyl-KTSAVLQSGFRKME-Edans was chemically synthesized (Anygen, Gwangju, Republic of Korea) and used for the SARS-CoV-2 3CL protease substrate. The 3CL protease activity was performed at 37 °C using 3CL protein and FRET peptide in the reaction buffer (20 mM Tris-HCl (pH 7.5), 200 mM NaCl, 5 mM EDTA, 5 mM DTT, and $1\%$ DMSO) for 3 h. For the inhibition assay, the purified 3CL protease was incubated with EGCG for 1 h before the addition of substrate. The fluorescence was measured at 528 nm with excitation at 360 nm using a Synergy HTX multimode microplate reader (Biotek, Winooski, VT, USA). ( −)-Epigallocatechin gallate (EGCG) (E4134, purity ≥ $95\%$) was purchased from Sigma-Aldrich (Saint Louis, MO, USA) and the green tea extract powder was provided by the AMOREPACIFIC R&I Center (Gyeonggi-do, Republic of Korea). Green tea extract contains epigallocatechin gallate (EGCG, 18.7 ± $1.2\%$), epigallocatechin (EGC, 11.2 ± $1.4\%$), epicatechin gallate (ECG, 3.8 ± $0.6\%$) and epicatechin (EC, 3.7 ± $0.6\%$) as active catechins (total catechin 37.4 ± $1.2\%$). To draw the inhibition curve, AAT Bioquest website program was used (https://www.aatbio.com/tools/ic50-calculator accessed on 1 December 2022). ## 2.3. Data Analysis Regarding COVID-19 Morbidity and Mortality All data were obtained from open sources. Specifically, information about COVID-19 morbidity and mortality for a particular date was obtained from ‘Worldometers info. Coronavirus’. The information on ‘Worldometer’ is based on official daily reports and considered as a reliable source [27,28]. The methodological approach used in this report is similar to that described previously [21,29]. Nevertheless, some description of this approach is provided below with more details, and specific details of the current work are provided in Supplementary Materials. Briefly, information about COVID-19 morbidity (defined as total number of cases per million population) and mortality (defined as a total number of deaths per million population) for a specific date was directly obtained from ‘Worldometers info. Coronavirus’ (https://www.worldometers.info/coronavirus/ accessed on 6 December 2022). Analysis was restricted to 134 countries or territories (according to UN classification) with at least a population of 3 million. Twenty-one of these countries/territories, with estimated per capita green tea consumption above 150 g annually, were considered as a group with high consumption. Countries/territories with estimated per capita green tea consumption below 150 g were considered as a group with low consumption (see [21,29]. for details). Considering that COVID-19 morbidity and COVID-19 mortality do not follow a normal distribution (Urashima et al., 2020), a non-parametric statistic (Wilcoxon (Mann–Whitney U Test) for Unpaired Data) was used for comparisons. In multiple linear regression analysis, the following factors as well as green tea consumption were included: population density, percentage of population aged above 65, percentage of urban population and Human Developmental Index (HDI). In a complementary analysis, an additional variable, namely vaccination rates, was added to the model. ‘ KyPlot’ software was employed for statistical assessments. ## 3.1. EGCG and Green Tea Extract Can Inhibit SARS-CoV-2 3CL Protease (P132H) We previously showed using an in vitro assay that both EGCG and green tea extract can inhibit the 3CL protease activity of SARS-CoV-2 [10,11]. Since then, the SARS-CoV-2 omicron variants have replaced SARS-CoV-2 and become the dominant strains circulating globally causing the COVID-19 pandemic to extend into a third year in 2022. The SARS-CoV-2 omicron 3CL protease has been reported to contain one amino acid substitution (P132H) in its polypeptide sequence (Figure 1A). Although the location of the mutated sequence is quite distant from the substrate binding site (Figure 1B), whether such a mutation may alter 3CL protease activity and the ability of EGCG or green tea extracts to suppress protease activity is unknown. To test whether EGCG or green tea extract can inhibit the protease activity of the 3CL protease variant (P132H), we produced SARS-CoV-2 3CL protease protein (P132H) and tested the enzyme activity using our in vitro assay. The purified 3CL protease protein (P132H) showed comparable activity to the original 3CL protease protein at all concentrations tested (Figure 2A,B), indicating that the mutation does not affect protease function. Next, we examined whether EGCG can inhibit protease activity by SARS-CoV-2 3 CL protease protein (P132H). EGCG treatment inhibits both original 3CL protease and 3CL protease (P132H) in a dose-dependent manner (Figure 2C). We also examined the inhibitory activity using green tea extract and showed that green tea extract treatment also effectively inhibits the protease activity of 3CL protease (P132H) in a dose-dependent manner similar to EGCG. ( Figure 2D). Thus, SARS-CoV-2 3CL protease activity is conserved in SARS-CoV-2 omicron, and the ability of EGCG and green tea extracts to inhibit 3CL protease activity is not altered in SARS-CoV-2 omicron. ## 3.2. Higher Per Capita Green Tea Consumption Is Associated with Lower COVID-19 Morbidity and Mortality as of 6 December 2022 Consistent with the fact that green tea can inhibit SARS-CoV-2 3CL protease activity and decrease viral infectivity [10,11,14,15,18], we previously reported differences in COVID-19 morbidity and mortality between groups of countries/territories with higher and lower per capita green tea consumption [20,21]. The abovementioned results reflect the cumulative epidemiological situation in January 2021 or before, prior to the beginning of the mass vaccination campaign and appearance of the omicron SARS-CoV-2 variant. In light of our above findings that green tea extracts and EGCG can inhibit SARS-CoV-2 omicron 3CL protease activity (Figure 2), we asked whether these epidemiological differences remained in this current stage of the global pandemic. Here, we mostly focused on the question of whether similar differences are still observed in spite of growing vaccination rates and the appearance of new variants of SARS-CoV-2. Therefore, using a similar approach, we primarily analyzed a recent 12-month period (6 December 2021–6 December 2022) separately (see Supplementary Materials for details). We found pronounced and statistically significant differences in COVID-19 mortality between groups of countries/territories with higher and lower green tea consumption (Table 1). The difference in COVID-19 mortality between the groups was still statistically significant in a subset of countries with a human development index (HDI) above 0.55 (Table S1). Moreover, in this restricted subset of countries, weak but statistically significant correlations between COVID-19 morbidity (or mortality) and per capita green tea consumption were observed using a multiple regression model accounting for several factors that have been reported previously as important confounders (population density, percentage of population aged above 65, percentage of urban population, HDI) [30] as well as vaccination rates [31]. These results are summarized in the Table S2 (a and b). In addition, using a similar approach, we analyzed the cumulative COVID-19 morbidity and mortality for the entire COVID-19 pandemic period as of December 6, 2022. We obtained qualitatively similar results in this analysis (Tables S3–S5). Overall, both our biochemical studies using the SARS-CoV-2 omicron and epidemiological studies in the current stage of the global COVID-19 pandemic indicate that green tea remains a potential therapy against SARS-CoV-2 infection and COVID-19 disease. ## 4. Discussion Since late 2019 when SARS-CoV-2 was first reported in China, many variants of the virus have appeared. Because many of the mutations of these variants occur at spike protein sequences [32], and these variants could potentially evade the human immune system [33], the SARS-CoV-2 3CL protease became a target of coronavirus drugs including Paxlovid [34]. Unlike the spike protein, the 3CL protease does not contain many mutations among the SARS-CoV-2 variants. The reason for this is likely because conservation of the protease’s important enzymatic function is necessary for the replication and success of the virus [35]. However, the SARS-CoV-2 omicron clade obtained a single amino acid mutation in the 3CL protease [25], although the location of this mutation is distant from the substrate binding site (Figure 1). Since green tea extracts and catechins showed inhibitory activity against 3CL protease [10,11,12,13,14], we decided to examine whether green tea extract and EGCG are also effective against the SARS-CoV-2 3CL protease mutant (P132H). We first showed that SARS-CoV-2 3CL protease mutant (P132H) activity is comparable to 3CL protease mutant; thus, the protease has retained its enzymatic function in the omicron strains. We also showed that EGCG and green tea extract is effective at inhibiting both 3CL proteases. Therefore, these results support that green tea or tea catechins are potentially effective against SARS-CoV-2 omicron variants. Since green tea and green tea catechins are known to inhibit SARS-CoV-2 infection, similar experiments can confirm whether they can also inhibit SARS-CoV-2 omicron infection. Our in vitro experiments show that green tea catechins specifically inhibit 3CL protease enzyme function. Additionally, green tea has many positive effects on human health that can also contribute to fighting COVID-19. Green tea constituents are beneficial in relation to factors associated with higher COVID-19 mortality such as cholesterol levels [36], obesity [37,38], diabetes [39], uncontrolled immune activation [40], and cardiovascular disease [41]. Finally, green tea catechins can potentiate adaptive immunity [16] and can act as ionophores for zinc ions, the latter being considered as potentially beneficial in relation to COVID-19 [42]. Pronounced differences in COVID-19 morbidity and mortality between groups of countries/territories with higher and lower green tea consumption were found as of 6 December 2022 (Table S3). These results extend previous observations, reflecting the epidemiological situation in January 2021 [29] and before (September and November 2020) [20,21,29]. This consistency over a prolonged period may be an additional though indirect argument supporting the therapeutic potential of green tea catechins in the amelioration or treatment of COVID-19. These results are in line with the rapidly growing evidence obtained from other studies in a recent review [43]. Additionally, the selective analysis of the epidemiological situation during the most recent one-year period suggests that green tea catechins may be effective even with growing vaccination rates and against new variants of SARS-CoV-2 including omicron. This is consistent with our pharmacological evidence obtained in the current study (Figure 2). Although ecological studies, taken alone, could not confirm a causal relation, these studies are still considered as useful and widely used in the field [27,30]. Limitations and potential concerns relevant to our current ecological results have been discussed in more detail previously [21,29], and briefly outlined below. Indeed, there are many factors that can differentially affect COVID-19 morbidity and mortality in distinct countries (e.g., the percentage of older population; administrative strategies to prevent transmission; condition-specific mortality risks; HDI). On the other hand, since numerous countries from all over the world were considered, it does not seem likely that these factors can systematically or strongly bias the results presented here. Furthermore, confounding factors reported as the most strong and consistent (HDI, percentage of older population) as well as other factors were included in our linear regression model. In this study, in addition to these factors, we address the potential concern of how differences in vaccination rates may bias our current results. Nonetheless, statistically significant correlations between COVID-19 morbidity and mortality and per capita green tea consumption were still observed in a linear regression model that included vaccination rates (Table S5). A separate though related question is whether the efficacy of green tea catechins in lowering COVID-19 morbidity and mortality remains consistent when vaccination rates in a population are increased. A direct answer to this question cannot be obtained using our ecological approach alone. However, a preliminary clue can be derived from our data: since the strength of correlations we consider here seems to be weaker during the recent 1-year period (Table S2) compared to cumulative data since the beginning of the epidemic (Table S5), a decrease in efficacy cannot necessarily be excluded. Given that this is the case rather than due to the appearance of new variants of SARS-CoV-2, one possibility is that green tea catechins can provide a non-additive action on the immune system consistent with their role in potentiating adaptive immunity [16]. Taken together, if the efficacy of green tea or green tea catechins (e.g., EGCG) can be confirmed in observational studies and clinical trials in combination with the results shown in this study, green tea or green tea catechins can be used as an inexpensive method to prevent or relieve COVID-19 diseases. ## References 1. Wu D., Wu T., Liu Q., Yang Z.. **The SARS-CoV-2 outbreak: What we know**. *Int. J. Infect. 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--- title: 'CochleRob: Parallel-Serial Robot to Position a Magnetic Actuator around a Patient’s Head for Intracochlear Microrobot Navigation' authors: - Housseyne Nadour - Alexis Bozorg Grayeli - Gérard Poisson - Karim Belharet journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10054852 doi: 10.3390/s23062973 license: CC BY 4.0 --- # CochleRob: Parallel-Serial Robot to Position a Magnetic Actuator around a Patient’s Head for Intracochlear Microrobot Navigation ## Abstract Our work introduces a new robotic solution named CochleRob, which is used for the administration of super-paramagnetic antiparticles as drug carriers into the human cochlea for the treatment of hearing loss caused by damaged cochlea. This novel robot architecture presents two key contributions. First, CochleRob has been designed to meet specifications pertaining to ear anatomy, including workspace, degrees of freedom, compactness, rigidity, and accuracy. The first objective was to develop a safer mathod to administer drugs to the cochlea without the need for catheter or CI insertion. Secondly, we aimed at developing and validating the mathemathical models, including forward, inverse, and dynamic models, to support the robot function. Our work provides a promising solution for drug administration into the inner ear. ## 1. Introduction The treatment of hearing loss due to inner ear damage has been a rapidly growing area of research and clinical trials in recent decades [1]. Many approaches have been proposed to treat different cochlear pathologies. Several robotic manipulators have been designed, and some of them have even been developed and tested in clinical studies [2,3,4,5,6]. The evolution of treatment approaches for cochlear pathologies has undergone two significant stages, moving from systemic administration to local administration. Based on the available information, researchers have proposed three methods of local administration: [1] transtympanic in situ drug administration method, which has limitations; [2] the catheter or CI implementation based method, which carries risk; and [3] the remote administration method, which is considered safe but requires a specialized robotic structure. With this paper, we aim to address this gap. The shift from systemic to local administration in cochlear drug delivery is due to several limitations, such as the blood–cochlear barrier preventing drug diffusion [7,8] and the requirement for high doses of oral or intravenous drugs [9], leading to limited candidate drugs and treatment duration. Additionally, the requirement for long-term treatment and the presence of significant adverse side effects further discourage the use of systemic administration [10,11]. The transtympanic in situ drug administration method consists of injecting the drug into the middle ear cleft via the tympanic membrane under local anesthesia, delivering it to the cochlea through the round window membrane [12]. However, the amount delivered is poorly controlled by this method [13] and diffusion beyond the basal turn of the cochlea is limited due to negligible perilymphatic flux [14]. The CI surgery combined to residual hearing preservation has been successful [5,15,16,17]; however, there is a risk of damaging the cochlea’s internal structures during insertion of the electrode array [18]. This damage can occur from translocation of the array and friction on the cochlear lateral wall, and tip-folding of the array can cause trauma and device malfunction [19]. Efforts to reduce trauma through methods such as magnetic guidance have been attempted [20,21,22,23], but the placement of an array inside the cochlea is not considered a safe option for patients with inner ear diseases who do not require CI for hearing rehabilitation [14]. Developing robotic platforms specified for CI-based drug delivery is still a point of interest [24,25,26]. For more details about cochlear implants, the reader can refer to [27,28]. Our strategy, the remote administration method, consists of using therapeutic SPMNP (SuperParamagnetic NanoParticles) for drug delivery inside the cochlea [29]. This strategy does not require the insertion of any catheter or CI inside the cochlea, but only the particles, which considerably limits any casual damage to the cochlea. The particles will be controlled remotely to the cochlea using magnetic forces generated by our proposed magnetic actuator [30], positioned around the patient’s head. As a further development, we propose a novel manipulator robot to position the magnetic actuator around the patient’s head in this paper. To outlines the plan of this article is as follows: The magnetic actuator’s operating principle and specifications are presented in Section 2. The design of the robotic system is described in Section 3. The forward and inverse kinematics models of the robot are explained in Section 4 and Section 5. The dynamic and space models are presented in Section 6 and Section 7. The joint control architecture is described in Section 8. The CochleRob manipulator prototype and experimental validation are detailed in Section 9. Conclusions and perspectives are provided in Section 10. ## 2.1. Anatomical Specifications The ear is composed of three parts: external ear, middle ear, and inner ear. The inner ear contains both the organ of hearing (cochlea) and the organ of balance (vestibular system). The cochlea, as it is viewed in Figure 1, is a set of membranous tubes, 31–33 mm. These tubes are coiled much like a snail shell to form two and a half turns around its axis [31]. There are two orifices at the external part of the cochlear bone in the middle ear, both of which are located at the base of the cochlea. The round window is a membranous opening in the bone within the scala tympani and the oval window, in the scala vestibuli. Perilymph is the fluid filling the scala tympani and vestibuli, and its volume in the human cochlea is about 70 µL. The height of the bony cochlea is approximately 4mm. The width of its basal coil, which is the largest, is about 7mm (see Figure 1). One can also note a slight inclination between turns, approximately 9 degrees between the basal and the middle turn and about 2.4 degrees between the middle and the apical turn [32]. Moreover, the cochlear spatial orientation has been studied in detail [33]. The modiolar axis of the cochlea has an average angle (A) of about 40 degrees with the Midsagittal plane. In addition, the cochlea’s axis is almost parallel to the horizontal plane of the skull since the lateral semicircular canal (LSC) forms an angle of 30 degrees forward and upward to the skull’s horizontal plane [22]. ## 2.2. Magnetic Actuator Specifications There are multiple solutions for propelling a microrobot in a viscous medium. The solution adopted here is to use a combination of permanent magnets [30,35]. Such a magnetic actuation system can generate magnetic fields that can induce effective forces to a magnetic device in a compact form-factor. The magnetic actutor proposed by our team [30] and presented in Figure 2 is studied to generate two Lagrangian points in the workspace, called L1 (unstable point) and L2 (stable point), Figure 3. We observe that, on the the actuator axis L1L2, the push force is generated between the two Lagrangian points and the pull force is generated elsewhere. This means that magnetic microrobot located around the point L2 on the axis L1L2 are doomed to be pushed or pulled towards L2. Hence, by positioning the segment L1L2 on a line connecting the magnetic microrobot and the desired position, the microrobot can be controlled in the viscous liquid of the inner ear, thanks to the attractive point L2. In a previous study conducted by our team [36], we introduced the guidance strategy for navigating a microrobot within the cochlea. This stragtegy aims at driving the magnatic microrobots (superparamagnetic nanoparticles) to the targeted cells in the inner ear. This strategy consists of four steps: [1]. Image reconstruction, [2]. Pre-planning, [3]. Trajectory segmentation, and [4]. Pushing/pulling force selection. The magnetic microrobots are encapsulated in a hydrogel and are deposited in contact with the round window membrane (entry point to the scala tympani in the middle ear, RWM, Figure 1). The magnetic actuator is used to extract the microrobots from the gel. Then, it is used to control their movement through the RWM into the scala tympani and to the target area. The actuator offers the possibility of an open loop control to move the microrobots inside the cochlea from the RWM to the apex. The actuator’s axis must be aligned with the direction of the particle displacement in order to be able to push or pull particles in this correct direction. To perform the movement in different directions, we need to move the actuator around the head in the 3D space. This requires the use of a robotic manipulator, adapted to the spherical geometry of the workspace and the constraints related to the cochlea’s anatomy and the magnetic actuator. ## 3.1. Optimal Robot Degrees of Freedom and Workspace The goal was to find the best possible combination of Degrees-of-Freedom (DoF) and workspace for this specific application. The operating principle of the magnetic actuator is the key element for defining the number of DoF. According to the previous actuator description (Section 2.2), in order to move the microrobots along the cochlear trajectory, the attractive Lagrangian point L2 must move within this cochlear trajectory, while keeping the line L1L2 tangent on the trajectory at the point L2. In that way, the microrobots will be adherent to L2 or be in the neighborhood on the line L1L2. This causes them to instantly push towards L2 L2: the microrobots always adhere to L2. Positioning a point in space requires three DoF and orientating an axis needs two DoF, i.e., five DoF are necessary and sufficient to perform the desired task: three linear movements (X, Y and Z) and two rotational movements (ψ and ϕ) (Figure 4). The point, L2, is supposed to be able to reach the top of the head, including the cochlea, on both sides. It should also be able to reach other important organs such as the brain and the eyes (for other medical purposes). Based on that, let the head be approximately a sphere (Figure 5) with a diameter equal to the bitemporal distance. Note: the Lagrangian point L2 is generally referred to as P in this paper, and some times as P1 or P2 when it is necessary to calculate in different frames. ## 3.2. From Specifications to the Shape of the Robot For purpose of compactness, rigidity, and accuracy, we tried to look for a mechanical architecture that can fulfill all the aforementioned specifications as well as possible. Accuracy is mandatory because the point L2 should travel through very small areas (like the cochlea) with high precision, while the structure must be rigid and able to bear significant weights since the magnetic actuator is around 1 kg. All of these factors must be considered together with the need for a compact platform. The desired kinematic structure must be able to position and orientate the actuator in 3D space. The best way to have a compact structure that can perform rotational movements is to think about arcs: this kind of mechanism is called spherical Remote Center of Motion (RCM). See, for example [37,38]. The relevent types mentioned in [37] are Prism Robot for tele-echography, which is a spherical serial structure, and Basic Spherical Mechanism, which is a spherical parallel one that is used in [39]. However, these kinds of RCMs cannot be exploited in our case for reasons of mechanical constraints and rotation range. In [40], the author suggested a mechanism (called Otelo robot) for tele-echography. A similar mechanism of five-DoF is proposed in [40]. RCMs have been widely used in many works like [37], and it is used in this work for purpose of compactness. As for purpose of rigidity and accuracy which are needed for moving the point L2 in small area, we see that the Delta structure developed by Reymond Clavel in 1985 is more compatible. In fact, Alain Codourey, one of the most famous developers of this kind of robot, stated that the Delta robot possesses a number of advantages when compared to serial arms. The most important advantage is certainly the possibility to keep the motors fixed on the base, allowing for a large reduction of the active mobile mass of the robot structure [41]. Besides this feature, the Delta robot consists of three chains, each of which is composed of two segments rather than the three segments in the serial case (to create three degrees of freedom of translation). These two features makes the structure more compact. He also stated in the same article that another advantage of parallel robots is their higher rigidity: these features offer more accurate and much faster manipulations. According to Clavel’s thesis [42], the Delta robot was developed in order to pick up and place light objects (20 g) at high dynamics. However, having three chains (in the Delta robot) connected to one point is meant in our case to increase the rigidity against the gravity, since the end-effector weight is around 1 kg and its speed is very low because its use is for medical purposes. In the same reference, it is stated that the Delta robot suffers from limited workspace (the price of rigidity and precision). This causes no trouble in our case, since the workspace needed to be reached is relatively small (see Figure 5). ## 3.3. Mechanical Design Description Figure 6 shows an assembly of different organs of the five-DoF robot. This robot is a hybrid combination of a spherical serial mechanism and a parallel one. It consists mainly of four parts: the support [1], the arc (the curved arm [2]), the slider [3], and the parallel structure (Figure 7). The arc is linked to the support by a without-friction ball-bearing articulation [4] and actuated by the motor [5] to generate the rotation ϕ. The slider can move smoothly on the arc thanks to a eight-balls-contact [6] and a pulley actuated by the motor [7]. Rolling the pulley [8] on a belt [9] (pasted on the arc [10]) generates the rotation ψ. The slider itself represents a mobile base for the Delta structure, which consists mainly of three identical kinematic chains [11] linking the slider with a mobile board [12] (it is conventionally called nacelle in [42]). Each kinematic chain comprises an arm [13] and a forearm [14], joined together with the nacelle via ball joints [15]. Each forearm is linked to its corresponding motor-gear axis via a hub [16]. The fact that the arms have a parallelogram structure restricts the movement of the nacelle to pure translations with no rotation with respect to the slider. This makes it easy to control the magnetic actuator [17] linked to the nacelle. Finally, the gears [18] allows to reduce the motor speeds 231 times (3 × 7 × 11), so even with the energy lost in the gears, the torque is increased by more than 200 between the rotors [19] and the joints. ## 3.4. CochleRob Joints Five joints are attributed to the robot for optimal number of degrees of freedom (DoF):The movement of the three kinematic chains of the delta structure is controlled by three joints, represented by the angles α1,α2, and α3. These angles represent the angle between the forearm [14] and the relative horizontal plane. The different dimensions and joints of the delta part is illustrated in Figure 8. This part can be simplified if each chain (segments l1 and l2) is translated toward the axis Oz1 by a distance l0. The equivalent configuration is illustrated in Figure 9, with r=l0−l3.The fourth joint is represented with the angle ϕ. It is the rotation of the slider [3].The fifth joint is represented with the angle ψ. It is the rotation of the arc [2]. See Figure 10. ## 4.1. Modeling The Forward Kinematics Model (FKM) aims to calculate the end-effector coordinates (position and orientations) as a function of the joint variables of the mechanism (ψ, ϕ, α1, α2, α3), see Figure 11. The frames are assigned to the robot links in Figure 8 and Figure 10 so that the rotations angles of the end-effector are the same as the serial part joints angles (ψ, ϕ). Having such a choice, we need just to find the end-effector position (X, Y, Z) as a function of ψ, ϕ, α1, α2, and α3, in order to establish the FKM. It is noticeable that the robot is composed of two main parts joined together in a serial chain:Serial part, in which the joints are ψ and ϕ.Parallel structure, for which the joints are α1, α2, and α3. Let the following frames and points be defined as the following:R0=x→0,y→0,z→0 is the word frame, Figure 10.R1=x→1,y→1,z→1 is a mobile frame fixed on the slider (component [3] Figure 7), as indicated in Figure 8, Figure 9 and Figure 10.R2 and R3 are tow frames shifted from R1 by rotations ϕ2=2π3 and ϕ3=4π3, respectively, around z→1, Figure 12.Pn=xn,yn,zn is the position of the nacelle center (component 12 in Figure 7), expressed in frame R1, Figure 8.P=X,Y,Z is the end-effector position (L2) expressed in R0. It is the aim of this section. P1=x,y,z is the end-effector position (L2), expressed in R1. In order to find the relationship between the joints angles and end-effector position P, we must first establish the expression of P1 with respect to the moving frame R1, as a function of α1, α2, and α3. In the second step, we project those calculated coordinates (x,y,z) into the steady frame R0: it is a transformation from R1 to R0 based on ψ and ϕ, shown in Figure 11. The rotation matrix from Ri to R1 is calculated as shown below (Equation [1]):[1]Ai=cos(ϕi)−sin(ϕi)0sin(ϕi)cos(ϕi)0001 with: ϕ1=0, ϕ2=2π3, ϕ3=4π3. The point Ci has the following coordinates (Equation [2]):[2]Ci=Ai·r+l1·cos(αi)0−l1·sin(αi)Ri=r+l1·cosαicosϕir+l1·cosαisinϕil1·sinαiR1 Then, the vector CiP expressed in R1, is obtained with (Equation [3]):[3]CiP=P−Ci=x−r+l1·cosαicosϕiy−r+l1·cosαisinϕiz+l1·sinαiR1 Equation [3] is used in the dynamic model. The method to calculate the coordinates (xn,yn,zn) of the nacelle position Pn with respect to R1 is explained in Clavel’s work [42], with the following equation (Equation [4]):[4]zn=M−M2−4·L·N2·Lxn=H5·z+H4H2yn=H1·z+H3H2 with:$L = 1$+H52+H12H22M=−2·H5·H4+H1·H3H22+E1·H5+F1·H1H2+G1N=D1+H42+H32H22−E1·H4+F1·H3H2 D1=−l22+l12+r2+2·r·l1·cos(α1)D2=−l22+l12+r2+2·r·l1·cos(α2)D3=−l22+l12+r2+2·r·l1·cos(α3)E1=2·(r+l1·cos(α1))·cos(ϕ1)E2=2·(r+l1·cos(α2))·cos(ϕ2)E3=2·(r+l1·cos(α3))·cos(ϕ3)F1=2·(r+l1·cos(α1))·sin(ϕ1)F2=2·(r+l1·cos(α3))·sin(ϕ3)F3=2·(r+l1·cos(α3))·sin(ϕ3)G1=−2·l1·sin(α1)G2=−2·l1·sin(α2)G3=−2·l1·sin(α3)H1=−(E3−E1)·(G2−G1)+(G3−G1)·(E2−E1)H2=−(F3−F1)·(E2−E1)+(E3−E1)·(F2−F1)H3=−(D3−D1)·(E2−E1)+(E3−E1)·(D2−D1)H4=(D3−D1)·(F2−F1)+(F3−F1)·(D1−D2)H5=−(G3−G1)·(F2−F1)−(F3−F1)·(G1−G2) Considering the distance L between the point Pn and the attractive point P1, we get the following expression, Equation [5]:[5]P1=Pn+00−LR1=xnynzn−LR1 Finally, through a transformation (one translation and two rotations) from R1 into frame R0, we find the end effector position with respect to R0:[6]P=A0″·P1+00R=A0″·xnynzn+R−LR1 where R represents the arc radius, and [7]A0″=cos(ϕ)−cos(ψ)·sin(ϕ)−sin(ψ)·sin(ϕ)sin(ϕ)cos(ψ)·cos(ϕ)sin(ψ)·cos(ϕ)0−sin(ψ)cos(ψ) ## 4.2. Validation of the FKM Model The aim of this validation is to compare our analytic FKM with the numerical FKM exported from SolidWorks to SimMechanics. For identical articular inputs, we compared the end-effector positions and orientations obtained by the two computational approaches (analytic and numerical models). Figure 13 shows the difference between two signals representing the end-effector position P=X,Y,Z with respect to frame R0. One signal is from the block named Robot representing the model imported from SolidWorks environment. The other comes from the block named Analytic FKM representing the model calculated in this section. Both diagrams receive their inputs from the same source; the result of the simulation is illustrated in Figure 14. The simulation shows that the FKM and SolidWorks approaches give very similar results since the errors are null (10−14≈0). The FKM elaborated in this section is thus validated. ## 5.1. Modeling The Inverse Kinematics Model (IKM) aims to calculate the joints angles α1, α2, α3, ψ, and ϕ as a function of rotation and position P of the end-effector, see Figure 15. As mentioned previously, the end-effector rotations are the same as the serial part joint angles ψ and ϕ. Thus, the objective of this section is to calculate α1, α2, and α3 in terms of (X,Y,Z), ψ, and ϕ. The transformation from P to P1 can be calculated easily by following the opposite steps indicated in the previous section. A superior option would be to establish it in a straightforward manner from Equation [6]:[8]P1=A0″t·P0−00RR1 Another backward step concluded from Equation [5]:[9]P=P1+00LR1=xyz+LR1 Multiple formulations have been proposed in order to calculate the IKM of the Delta robot [42,43]. The one used in [42] consists of [10]αi=arctan−2z+Fi−2r−S−Qi(rl1−1) where: Fi=4z2+4r2−S2+Qi2(1−r2l12)+Qi(−2r·Sl1−4r)Qi=2·x·cos(ϕi)+2·y·sin(ϕi)$S = 1$l1−x2−y2−z2+l22−l12−r2 ## 5.2. Numerical Validation of the IKM Model Since there is no numerical IKM to compare with, we used the previous numerical (or analytical) FKM to validate our analytic IKM implicitly. Contrary to the previous validation, where we put the two models in parallel connection and compared their outputs, this time, we put our analytical IKM and the FKM in series as described in Figure 16. Eventually, if the IKM maps correctly from their inputs, i.e., the Cartesian coordinates (X,Y,Z,ϕ,θ) to the joints’ parameters (α1,⋯,θ), the outputs of FKM (X,Y,Z) (the block named Robot) must be identical to the inputs of the analytic IKM (X,Y,Z). The scope in Figure 17 shows the errors are null (10−13≈0), which means that the IKM maps correctly. ## 6. The Dynamic Model This section presents a dynamic model of the hybrid robot that defines the necessary torques, Ti, that must be applied by each motor i when the mechanism performs some desired task: see Figure 18. Obviously, the torque Ti, provided to the different kinematic chains, has the role to undo the gravity effects on the robot organs. It also must ensure that they travel through space within some desired acceleration as well: see Equation [11]:[11]Ti=Tig+Tia Such that As described previously, during the operation, the end effector travels through the space with a very low velocity. Moreover, its mass is very considerable (around 1 kg), which means the acceleration torque is negligible when compared to the gravity torque effect. In addition, the gear ratio ($$n = 231$$) is also an important reason to ignore the acceleration torque of the different organs. Thus, the only dynamic that will be involved is the angular acceleration (θi¨) of each motor rotor, since it is not affected by the gearbox reduction. That being said, the acceleration torque is reduced to Tia=Ji·θi¨. This fact allows us to have a very simplified and accurate model, rather than a very complicated one. Thus, the Equation [11] becomes Equation [12]:[12]Ti=Tia+Tig=Ji·θi¨+Tig The following study will establish the dynamic model of the Delta structure. Then, the dynamic model of the serial structure will be established. ## 6.1. The Dynamic Model of the Delta Structure The main factor in this section is the gravity. With respect to the original base R0, it is a vector that has one component, laid upon the z-axis:[13]g→=0,0,−9.81t Meanwhile, it is a mobile vector with respect to the Delta structure. Having the gravity g1 expressed in R1 is more compatible to calculate the gravity torques Tig for the Delta structure. g1→ is the expression of the gravity in R1:[14]g1→=A0″−1·g→ Let be the following denotations:M1: the mass of the forearm l1.M2: the mass of the parallel sticks l2.M3: the mass of the nacelle.the center of mass of each parallel sticks is the midpoint of the segment l2.the center of mass of each forearm is at a distance of d1 from the corresponding joint Ai. Having three masses M1, M2, and M3 on each kinematic chain (Figure 18) is equivalent to having two masses Me1 and Me2 linked to the corresponding elbow Ci and the point P, respectively, (roughly speaking, the configuration Figure 18 is equivalent to the configuration Figure 19), with Me1=M1·d1l1+M22 and Me2=M3+3·M22 The gravitational forces (expressed in R1) of those two masses are [15]Ni→=g1→·Me1,with:$i = 1$,2,3.Z→=g1→·Me2 The force Ni→ is applied on the elbow Ci, while Z→ is applied on the point P. It is composed of three components laid on the parallel segments. shown in Figure 20:[16]Z→=Zu1→+Zu2→+Zu3→ given that:[17]Zu1→=Zu1·u1→Zu2→=Zu2·u2→Zu3→=Zu3·u3→ where u1→, u2→, and u3→ are unit vectors expressed in R1 and carried on the parallel segments (l2), with [18]u1→=C1P→C1P,u2→=C2P→C2P,u3→=C3P→C3P with CiP is determined in Equation [3]. Then, the Equation [16] becomes [19]Z→=u1→,u2→,u3→Zu1Zu3Zu3 Thus, the components of the force Z→ with respect to the unit base u1→u2→u3→ are well determined:[20]Zu1Zu3Zu3=u1→,u2→,u3→−1Z→ As illustrated in (Figure 21), the total force applied on each elbow *Ci is* [21]fi→=Zui.ui→+Ni→⏟expressedinR1 Each elbow i belongs to its associated base Ri. Expressing fi→ in this base is convenient to next calculations. To do that, we multiply fi→ by Ai−1=AiT. This matrix is elaborated in Equation [1]. Moreover, each forearm has only one freedom in the plane Oxzi, meaning that the only component of fi→ that has mechanical work is fixz. The component fiy has no effect: see Figure 22: [22]fixz→=100000001·AiT·fi→⏟expressedinRi Next, the torque due to the gravity applied on each forearm i, with respect to its corresponding joint, Ai, is [23]0,1,0·ACi→×fixz→ where:[24]ACi→=l1·cos(αi)0−l1·sin(αi)Ri Finally, the torque provided by each actuator i associated with the joint *Ai is* [25]Tig=−0,1,0·ACi→×fixz→·1231 The dot product has appeared because the torque vector ACi→×fixz→ has no component on the plane Oxzi, but rather, only one component on the y-axis that affects the forearm. The minus sign has been introduced because the torque provided to the joint i must oppose the gravity torque in order to prevent its effect on the elbow. The number 231 represents the gearbox ratio. By dividing by this ratio, we get the torque that must be generated by the motor i. ## 6.2. The Dynamic Model of the Serial Structure The gravity has no effect on the fifth joint (ϕ). Then, [26]T5g=0 It substantially affects the fourth actuator, associated to (ψ), due to the end-effector mass M3 and the slider mass M4, as is illustrated in Figure 23. The torque generated with respect to the point O is [27]C=R−zn·M3+R·M4·sin(ψ) Although the masses of the kinematic chains are neglected, the torque due to these masses can be approximately introduced in the previous equation as following:[28]C=R−zn·M3+3·M1+M22+R·M4+3·M1+M22·sin(ψ) Let ψ′ be the rotation of the pulley (component [7] Figure 7), C′ be the torque generated by the pulley, and C be the torque generated by a fictive actuator hypothetically placed at the center O. Then, the work provided by the pulley, C′.dψ′, equals the work provided by the fictive actuator, C·dψ. [ 29]C′·dψ′=C·dψ Since there is no sliding between the pulley and the arc (as it is demonstrated in Figure 24), [30]dψ=dψ′·RpR where *Rp is* the pulley radius and R is the arc radius (component [2] Figure 7). From Equations [29] and [30], [31]C′=C·RpR By introducing the gearbox ratio of $$n = 231$$, we get [32]T4g=C′231 Finally:[33]T4g=sin(ψ)Rp231·R·R−zn·M3+3·M1+M22+R·M4+3·M1+M22 Note that the motors rotation angles have the following relations:[34]θi=231·αi;$i = 1$,2,3.θ4=231·RRp·ψθ5=231·ϕ To conclude, the dynamic model is briefly described by the following equations: [35]Ti∈{1,2,3}=Ji·θi¨−0,1,0.ACi→×fixz→.1231T4=J4·θ4¨+sin(ψ)Rp231·R·R−zn·M3+3·M1+M22+R·M4+3·M1+M22T5=J5·θ5¨ ## 6.3. Validation of the Dynamic Model The dynamic model, Equation [35], is compared with the numerical model imported from the SolidWorks environment in this section, shown in Figure 25. In this simulation, the actuator moves in space along a desired trajectory, and its mass is 1 kg. The velocity is not as low as previously supposed. It is considerable enough to know the extent of the model accuracy. Figure 26, Figure 27 and Figure 28 represent the errors of the torques Ti. Even though the movement of the robot was fast, the reason to not calculate the different organs’ dynamics (due to their accelerations) is still fulfilled here. In fact, the simulation shows that the models have high accuracy, since the errors are 10−6, 10−5, and 10−4 N·m, which means there is no error. ## 7. The State Model In this system, the state variables are the rotation angles θi, described in Equation [34], their angular velocities θ˙i, and the current of each motor Ii. The tensions u1, u2, u3, u4, and u5 are the system inputs. The set of differential equations for each motor are [36]Ii˙=−RL·Ii−KL·θ˙+1Luiθi¨=1J·Ti−1J·TigTi=K·Ii These equations represent, respectively, the electrical equation, the mechanical equation, and the electromechanical equation. R is the resistance, L is the induction, and K is the velocity constant (it is equal to the torque constant). Let us take the following denotations: a3=KJ, ag=−1J, b1=1L, b2=−KL, b3=−RL. and: x1=θi, x2=θi˙, x3=Ii Then, each motor state model will be as following:[37]x1˙=x2x2˙=a3·x3+ag·Tigx3˙=b3·x3+b2·x2+b1·ui The whole robotic system model is illustrated in Figure 29. ## 8.1. Control Architecture This is a non-linear system of 15 state variables. A PID controller can be introduced if we consider Tig as a perturbation on the system. Alternatively, a better choice would be to transform the model to a linear one with feedback linearization. The state model can be separated to two submodels, as illustrated in Figure 30 below: The electrical subsystem can be linearized and decoupled from the mechanical subsystem by applying feedback linearization ui=−b2·x2+vib1, which will undo the mechanical term to obtain the following linear submodel:[38]x3˙=b3·x3+vi This linear system can be controlled with linear controllers such as a PID. We take advantage of the fact that the electrical subsystem is much faster then the mechanical subsystem, so we directly control the mechanical subsytem via the output of the electrical subsystem (cascade controller). We consider x3 as the input of the mechanical subsystem. We apply the linearizer feedback: x3=−ag·Tg+va3 to get a linear process: [39]x˙1x˙2=0100·x1x2+01·v This decoupled linearized system can be controlled with a linear controller. The friction of the various Delta structure parts will have almost no effect on the motors torques due to the following reasons:As discussed and validated in the dynamic model section, the velocity and acceleration of the various Delta structures have no effect on the motors’ torques because of the high-reduction and the slowness required during the operation. Thus, the friction is also neglected since it is proportional to the velicty. In case we want to consider friction of the motors rotors, the Equation [39] takes the following form: [40]x˙1x˙2=010−ζ·x1x2+01·vWith (ζ·x2) being the friction of each motor. It is convenient to deploy a cascade control that involves two controllers, one of which nestles inside the other, such that the outer controller (position controller) feeds the inner one (current controller) with the set references, x3*, shown in Figure 31. Such a system can give an improved response to disturbances [44]. ## 8.2. Trajectory, Validation by Simulation In this section, we simulate the controller by assigning a desired trajectory to the end effector. The point L2, that travels through the cochlea, is approximated to be a helical curve, on which the axis L1L2 must be tangent. The arc makes multiple half turns because of patient body constraints. The simulation, made using SimMechanics and shown in Figure 32, gives the results represented in Figure 33. Snapshots are shown in Figure 34. The results illustrated in Figure 33 show that the motors’ angles very accurately follow the given references. Figure 34 shows that L2 could travel through the desired trajectory, keeping the axis L2L1 tangent on the curve. This validates both the IKM and the controller. ## 9. Prototyping and Experimental Validation After manufacturing the various mechanical organs of the platform via an additive manufacturing technique, all these parts, including the sensors and actuators, have been assembled to make the first prototype of the CochleRob manipulator (Figure 35). This manipulator is controlled via a computer using LabVIEW software and Maxon controllers. The motors are Maxon as well. They were chosen after a trade-off was done between its length (which should ideally be short) and its torque (which should be higher). This implemented closed loop uses a classic PID controller. The experimental results are illustrated in Figure 36. As we can see, the motors’ angles very accurately follow the given references. This experiment validates the operation of the platform and the different models developed in this work. ## 10. Conclusions and Perspectives Our research into a new solution for treating inner ear diseases by remotely-controlled local drug administration resulted in a novel manipulator robot, CochleRob. The following are the key findings and achievements of our work:Our work introduces a new approach for intracochlear drug administration for the treatment of hearing loss through the development of the hybrid parallel–serial robot, CochleRob. This robot has a compact, precise, and rigid structure with five degrees of freedom that meets the requirements of positioning a magnetic actuator within the inner ear, including the necessary workspace and degrees of freedom. CochleRob reduces the risk of cochlear damage by the introduction of electrode arrays or catheters inside the cochlea. Drugs are delivered remotely, without the need for catheter or CI insertion. Through the validation of mathematical models, including kinematics, dynamics, and control laws, we have demonstrated the feasibility and effectiveness of our proposed solution. The results obtained from simulations were highly satisfactory, supporting the potential of CochleRob as a promising solution for the safe treatment of hearing loss. The proposed robot has been successfully prototyped and its components were manufactured using the additive manufacturing process. The robot was effectively controlled using Labview software, further demonstrating its viability as a solution for treating hearing loss. The motors chosen for the robot met the necessary specifications for torque and volume. It is important to note that, while our proposed solution presents a promising step towards safe and effective treatment of hearing loss, further research and development are necessary to fully exploit its potential and to enhance the feasibility and reliability of our proposed robot. For example:*It is* important to consider the potential movement of the patient. Currently, it is possible to perform the procedure with a stabilized head using a face mask, a headband, or even anesthesia; however, this solution may not always be feasible or desirable. To address this issue, the head position can be tracked and fed back to the controller in real-time, enabling the adjustment of the assigned trajectory and reducing the risk of error. Several potential solutions for tracking the head position can be investigated, including deep neural network-based visual tracking using face landmark detection, among others. 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--- title: 'A Novel Symbiotic Beverage Based on Sea Buckthorn, Soy Milk and Inulin: Production, Characterization, Probiotic Viability, and Sensory Acceptance' authors: - Nicoleta-Maricica Maftei - Alina-Viorica Iancu - Roxana Elena Goroftei Bogdan - Tudor Vladimir Gurau - Ana Ramos-Villarroel - Ana-Maria Pelin journal: Microorganisms year: 2023 pmcid: PMC10054883 doi: 10.3390/microorganisms11030736 license: CC BY 4.0 --- # A Novel Symbiotic Beverage Based on Sea Buckthorn, Soy Milk and Inulin: Production, Characterization, Probiotic Viability, and Sensory Acceptance ## Abstract Nowadays, vegan consumers demand that food products have more and more properties that contribute to the prevention of some diseases, such as lower fat content, increased mineral content (calcium, iron, magnesium, and phosphorus), pleasant flavor, and low calorie values. Therefore, the beverage industry has tried to offer consumers products that include probiotics, prebiotics, or symbiotics with improved flavor and appearance and beneficial effects on health. The possibility of producing beverages based on soy milk with sea buckthorn syrup or sea buckthorn powder supplemented with inulin and fermented with the Lactobacillus casei ssp. paracasei strain was examined. The aim of this study was to obtain a novel symbiotic product that exploits the bioactive potential of sea buckthorn fruits. Tests were carried out in the laboratory phase by fermenting soy milk, to which was added sea buckthorn syrup ($20\%$) or sea buckthorn powder ($3\%$) and inulin in proportions of $1\%$ and $3\%$, with temperature variation of fermentation (30 and 37 °C). During the fermentation period, the survivability of prebiotic bacteria, pH, and titratable acidity were measured. The storage time of beverages at 4 °C ± 1 °C was 14 days, and the probiotic viability, pH, titratable acidity, and water holding capacity were determined. Novel symbiotic beverages based on sea buckthorn syrup or powder, inulin, and soy milk were successfully obtained using the Lactobacillus casei ssp. paracasei strain as a starter culture. Moreover, the inulin added to the novel symbiotic beverage offered microbiological safety and excellent sensory attributes as well. ## 1. Introduction Today, all around the world, people’s desire to consume functional drinks is huge, and for this reason, they have begun to be added to the modern medicine cabinet. From a commercial and medical point of view, there is a wide variety of functional beverages that can meet the different nutritional requirements and ingredient preferences of consumers around the world. Some of the common categories include vegetable and fruit-based drinks, whey and soy protein drinks, sports drinks, and tea-based drinks. A few examples can be mentioned, such as kvass, produced from rye flour or stale rye bread in several Eastern Europe countries and Russia [1]; borş, a liquid obtained by natural fermentation of an aqueous suspension of wheat bran—“tărțe” means “bran” in Romanian—and corn flour [2], green mung beans, and red kidney beans [3]; fruit beer; water kefir; vinegar [4]; boza, obtained from millet, corn, wheat, or rice and consumed in Bulgaria, Albania, Turkey, Greece, and Bosnia Herzegovina [5]; Jerusalem artichoke [6]; prickly pear juice [7]; and apricot juice [8]. Among all functional food categories, the functional beverage market is the fastest growing, and by 2025, it is expected to increase to $40\%$ of entire consumption [9]. Sea buckthorn (Hippophae L.) is a valuable plant extensively characterized by a unique composition of bioactive compounds. Its use is growing in Europe, Canada, Asia, and the USA [10]. Due to high amounts of antioxidants, it is widely used for nutraceutical and medicinal purposes. Apart from its antioxidant capacity, sea buckthorn was observed to have antibacterial and antiviral [11], hepatoprotective and dermatological [12], antidiabetic [13], anti-inflammatory [14], and anticarcinogenic [15] effects. The positive biological, physiological, and medicinal effects of sea buckthorn were extensively described in a multitude of studies [16,17,18,19,20]. Vegetable beverages are extracts from legumes, plants, cereals, seeds, etc., in water and have been used worldwide as a replacement for cow’s milk. There is a large market for vegetable beverages all around the world, but soy drinks are the most consumed [21]. According to a report by Grand View Research, the soy beverage segment led the industry in 2021 and accounted for the maximum share of more than $38.40\%$ of the overall revenue [22]. The global soymilk market size was valued at USD 7.30 billion in 2018 in a market analysis report [23]. The main reason for the huge consumption of vegetable and plant-based drinks such as soybean beverages, to the detriment of dairy products, is caused by growing consumption by people with medical problems such as allergy to cow’s milk proteins, lactose intolerance, and/or cholesterol problems [24]. In recent years, globally, consumers have accepted the use of vegetable and plant sources to produce functional foods due to their bioactive components that present better health benefits, which also favored the increase in their consumption [25]. Inulin is a natural polysaccharide that belongs to a class of dietary fibers that are usually found under the name of fructans [26]. The compound that results from the combination of inulin with fructooligosaccharides can be used as a dietary non-digestible fiber. It is often used in food industries because it promotes a beneficial effect on the host’s gut microbiota by stimulating the growth of bifidobacteria in the human intestine. The main reason inulin is used is its prebiotic effect. On the other hand, it is also utilized for the control of sugar levels in the blood, prevention of obesity, lipid metabolism, the absorption of mineral ions from the gut, and colon cancer [27]. These are some extra benefits of inulin regarding the beneficial effects on the human body. Because the fermentation process involves mixed cultures of LAB, or fungi and yeast, traditional fermented foods are an abounding source of microorganisms, and some show probiotic characteristics [28]. In the literature, it is mentioned that upon ingestion of probiotics (viable microorganisms) in adequate amounts, health benefits are exerted, which improve the intestinal microbial balance. Lactobacilli and bifidobacteria are the most used probiotic that can survive in the intestinal tract. Moreover, by combining probiotics and prebiotics (i.e., symbiotics), synergistic benefits may be observed. However, there is a small number of studies on the development of symbiotics, and the in vivo and in vitro effectiveness of symbiotics has not been intensively studied to date. Innovations and novel product development come with their own set of challenges, and each matrix (vegetable or fruit) is unique. These products require the standardization of the process to obtain a product with acceptable organoleptic properties and, more importantly, demonstrable health benefits. Hence, this study aimed to develop a novel symbiotic beverage based on lactic acid bacteria, soy milk, and sea buckthorn syrup or powder enriched with inulin to evaluate the physicochemical, nutritional, bioactive, and sensory characteristics of the formulation obtained. The viability of probiotic bacteria, the major physicochemical properties during 6 h of fermentation and 14 days of storage at 4 °C and the sensory properties of these products were analyzed. ## 2.1.1. Soy Milk In this experiment, Dr. Oetker soymilk–Soy Beverage Inedit from Company, Romania—was used. This is a sterilized product obtained from selected organic-certified ingredients. Per the labeled data, the product contains the following ingredients: $1.1\%$ proteins, $0.0\%$ sugars, and $1.9\%$ lipids. ## 2.1.2. Sea Buckthorn Syrup The sea buckthorn syrup used in these experiments came from the Plafar market in Galati, Romania. The untreated syrup contains the following soluble solids: 6° Brix with a pH of 3.10. All samples utilized during the experiment came from the same batch. ## 2.1.3. Plant Material for Sea Buckthorn Powder Sea buckthorn berries were collected from the region of Moldavia (Romania) in September 2020 and were stored at −20 °C prior to the experiments. Sea buckthorn fruits were previously subjected to washing, sorting, and cleaning operations and were squeezed with the help of a mixer, and the collected juice was freeze-dried with a Freeze-dryer Alpha 1-4 LDplus (Martin Christ Gefriertrocknungsanlagen GmbH, Osterode am Har, Germany). ## 2.1.4. Starter Cultures (Probiotic Bacteria) Lactobacillus casei ssp. paracasei was provided by Christian Hansen (Hørsholm, Denmark) as a starter culture with the commercial name L. casei® 431 in a freeze-dried form. Starter culture maintenance and storage were carried out per the manufacturer’s recommendation. ## 2.2. Fermentation of Beverages and Analytical Assays Four pilot-scale beverage-making trials with:(a)$20\%$ sea buckthorn syrup (w/w) in milk and $1\%$ (w/v) commercial inulin;(b)$20\%$ sea buckthorn syrup (w/w) in milk and $3\%$ (w/v) commercial inulin;(c)$3\%$ (w/v) sea buckthorn powder in milk and $1\%$ (w/v) commercial inulin;(d)$3\%$ (w/v) sea buckthorn powder in milk and $3\%$ (w/v) commercial inulin, respectively, were prepared. A total quantity of 1500 g per beverage formulation was produced per each trial, and the whole experiment was repeated three times. After mixing the soy milk with sea buckthorn syrup or sea buckthorn powder and inulin, the mixtures were homogenized separately with an Ultra Turrax blender (IKA, Merck, Darmstadt, Germany) at 14,000 rpm until all ingredients were dissolved in the soy milk. Then, 100 mL mixtures were inoculated with starter culture and were fermented for 6 h at 30 and 37 °C. Samples were taken during the incubation at 0, 2, 4, and 6 h to test the following parameters: starter culture growth, pH, and titratable acidity. After fermentation, the samples were stored for 14 days at 4 °C ± 1 °C. During the entire storage time, the viability of probiotic bacteria, pH, titratable acidity, and water-holding capacity were measured. A pH meter (MP2000, Mettler Toledo, Greifensee, Switzerland) was used to measure the pH. A solution of 0.1 N NaOH was used to determine the titratable acidity, and it was expressed in grams of lactic acid per 100 mL of fermented product. Immediately after preparation, its physico-chemical characterization was determined. An Atago RX-1000 refractometer (Atago Company Ltd., Tokyo, Japan) was used for the soluble solid content, and an InoLab Multilevel 1 conductive meter (Senton, GmBh, Egelsbach, Germany) was used for the electrical conductivity of the beverages. ## 2.3. Probiotic Viability DeMan–Rogosa–Sharpe (MRS) agar was used to grow lactic acid bacteria (Lactobacillus casei ssp. paracasei). A series of dilutions using $0.1\%$ (w/v) peptone water (Merck) were prepared by aseptically removing the diluent of culture until the dilution factor determined in the preliminary test was achieved. Using the spread plate method, 0.1 mL of the sample was transferred onto the agar, and plates were incubated at 37 °C for 48 hrs. Anaerobic conditions were established using an anaerobic jar (Merck) with Anaerocult® A kit (Merck). Plates containing from 30 to 300 colonies were chosen for enumeration, which was expressed in colony-forming units per milliliter of product (CFU·mL−1). Analyses were performed in triplicate. ## 2.4. Water-Holding Capacity (WHC) To measure the water-holding capacity (WHC) in the beverages, approximately 10 g of beverage was transferred into a 20 mL glass tube and centrifuged (Mikro 220R, Hettich, Tuttlingen, Germany) at 2500 rpm for 10 min at 20 °C (modified method of [29]). The WHC was calculated as follows: Water-holding capacity, % = (weight of supernatant/weight of beverage) × 100[1] ## 2.5. Rheological Measurements For the study of the beverage’s rheological properties, a rheology assay was carried out immediately after the manufacturing of each beverage formulation using an RHEOTEST-2 type rotating viscometer manufactured by VEB-MEDINGEN, Germany. All samples were gently stirred before rheological analysis. A total of 50 g of the sample was tested, and the coaxial cylinder device S3 was used due to the medium viscosity of the samples. The shear rate (γ) varied between 0.1667 to 145.6 s−1, and the working frequency was 50 Hz. The apparent viscosity (η) was calculated as:[2]η=τγ where γ = shear rate and η = apparent viscosity. ## 2.6. Sensory Evaluation Sensory evaluation was carried out after 24 h storage at 4 °C. The hedonic scale was used to determine the degree of sensory acceptance for symbiotic beverages based on soy milk, sea buckthorn syrup or powder, and inulin. Ten untrained panelists were given 10.0 g of each sample. The samples were served at 8 ± 2 °C in plastic cups labeled with three-digit codes and were evaluated for aroma, texture, taste, and overall acceptability based on a seven-point hedonic scale (1 = dislike extremely, 5 = either like or dislike, 7 = like extremely). ## 2.7. Statistical Analysis All the experiments were carried out in triplicate, and the data were analyzed using the *Statgraphics plus* v.5.1 package (Manugistics Inc., Rockville, MA, USA) with one-way analysis of variance. The results were presented as mean ± S.D (standard deviation). The comparison of means was conducted using Duncan’s Multiple Range Test (DMRT) with values that have no common superscript significantly different ($p \leq 0.05$). ## 3.1. Microbial Growth and Physico-Chemical Parameters during the Fermentation Period The counts for Lactobacillus casei ssp. paracasei (L. casei® 431) strain in fermented beverages are shown in Figure 1a,b. In all samples, L. casei® 431 grew without the need to add nutrient supplementation. After 6 h of fermentation, the microbial load (L. casei® 431 strain) increased exponentially in the product to around 1.13·108 CFU·mL−1 for sea buckthorn powder (SBP) beverages and 1.11·108 CFU·mL−1 for sea buckthorn syrup (SBS) beverages (Figure 1a,b), starting from an initial concentration of 4.8·105 CFU·mL−1 from the sample with SBS and 5.2·105 CFU·mL−1 from the sample with SBP. The multiplication rate increased progressively for all samples ($p \leq 0.05$). For the sample with $3\%$ inulin and SBP (5.2·107 CFU·mL−1) fermented at 37 °C, significantly more growth was observed. The pH values of all beverages (Figure 2a,b) decreased from the initial pH of 4.21, 4.01 to 3.87 and 3.88 for the SBS samples fermented at 30 °C and 37 °C with $1\%$ and $3\%$ inulin, respectively. For SBP beverages, the pH values after 6 h of fermentation were similar—3.89 at 30 °C for both beverages and 3.86, 3.92 at 37 °C for beverages with $1\%$ and $3\%$ inulin, respectively. The pH decrease was caused by the production of organic acids. As shown in Figure 3a,b, the titratable acidity of the samples increased alongside the decrease in pH for all samples. The titratable acidity reached 1.07 g lactic acid 100 mL−1 for the sample with $1\%$ inulin and 0.89 g lactic acid 100 mL−1 for the sample with $3\%$ inulin and SBS fermented at 30 °C, post 6 h of fermentation. For the SBS samples fermented at 37 °C, the titratable acidity reached 1.08 g lactic acid 100 mL−1 and 0.93 g lactic acid 100 mL−1. At the end of the fermentation, there was approximately 0.65 g lactic acid 100 mL−1 and 0.48–0.74 g lactic acid 100 mL−1 for SBP beverages with $1\%$ and $3\%$ inulin, respectively, fermented at 30 °C and 37 °C. The physicochemical and rheological characteristics are presented in Table 1 and Table 2 for all beverages before inoculation with probiotic bacteria. The increase in the soluble solids content and the decrease in pH were caused by the increase in inulin content. The viscosity of the beverages increased with the concentration of inulin (Table 2), regardless of the fermentation temperature. For SBS beverages, the increase in inulin concentration percent decreased the acidity, as observed in Table 1. For SBP beverages, percent acidity increased with the increase in inulin concentration. The electrical conductivity was the same for beverages with $3\%$ inulin and increased for beverages with $1\%$ inulin. During the fermentation period, the increase in acid production, as demonstrated by the lower pH and higher titratable acidity values, was associated with the consumption of TSS. In conclusion, these are indicative of the post-acidification microbiological process. ## 3.2. Survivability of Probiotics and Physicochemical Parameters during the Storage Period It can be observed from our results that the L. casei® 431 strain has good survival rates without nutrient supplementation in all beverages. Figure 4a,b presents the changes in the cell viability of the L. casei® 431 strains ($p \leq 0.05$) for the 14 days of cold storage at 4 ± 1 °C. This evaluation began after the end of the 6 h of fermentation. There was a reduction in the viability of L. casei® 431 cells after one day of storage in all formulations. At the end of the storage period, the total viable cells of L. casei® 431 were decreased moderately to 1.11·107 for the SBS beverage with $1\%$ and 1.15·107 for the SBS beverage with $3\%$ inulin, fermented at 30 °C, and 1.14·107 and 1.15·107 CFU·mL−1 for the SBS beverage with $1\%$ and $3\%$ inulin, fermented at 37 °C (Figure 4a), respectively. However, the SBP beverage with $1\%$ and $3\%$ inulin fermented at 30 °C and 37 °C presented a bigger population of L. casei® 431 compared to all the formulations ($p \leq 0.05$). After the storage period, the viability of L. casei® 431 remained at an acceptable level (over 107 CFU·mL−1). Figure 5a,b presents the pH evolution ($p \leq 0.05$) for all samples during the storage period. The pH ranges between 3.61 and 3.64 for the SBS beverage with $1\%$ inulin fermented at 30 °C and 37 °C, respectively, and 3.59 for SBS with $3\%$ inulin for both temperatures of fermentation after storage time. However, for the SBP beverages, the pH decreased gradually over time ($p \leq 0.05$), ranging between 3.57–3.64 and 3.54–3.67 for samples fermented at 30 °C and 37 °C, respectively. One of the metabolites associated with functional and nutritive characteristics of fermented beverages—lactic acid—was determined. In Figure 6a,b ($p \leq 0.05$), the values for all beverages after the storage time are shown. After 14 days of refrigerated storage, the acidity values increased ($p \leq 0.05$) in all beverages, except for the SBP beverage with $1\%$ inulin fermented at 37 °C, which showed a lower increase in this parameter in the time of storage. During the period of storage, the WHC was higher for the beverages fermented at 30 °C and 37 °C (Figure 7a,b). Regardless of the inulin, the WHC increased with the increase in inulin concentration. As shown in Figure 7, the WHC of SBS and SBP fermented at 30 °C and 37 °C, respectively, with $3\%$ inulin, was significantly higher than that of other groups ($p \leq 0.05$). SBP beverage with $3\%$ inulin fermented at 37 °C had the largest water-retention capacity, while the WHC of SBS was only $71.96\%$, which was the weakest. ## 3.3. Sensory Evaluation The sensory analysis results are shown in Table 3. Significant differences were observed between all beverages ($p \leq 0.05$). The SBS and SBP samples with the highest content of inulin ($3\%$) fermented at 37 °C had a more intense color and were, therefore, better scored by the panelists. Regardless of the attributes of flavor and taste, there are no significant differences ($p \leq 0.05$) within samples (fermented at both temperatures) supplemented with inulin. Formulation SBP ($3\%$ inulin, fermented at 37 °C) (Table 3) had the highest values for flavor, taste, and overall acceptability attributes, differing significantly from the others ($p \leq 0.05$). ## 4. Discussion The beneficial effects of prebiotics and probiotics in diets have been and still are under exploration. Results provided from a limited number of contradictory studies create difficulties in developing a general recommendation for obtaining a novel functional beverage. Nazir et al. [ 30] declared that science-based demonstrations are necessary to validate health claims and successfully market new functional beverages. This study examined the possibility of producing a symbiotic beverage based on soy milk with sea buckthorn syrup or sea buckthorn powder supplemented with inulin and fermented with the Lactobacillus casei ssp. paracasei strain. Studies that have examined the effects of multiple prebiotics on food consumption, such as inulin, oligosaccharides, fructooligosaccharides, and soy milk, sea buckthorn syrup, or sea buckthorn powder fermented with lactic acid bacteria, showed inconsistent results. From what we know, it appears that there are no studies available reporting on the symbiotic beverages based on soymilk, sea buckthorn syrup, or sea buckthorn powder and inulin; in this regard, it proves to be a difficult task to compare our results with those reported for other beverages because of the differences in the used experimental conditions, food matrix, studied microorganisms, and the used analytical and instrumental methods and apparatus. The cell viability of L. casei® 431 was not affected by either the time, concentration, or temperature. However, at the 6th h of fermentation, its number increased, and the results indicated that there was competition for the nutrients. The increase in cell numbers was higher at 37 °C for the SBP beverage with $3\%$ inulin, compared to 30 °C and 37 °C, for the SBS beverage with 1 and $3\%$ inulin. As shown in Figure 1a,b supplementation with different amounts of inulin in the beverage affects the growth of L. casei ® 431; the cell numbers in the samples increased with the amount of inulin. During storage, the cell numbers of L. casei ® 431 slightly increased and remained at 1.4·108 and 1.9·108 CFU mL−1 for the SBP beverage with $3\%$ inulin fermented at 30 °C and 37 °C, respectively (Figure 4a,b). Generally, during storage, cell numbers of L. casei ® 431 increased slightly for all beverages at both temperatures of fermentation. Analysis of variance for the probiotic counts showed that supplementation with different amounts of inulin in the beverage affected the growth of L. casei ® 431; the cell numbers in the samples increased with the amount of inulin both during fermentation and the storage period. The recommended level of viable probiotic cells at the time of food consumption is 107–108 CFU·mL−1; after 14 days of storage at 4 °C [31], our viable cells of L. casei ® 431 remained at the level mentioned. No less than a million viable cells/mL of the probiotic product are needed to reach the minimum amount of health benefits for consumers, as [32] mentions. Our results demonstrate that the L. casei ® 431 culture strain can be used as a probiotic for obtaining symbiotic beverages based on soymilk, sea buckthorn syrup, or sea buckthorn powder and inulin. In conclusion, we can declare that it is very important to test the compatibility between probiotics and prebiotics to provide a positive interaction capable of increasing microbial viability during the fermentation and storage period. We can also confirm the use of good preparation practices because no microbial contaminants were detected in the symbiotic beverages during the storage period. The pH values of all samples decreased from the initial pH after 6 h of fermentation and showed nearly the same final pH. The decrease in pH was possibly due to the accumulation of lactic acid. It should be mentioned that fermented products based on soy milk are dependent on pH because it influences the stability, aroma, flavor, and texture of the final product. The product becomes too acidic, and the soybean proteins precipitate when pH < 4.0. Behrens et al. [ 33] declared that at a pH above 4.5, the flavor of the product is conserved. The improvement in the sensory quality of soymilk is obtained by the masking of volatile soybean compounds (n-hexanal and pentanal) by the fermentation products, especially compounds such as lactic acid, diacetyl, and acetaldehyde [33]. Likewise, for symbiotic beverage production, it is very important to have enhanced acid production during fermentation because it depends upon the growth, viability, and ability of L. casei to ferment the milk carbohydrates [34]. In conclusion, the pH of the beverages must be stabilized at higher values. The reduction in pH may be due to the release of organic acids following the post-acidification phenomenon, a phenomenon attributed to the fermentation of probiotics during refrigeration. The post-acidification phenomenon, thus, affects the viability of the starter culture [35]. However, Filannino et al. [ 36] suggest that the main advantage of the decrease in pH due to the accumulation of lactic acid during the fermentation period is better shelf-life preservation of the food. Additionally, the absence of coliform and mold counts during microbiological quality control may be correlated with the phenomenon of accumulation of lactic acid during the fermentation period. Our results agree with the results reported by Narvhus et al. [ 37]. They used lactococcal fermentation to obtain fermented milk at 22, 30, and 37 °C. After the fermentation, they observed that the products incubated at a temperature of 37 °C had a faster decrease in pH at the beginning of the fermentation period, but at the end of fermentation, the products incubated at 30 °C, as well as those incubated at 37 °C, had the same final pH [37]. The titratable acidity increased with the decrease in pH for all symbiotic beverages during fermentation for both temperatures. The SBS beverages had a higher value of titratable acidity compared with SBP during the fermentation and storage period. These differences could be assigned to the presence of $3\%$ more solids of nonlipid origin (sea buckthorn powder) in the SBP beverages. Additionally, the titratable acidity increased with the decrease in pH during fermentation for both temperatures and for all beverages. Likewise, Gardner et al. [ 38] reported using mono and mixed cultures of lactic bacteria to obtain fermented vegetable juice. The amount of lactic acid varied in the range of 0.3 g·mL−1 to 1.5 g·mL−1 [24]. Guzel–Seydim et al. [ 39] mentioned that the acidity of fermented beverages is commonly maintained or decreased during the storage period. This fact is attributed to microbial proteolysis. Costa dos Santos et al. [ 40] stated that the phenomenon of microbial proteolysis is a continuous fermentation process during which the lactic acid bacteria assimilate the lactate present in the environment. Electrical conductivity is an important parameter for evaluating the quality of any juice because it gives an idea of the freshness of the product. Moreover, electrical conductivity is influenced by the pH of the solution, the valence of the ions, and the degree of ionization. The values obtained in our study for electrical conductivity might be related to the components or vitamins released from sea buckthorn or inulin. Similar remarks were made by Boubezari et al. [ 41] for a probiotic juice based on carrots and L. plantarum J12. The sea buckthorn powder significantly influenced the rheological parameters of the symbiotic beverage, which may be related to changes in the microstructure (e.g., inulin crystallization, gel formation) caused by the addition of inulin. The consistency index (k) was influenced by different formulations. However, the addition of inulin increased this index, and the association of inulin and SBP influenced the consistency index ($p \leq 0.05$). These results suggest that the combination of inulin with SBP had a synergistic effect, changing the beverage’s consistency. Similar studies evaluating the effect of inulin on the rheological parameters were reported by [42], which declared that viscosity was influenced by inulin. Additionally, observed differences in viscosity between samples with inulin and samples without were mentioned in [43]. The WHC values obtained on the first day of sampling were lower than those found during storage and significantly increased with increasing inulin concentrations. Our results agree with the results reported in [44]. In contrast, Lin et al. [ 45] reported that during the storage period, for beverages based on L. chinense Miller juice, milk and soy milk were fermented with mixed cultures composed of the following strains: *Bifidobacterium longum* and Lactobacillus paracasei subsp. paracasei NTU101, no syneresis phenomenon was observed. Our results show that with the increase in inulin concentration percent, the viability of probiotic culture and acidity increased, while the water holding capacity and pH decreased for all symbiotic beverages. Regarding sensory analysis, due to the expanding influence of cultures from all over the world, Terpou et al. [ 46] declared that today, most consumers are much more open to tasting new flavor combinations, especially with ingredients that can confer beneficial effects in terms of health. The content of sea buckthorn powder and the presence of a probiotic and prebiotic in SBP samples could be the reasons for their greater acceptability than SBS beverages. Rinaldoni et al. [ 47] mentioned that ingredients such as inulin and protein concentrates are often used in the food and beverage industry to prepare food products, beverages, and desserts based on soy milk, not only to replace fats but also to provide special properties to the products (e.g., functional and nutritional properties). In this regard, the simultaneous addition of L. casei ® 431 and inulin improved the texture, color, and flavor of the symbiotic beverages. Considering the overall results of the sensory analysis, one can declare that the addition of inulin in beverages based on soy milk and sea buckthorn syrup or powder fermented with probiotic bacteria can improve the degree of acceptability of these symbiotic drinks. However, much more future study is needed that focuses on improving the taste and sensory acceptability of these types of beverages. The results obtained in the sensory evaluation indicate that inulin can improve the sensory attributes of the symbiotic beverage. We can also declare that inulin, together with soy milk, sea buckthorn, and probiotic culture, make our product a healthy beverage. Iraporda et al. [ 48] observed a satisfactory growth of L. paracasei BGP1 in the soy-based formula. Moreover, they reported that fermented soy-based beverages with inulin represent a good matrix for probiotic delivery. Fermented soy-based beverages with inulin are an alternative to traditional dairy probiotic beverages and contribute to diversifying this type of agri-based food products [48]. Research groups worldwide continue to explore fruit and vegetable juice matrices for new probiotic product development. For instance, [49] incorporated initial populations of L. acidophilus, L. rhamnosus, L. paracasei ssp. paracasei, Sacch. Boulardii, and B. lactis into a non-fermented vegetarian frozen soy dessert made with a soy beverage, sugar, oil, stabilizer, and salt [50] using a mix of two starters (S. thermophilus and L. delbrueckii subsp. bulgaricus) to inoculate either cows’ milk or soy beverage with either the probiotic bacteria L. rhamnosus, L. johnsonii, or human-derived bifidobacteria. Regardless of the substrate used, a major problem with using probiotics in fruit juices is their viability in an acidic medium, which could be solved by proliferation-promoting compounds such as inulin, which is projected in the context of symbiotic products [51]. From this point of view, it was a difficult task to compare our results with those reported for other beverages because of the differences in the experimental conditions, food matrix, and the microorganisms studied by us and the ones mentioned in the literature. ## 5. Conclusions Inulin was successfully incorporated as a prebiotic to produce a novel symbiotic beverage based on soymilk, sea buckthorn syrup or sea buckthorn powder, and inulin. SBP beverages had high survival rates during the 14 days of storage compared to SBS beverages. As a matter of fact, the achieved viabilities of the probiotic culture constantly surpassed the levels of the threshold (106–107 CFU·mL−1) that are needed to confer health benefits during the time of consumption of a probiotic beverage. Following the experiments, it can be concluded that inulin can be used to obtain a symbiotic product based on soy milk and sea buckthorn juice/powder fermented with L. casei ® 431, but the pH of the product must be stabilized at higher values. Moreover, the inulin added to the novel symbiotic beverage offered microbiological safety and excellent sensory attributes. Sea buckthorn powder and inulin in the symbiotic beverage not only satisfied the role of a functional ingredient, but the symbiotic beverages produced had a better mouthfeel. Finally, because the produced symbiotic beverages combine the health benefits of both prebiotic and probiotic characteristics, they show a high commercialization potential within the beverage industry. 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--- title: 'Anti-VEGF Treatment of Diabetic Macular Edema in Denmark: Incidence, Burden of Therapy, and Forecasting Analyses' authors: - Yousif Subhi - Ivan Potapenko - Javad Nouri Hajari - Morten la Cour journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10054899 doi: 10.3390/jpm13030546 license: CC BY 4.0 --- # Anti-VEGF Treatment of Diabetic Macular Edema in Denmark: Incidence, Burden of Therapy, and Forecasting Analyses ## Abstract Background: The aim of this study was to analyze demographically stratified incidence rates of patients with diabetic macular edema (DME) commenced in anti-VEGF therapy, to study temporal trends, to report the proportion of patients in active therapy over time, and to develop a model to forecast the future number of patients in active treatment. Methods: This was a retrospective registry-based study of all patients with DME who received at least one intravitreal anti-VEGF treatment from 1 January 2007 to 30 June 2022. Population data were extracted from Statistics Denmark. Results: This study included 2220 patients with DME who were commenced in anti-VEGF therapy. Demographic analyses revealed higher incidence rates among males than females and among those aged 60–80 years. The number of patients in active treatment followed an exponential decay curve; hence, this was used to mathematically model the number of patients in active therapy. The number of patients in active treatment is expected to stay relatively stable with a minimal increase until the year 2023. Conclusions: This study provides insight into the practical aspects of the anti-VEGF treatment of DME that allow the planning of adequate health services. ## 1. Introduction Diabetes is one of the most prevalent diseases with global estimates of 533.6 million individuals with diabetes [1]. This number is expected to increase, albeit with variating speed in different countries [1]. Diabetes leads to a range of complications throughout the body, including diabetic eye disease. Diabetic retinopathy and maculopathy are the cornerstones of diabetic eye disease and together brings diabetic eye disease to one of the leading causes of vision loss worldwide [2]. The retinopathy in diabetes is a consequence of a complex interplay between retinal ischemia, vascular changes, dysfunction of the inner blood–retina barrier, and expression of vascular endothelial growth factor (VEGF) [3,4,5]. These pathophysiological circumstances can eventually lead to a clinically observable macular edema [3,4,5]. Since diabetic maculopathy, or the more descriptive term diabetic macular edema (DME), predominantly affects the macula, clinically significant cases can impair vision and need treatment. Hence, DME is an important cause of visual impairment from diabetic eye disease. Treatment of DME can save or improve vision. Macular laser treatment for DME was practiced for many years in which focal laser photocoagulation was applied to reduce macular edema, halt the worsening of vision, and in some cases improve visual acuity [6]. The exact mechanism by which macular laser was effective remains to be fully elucidated [5], but its efficacy was superior to that of observation [5,6]. After the introduction of anti-VEGF therapy, pivotal large multicenter randomized controlled trials determined the superior efficacy of anti-VEGF against DME, and anti-VEGF treatment as first-line therapy has since been the cornerstone of DME management [7,8,9,10]. Intravitreal anti-VEGF therapy demands repeated injections over time. From a healthcare planning perspective, it is important to understand the number of injections over time in relation to patient burden to better plan adequate treatment facilities and services [11,12]. Unlike neovascular age-related macular degeneration (AMD), which requires continuing treatment for years for the majority of patients [13,14,15,16], in DME, studies report that the burden of anti-VEGF treatment is mainly in the first years of therapy [17,18,19,20,21]. This circumstance for DME presents an entirely different consideration than, e.g., neovascular AMD, in terms of the number of patients in active therapy when planning a large-scale, anti-VEGF therapy service for DME. In this study, we extracted a large dataset from one of Europe’s largest departments of ophthalmology and extracted corresponding population census data to better understand the incidence of patients with DME commenced in anti-VEGF therapy and to understand temporal trends and burden of therapy as the proportion of patients in active therapy over time and developed a model to forecast the future number of patients in active treatment. ## 2.1. Study Design This was a retrospective study of patients with DME in the Capital Region of Denmark (~1.9 million inhabitants). The Capital Region of *Denmark is* the most populous region of Denmark and includes the Danish capital Copenhagen. Patients included were those with DME who received anti-VEGF therapy from 1 January 2007 to 30 June 2022. This was a registry-based study. Study approval was obtained from the department, from the Danish Data Protection Agency (jr. no. FSEID-00006126), and from the Centre of Regional Development/Institutional Review Board (jr. no. R-20052134). All aspects of this study adhered to the tenets of the Declaration of Helsinki. Study data were extracted from the clinical database BOB that stores data on all patients in anti-VEGF treatment in the Capital Region of Denmark [22], including information on the retinal diagnosis and time of administration of anti-VEGF treatment. All population census data were extracted from Statistics Denmark [23], which is the statistical authority in Denmark. Statistics Denmark compiles data on population count, immigration and emigration trends, live births, and deaths. These data are provided to the Danish Institute for Economic Modelling and Forecasting (DREAM)—an independent, semi-governmental institution that provides forecasting analyses of the Danish society and economy [24]. Statistics Denmark then publishes the most likely model of the future forecast of the Danish population based on DREAM analyses [24]. ## 2.2. Clinical Pathway of Patients with Diabetic Macular Edema Public tax-based healthcare coverage allows all Danish citizens the right to access health services, free of charge. Access to specialized health care is managed through general practitioners. One of the few examples is the access to specialized eye care. Patients can book an appointment with a private ophthalmologist without the need for a referral from their general practitioner or other health care professional. For patients with diabetes, nationwide programs promote systematical examination of patients including relevant biochemistry at regular intervals, and patients are also seen by a range of specialists to screen for and treat complications, including regular retinal examinations. According to the Danish national guidelines [25], patients with diabetes are screened according to an individualized screening interval (Table 1). Screening of diabetic retinopathy and maculopathy is based on fundus photography and optical coherence tomography (OCT) upon suspicion of maculopathy. In Denmark, only selective public hospital departments, and no private hospitals, can provide on-label anti-VEGF treatments as outlined by the national health law. A few clinics provide off-label anti-VEGF (i.e., bevacizumab) treatments for a few patients for various reasons. Thus, almost all patients in need of anti-VEGF treatment are referred to one of these public hospital departments for evaluation and commencement of anti-VEGF treatment. In the Capital Region of Denmark, all referrals are made to the Department of Ophthalmology, Rigshospitalet, and thus registered in the BOB database if the retinal specialist commences anti-VEGF treatment. This unique organization in a single center with high expertise allows a combination of high compliance to ophthalmic therapy in patients who are otherwise low compliance to therapy and the possibility to conduct large-scale epidemiological studies of disease epidemiology and treatment burden [12]. ## 2.3. Treatment Commencement, Regimen, and Discontinuation All patients had best-corrected visual acuity (BCVA) measured with Snellen chart, slit-lamp biomicroscopy, dilated retinal examination, and macular OCT. Macular OCT was made using Topcon Triton swept-source OCT (Topcon Corporation, Tokyo, Japan) or Heidelberg Spectralis spectral-domain OCT (Heidelberg Engineering, Heidelberg, Germany). Fluorescein angiography was performed in select cases of uncertainty on the source of macular edema. Treatment was commenced according to the local department guidelines, which indicates that anti-VEGF treatment is commenced with 1–3 injections depending on the severity of the DME. Patients are re-evaluated 1–2 months after their last anti-VEGF injection, and re-treatment is commenced depending on the presence of macular edema. If the macular edema is resolved, the patient is seen at 2–4 months intervals at the physician’s discretion. According to national guidelines, Ranibizumab (Novartis, Basel, Switzerland) was the first choice of treatment until 2013, and Aflibercept (Bayer, Leverkusen, Germany) was the first choice of treatment from 2014 and onwards. Patients could be changed from Aflibercept to Ranibizumab and vice-versa upon lack of treatment response evaluated at the physician’s discretion. Lack of treatment response on anti-VEGF would lead to discontinuation of anti-VEGF therapy and initiation of local photocoagulation therapy and/or intravitreal dexamethasone therapy at the physician’s discretion. For proliferative diabetic retinopathy, panretinal photocoagulation was the first choice, and cases could be commenced in anti-VEGF therapy or vitrectomy on a case-by-case basis, where panretinal photocoagulation treatment was insufficient in obtaining disease control. Patients with proliferative diabetic retinopathy treated with anti-VEGF therapy without the presence of any DME were not included in this study. Upon complete resolution of anti-VEGF treatment without the need for treatment for 6–12 months, cases were discontinued for follow-ups at national retinal screening sites or at private ophthalmologists every 3–4 months for the rest of their life. Treatment was also discontinued in cases with a lack of treatment response despite anti-VEGF or other treatments and where BCVA ≤ 0.05 Snellen. ## 2.4. Data Analysis and Statistics Patients were included in our data if they had received at least one anti-VEGF injection. All patients were only included once, regardless of one or both eyes were treated. All statistical analyses were made in Python v. 3.11. For curve fitting, we employed the Levenberg–Marquardt algorithm in the SciPy package v.1.10.0. The incidence of patients with DME in anti-VEGF treatment was calculated as the ratio between the number of patients receiving their first anti-VEGF injection (in either eye) and the population number in the Capital Region of Denmark. This incidence was also calculated using the appropriate age- and sex-stratified patient data and census data. The number of patients in active therapy followed an exponential decay curve irrespective of the time of treatment commencement. Thus, we used this observation to mathematically express the numbers as a∙e−k·t in which a and k are parameters fitted using historical data. Based on this, a mathematical model was created to express the number of actively treated patients by only using the two fitted parameters and the number of new patients in any year:[1]A(T)=∑$t = 1$Tn(t)·e−k·(T−t) which allowed us to express the number of actively treated patients (A) by only using the two fitted parameters and the number of new patients (n) in any year (T). This model allows prediction of the future number of patients when also using data on predicted population data and age-stratified incidence of patients with DME in anti-VEGF treatment. This model assumes neither temporal changes in the indication nor efficacy of the given treatment. This mathematical approach is previously described in detail by Potapenko and la Cour [12]. ## 3.1. Number of Patients and Temporal Trends During the study period, 2220 patients with DME were commenced in anti-VEGF therapy and 1953 patients were later discontinued from anti-VEGF therapy. We saw a gradual increase in the number of patients commenced in anti-VEGF treatment until the year 2019. Discontinuation of patients from anti-VEGF therapy also increased gradually. From the year 2020 and onwards, due to the COVID-19 epidemics and its impact on referral and discontinuation patterns, we observed a shift towards a lower number of new patients and an increasing discontinuation. Temporal trends of patients with DME in anti-VEGF therapy are illustrated in Figure 1. ## 3.2. Population Incidence of Patients with Diabetic Macular Edema Commenced in Anti-VEGF Therapy The annual incidence of DME commenced in the Capital Region of Denmark in 2012–2021 was on average 193 individuals, which is equivalent to 10.7 per 100.000 inhabitants annually. Age- and sex-stratified incidence rates are presented in Table 2. The incidence of DME was higher in males than females and peaked among individuals aged 60–80 years. Using age- and sex-stratified population forecasts for the number of individuals in the Capital Region of Denmark, we extrapolated the number of patients with DME commenced in anti-VEGF therapy until the year 2035 (Figure 2). Based on these analyses, we expect an annual incidence rate of ~160–175 individuals with a minimal increase over time. ## 3.3. Proportion in Active Anti-VEGF Treatment over Time The proportion of patients with DME in active anti-VEGF treatment was $61.1\%$ after year 1, $48.2\%$ after year 2, $36.9\%$ after year 3, $31.2\%$ after year 4, $25.1\%$ after year 5, and $10.2\%$ after year 8 (Figure 3). These observations substantiate two important messages. First, approximately half of all patients remain in anti-VEGF therapy for 2 years. Second, the number of patients in active treatment exhibited a pattern of decrease relative to its previous value, i.e., an exponential decay. An exponential decay can be mathematically expressed using f(t) = a∙e−k·t, which in this case can be modelled to $a = 0.601$, $k = 0.217$, and t = time from commencement of anti-VEGF therapy (Figure 3). The model had a high goodness of fit at R2 = 0.81. According to our model, we expect that only $60.1\%$ will remain in therapy after the first year and that the number of patients in active treatment will decrease by $21.7\%$ for each following year. ## 3.4. Modelling the Future Number of Patients with Diabetic Macular Edema in Anti-VEGF Treatment Based on the historical data, our model and population forecasts, we extrapolated the number of patients in active anti-VEGF therapy (Figure 4). We estimate stability in the number of patients in active anti-VEGF therapy with very small expected growth, at least until the year 2035. Our analyses exclude historical data for 2020 and 2021 from the model due to the COVID-19 epidemics and its impact on referral and discontinuation patterns; thus, these numbers assume a return to pre-COVID-19 state of normality. ## 4. Discussion This study allows insight into important aspects of the trends in anti-VEGF therapy of DME in the Capital Region of Denmark. In the years 2007–2011, we observed an adaptation trend with an increasing number of patients referred for therapy. The following years had a stable number of new patients. The discontinuation trend exhibited an almost delayed pattern in comparison to that of new patients, which reflects the fact that a large number of patients were discontinued from therapy after a few years. The increase in discontinuation of therapy in 2021–2022 should be interpreted with caution, since this period is also affected by various circumstances related to the COVID-19 epidemics. Analysis of patient demographics showed that the incidence of DME commenced in anti-VEGF therapy was higher in males than females and that the incidence peaked in the age range of 60–80 years. These findings are in line with epidemiological reports of DME [26]. For patients in active treatment, we observed that in a period of stability (i.e., after the adaptation stage and prior to the COVID-19 epidemics), there is an interesting phenomenon of stability in the number of patients with DME in active therapy while the patient population itself is subject to a continuous change. This pattern is observed for the years 2015–2019 in Figure 2 and Figure 3, as well as the forecasts in Figure 3. When planning an anti-VEGF therapy for patients with DME, our observations indicate that efforts need not be made into expanding the future number of injection rooms or personnel, but instead on patient education and circumstances around the intake of new patients and efforts regarding discontinuation, which include information regarding the condition from a tertiary specialized healthcare organization to a primary healthcare unit for future screening and observation. The importance of this cannot be overstated; in patients with retinal diseases, those with DME rank poorest in health literacy [27]. The DRCR Retina Network Protocol T Extension Study reported treatment and clinical outcomes at 5 years after the commencement of anti-VEGF therapy [18]. This was an extension study to the original Protocol T study, which randomized and compared the efficacy of aflibercept, bevacizumab, or ranibizumab [17]. The extension study of 317 patients with DME found that after the first 2 years, only a minority were in need of further anti-VEGF injections [18]. Large real-life studies with long-term outcome data (≥5 years) of treatment burden are limited. The VISION study reported real-world treatment patterns for eyes with DME treated with anti-VEGF for at least 3 years [19]. This multicenter study of nine Belgian clinics reported long-term efficacy for 55 patients with DME [19]. Here, the median number of injections for all patients was 5.0 in the first year, which fell to 3.0, 1.0, 0.0, and 0.0 in the 2nd, 3rd, 4th, and 5th years, respectively [19]. Zirpel et al. reported Swiss long-term outcome data for 191 patients with DME and found that number of injections fell dramatically after the first year, and that loss to long-term follow-up was mainly due to discontinuation and referral back to the private ophthalmologist for screening and observation [20]. A multicenter retrospective study of 12 institutions in Latin America and Spain included 201 patients with DME for a study of 5-year outcomes after anti-VEGF therapy [21]. This study reported a gradual decline in the mean number of injections per year at 3.3, 2.1, 1.5, 1.3, and 1.2 for 1st, 2nd, 3rd, 4th, and 5th years, respectively [21], which from our point of view also exhibits an exponential decay pattern. Interestingly, many such studies report the number of injections for the entire population, but not the number of patients in active treatment, which only gives partial insight into the actual burden of treatment. In our study of 2220 patients with DME with follow-up data for up to 14 years, we are able to confirm the notions of other real-life studies on a larger scale. The limitations of this study should be kept in mind. First, this was a retrospective database study of routine patients with DME commenced in anti-VEGF therapy, and therefore, data did not include patients with DME who did not have CSME, patients with DME who did not want anti-VEGF therapy for any reason, or were ineligible for anti-VEGF therapy for any reason. This means that our incidence data will underestimate the total number of patients with DME. Second, some of the analyses exclude data from 2020 and 2021 due to the COVID-19 epidemics, and we forecast future numbers under the assumption that we at some point will return to a pre-COVID-19 state of normality. Only time can tell if that is true. Third, our population forecasts rely on the accuracy of calculation from Statistics Denmark, which is based on a range of assumptions, which are best guesses—not facts. Fourth, the recent approval of brolucizumab and faricimab has introduced new anti-VEGF drugs for which long-term real-life data for DME do not exist. Thus, there is also the uncertainty of whether the pattern of decay of those in treatment will remain the same. Finally, the incidence of diabetic retinopathy or DME is correlated to blood glucose control. In the Capital Region of Denmark, the Steno Diabetes Center organization, which is a specialized diabetes hospital that works as an integrated part of the public healthcare system, has been acknowledged for its contribution to improved blood glucose control and a low rate of microvascular complications [28,29,30]. Populations with different levels of blood glucose control may experience different incidence rates of DME. A difference in blood glucose control may also play a role in the long-term need for anti-VEGF therapy. These circumstances should be considered as a limitation in the generalizability of our results to other populations. In conclusion, we here report the incidence of patients with DME commenced in anti-VEGF therapy and present temporal trends. We confirm the findings of previous studies that the burden of treatment is mostly within the first couple of years. 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--- title: Nobiletin Intake Attenuates Hepatic Lipid Profiling and Oxidative Stress in HFD-Induced Nonalcoholic-Fatty-Liver-Disease Mice authors: - Zunli Ke - Chaowen Fan - Jun Li - La Wang - Haiyang Li - Weiyi Tian - Qi Yu journal: Molecules year: 2023 pmcid: PMC10054910 doi: 10.3390/molecules28062570 license: CC BY 4.0 --- # Nobiletin Intake Attenuates Hepatic Lipid Profiling and Oxidative Stress in HFD-Induced Nonalcoholic-Fatty-Liver-Disease Mice ## Abstracts Nobiletin (NOB) is a naturally occurring compound, commonly found in citrus peel, that shows hepatoprotective and lipid-reducing effects. However, the lipid biomarkers and the potential improvement mechanisms have not been adequately explored. Therefore, we investigated the ameliorative effect and the molecular mechanism of NOB on NAFLD induced by a high-fat diet in mice. The results showed that supplementation with NOB over 12 weeks markedly improved glucose tolerance, serum lipid profiles, inflammatory factors, hepatic steatosis, and oxidative stress. These beneficial effects were mainly related to reduced levels of potential lipid biomarkers including free fatty acids, diacylglycerols, triacylglycerols, and cholesteryl esters according to hepatic lipidomic analysis. Twenty lipids, including DGs and phosphatidylcholines, were identified as potential lipid biomarkers. Furthermore, RT-qPCR and Western blot analysis indicated that NOB inhibited the expression of lipogenesis-related factors such as SREBP-1c, SCD-1, and FAS, and upregulated the expression of lipid oxidation (PPARα) and cholesterol conversion (LXRα, CYP7A1, and CYP27A1) genes as well as antioxidation-related factors (Nucl-Nrf2, NQO1, HO-1, and GCLC), indicating that NOB intake may reduce lipid biosynthesis and increase lipid consumption to improve hepatic steatosis and oxidative stress. This study is beneficial for understanding the ameliorative effects of NOB on NAFLD. ## 1. Introduction Polymethoxylated flavones (PMFs) are a subgroup of plant flavonoids that occur mainly in citrus fruits (Citrus L. Rutaceae), especially in the citrus peels. PMFs are of interest for their various biological activities, such as their anti-oxidative, anti-inflammatory, and anti-cancer properties [1]. Nobiletin (5,6,7,8,3′,4′-hexamethoxyflavone, NOB) is one of the main PMFs in citrus peel, and it exhibits a potent regulation of lipid accumulation, antidiabetic activity, hepatoprotective activity, anti-inflammatory activity, antioxidant activity, and so on [2,3]. The literature reports that NOB showed benefits for dyslipidemia in both C57BL/6 and LDL receptor-deficient (Ldlr-/-) mice fed a high-fat diet (HFD) [4,5]. NOB increased the gene expression of PPARα co-activator 1α (Pgc1α) in the liver, leading to an increase in fatty acid (FA) oxidation [4]. Furthermore, NOB downregulated the expression of hepatic sterol regulatory element-binding protein-1c (Srebp-1c) in a high-glucose-induced HepG2 cells model [6]. These regulating actions might account for the beneficial activity of NOB in attenuating hepatic triglyceride (TG) deposition and improving metabolic disorder. Although the beneficial regulation of NOB on hyperlipemia and lipid metabolism has been reported in studies using lipidomics to explore the efficacy of NOB, the lipid biomarkers responsible for the bioactivities of NOB and the amelioration of hepatic oxidative stress in a non-alcoholic fatty liver disease (NAFLD) mouse model are rare. NAFLD is a manifestation of hepatic metabolic syndrome. It is always characterized as “simple” steatosis (fatty liver) with a potentially progressive inflammatory phenotype of nonalcoholic steatohepatitis (NASH) that can progress to cirrhosis and/or hepatocellular cancer [7]. It affects approximately a quarter of the population worldwide, and its prevalence continues to increase in the context of the growing obesity epidemic, especially in western countries [8]. In China, the prevalence of NAFLD has increased significantly from 18 to $29\%$ within a decade. It is predicted that China will soon have the highest growth in the prevalence of NAFLD [9]. The prevalence of NAFLD can reach 90–$95\%$ in obese individuals and affects up to $70\%$ of patients with type 2 diabetes [10]. In addition, patients with NAFLD are at higher risk of cardiovascular diseases. Because there are no licensed therapies, NAFLD is predicted to become the most common indication leading to liver transplantation [11]. Therefore, approved therapeutic strategies for this disease are urgently warranted. NAFLD is characterized by the excessive deposition of lipids in hepatocytes, and this occurs concurrently with increased lipotoxicity from high levels of free fatty acids (FFA), free cholesterol (TC), and other lipid metabolites, which could lead to mitochondrial dysfunction with oxidative stress and generation of excessive reactive oxygen species (ROS) [12]. Oxidative stress is regarded as a main inducer in the pathophysiology of inflammatory chronic liver diseases, including NAFLD. Chronic lipid disturbance is strongly associated with impairment of the balance between oxidants and antioxidants, which affect metabolism-related organelles, leading to cellular lipotoxicity, mitochondrial dysfunction, and lipid peroxidation [13,14]. Increased oxidative stress also activates hepatocyte stress pathways, leading to inflammation and causing the progression of NASH. The nuclear factor-E 2-related factor-2 (Nrf2) pathway is a pivotal component to protect against oxidative-stress-induced injury by upregulating its target factors such as heme oxygenase 1 (Ho-1), glutamate cysteine ligase catalytic subunit (Gclc), NAD(P)H:quinone oxidoreductase (Nqo1), and glutathione S-transferase A2 (Gsta2), contributing to the restoration of normal lipid metabolism. Thus, alleviating hepatic oxidative stress by the Nrf2 pathway emerges as an effective therapy to improve NAFLD development and progression [13]. Lipidomics is an effective and sensitive strategy that is capable of exploring biological responses by investigating lipid composition and identifying lipid biomarkers at a molecular level [15,16]. Currently, lipidomic analysis has been applied to evaluate the beneficial effects of natural compounds [17,18,19]. For example, lipidomic analysis revealed that tangeretin intake showed cholesterol-lowering effects and this function was related to lowering the levels of FFA, diacylglycerols (DGs), TGs, ceramides (Cers), and cholesteryl esters (CEs) [18]. Moreover, lipidomic analysis showed that the lipid-lowering effects of arabinoxylan, that had been attributed to the decreasing levels of some FFA, 12α-hydroxylated bile acids, and carnitines (CARs) on type 2 diabetic rats, were in fact due to an increase in lysophosphatidylcholine (LPC) levels. In addition, the underlying molecular mechanism of the beneficial effects of dietary ω-3 polyunsaturated fatty acids was also investigated by lipidomic analysis [20]. Based on the aforementioned studies, lipidomics has become an important tool of mechanistic exploration in nutrition and medicinal research. In this work, we hypothesize that NOB has beneficial effects on hepatic lipid metabolism and oxidative stress as well as the associated metabolic dysfunction in NAFLD mice. Therefore, we combined biochemical and lipidomic analysis to investigate the effect and the underlying mechanisms of the regulation of lipid metabolism and oxidative stress after supplementing with NOB in a HFD-induced NAFLD mouse model. ## 2.1. Effects of NOB on Body Weight Gain, Food Intake, and GTT in HFD-Induced NAFLD Mice HFD-fed mice exhibited a significantly higher body weight gain when compared to the Chow group mice, but a dietary supplementation of $0.1\%$NOB (LNOB) and $0.2\%$NOB (HNOB) could reduce the body weight gain. HNOB significantly inhibited the body weight gain induced by a high-fat diet (Figure 1A). It was also found that daily NOB supplementation showed no significant change in food intake when compared with the HF-diet group (Figure 1B). A long-term HFD is associated with obesity, dyslipidemia, and glucose intolerance. As shown in Figure 1C, the FBG in the HFD group mice was higher than that in the Chow group, while a 12-week dietary supplementation with NOB decreased the FBG and the HNOB group mice showed a significant reduction. During the GTT, HNOB group mice had lower glucose levels at 15 min, 60 min, and 90 min. In addition, the HNOB-supplementation group also showed significantly lower AUC values when compared with the HFD group. However, the LNOB-supplementation mice only showed a lower glucose level at 15 min (Figure 1C). In summary, dietary supplementation with NOB alleviated abnormal glucose levels caused by HFD feeding. ## 2.2. Effect of Dietary NOB on Serum Biochemistry in HFD-Induced NAFLD Mice As shown in Figure 1D, E, the HFD group mice had obviously higher ALT and AST levels, indicating the induction of liver injury by the HFD. HNOB supplementation decreased the AST level but not the ALT level, after 12 weeks of feeding. Moreover, Figure 1F–I show that the HFD group mice had dyslipidemia, which was characterized by the increasing serum TC, TG, and LDL-C levels when compared with the Chow group mice. Interestingly, dietary supplementation with NOB significantly reduced serum TG and TC levels but did not affect the serum LDL-C and HDL-C levels. NAFLD is always accompanied by inflammation. Therefore, we analyzed the inflammatory factors in serum. As shown in Figure 1J–L, the serum IL-1β, IL-6, and TNF-α concentrations were significantly increased in HFD group mice (compared with the Chow group). However, NOB supplementation for 12 weeks obviously reduced the serum levels of IL-1β, IL-6, and TNF-α. ## 2.3. Effect of NOB Supplementation on Hepatic Lipid Accumulation in HFD-Induced NAFLD Mice As shown in Figure 2A, the HFD group mice showed moderate to obvious macrovesicular steatosis shown by hepatic H&E staining, when compared with the Chow group, whereas NOB administration improved hepatocyte steatosis. In addition, the ORO staining also showed an excessive lipid droplet accumulation in the livers of HFD group mice in contrast to the Chow group, and NOB intake decreased the size of these lipid droplets (Figure 2A). Figure 2B shows that the HFD caused higher NAS (compared with that of the Chow group), while both LNOB and HNOB group mice demonstrated lower NAS (compared with that of the HFD group). Overall, the histological investigation found that excessive lipid deposition and the degree of liver steatosis were both improved by NOB supplementation. Mice in the HFD group also showed significantly higher TG and TC contents in the liver (compared with the Chow group), indicating obvious hepatic lipid deposition. Expectedly, TG and TC levels were significantly reduced (compared with the HFD group) in the LNOB and HNOB groups (Figure 2C,D). Taken together, these results provided evidence that NOB treatment might reduce lipid accumulation in the liver induced by a HFD, thereby exerting an ameliorative effect on hepatic steatosis. ## 2.4. Effect of NOB Supplementation on Hepatic Oxidative Damage in HFD-Induced NAFLD Mice Excessive hepatic lipid accumulation leads to hepatic oxidative damage. As shown in Figure 2E–G, HFD mice exhibited a lower content of the antioxidant substances SOD and glutathione (GSH), and a higher content of peroxidation products MDA when compared with the Chow group. In contrast, NOB administration improved the hepatic antioxidant capacity of mice including elevating the GSH concentration and reducing the MDA concentration. These results indicated that NOB treatment might ameliorate the oxidative injury of the liver caused by HFD feeding. ## 2.5. Lipidomic Analysis after NOB Supplementation In order to explore the effect of NOB on hepatic lipid biomarkers, the species-level analyses of lipids from Chow, HFD, LNOB, and HNOB groups were analyzed according to the lipidomic approach. A total of 1276 lipid metabolites were identified from the four group of mice, including 17 eicosanoids, 39 FFAs, 280 TGs, 101 DGs, 12 phosphatidic acid (PAs), 107 phosphatidylcholines (PCs), 29 etherphosphatidylcholines (PC-Os), 84 phosphatidylethanolamines (PEs), 78 etherphosphatidylethanolamines (PE-Os), 57 phosphatidylethanolamine-based plasmalogens (PE-Ps), 32 phosphatidylglycerols (PGs), 43 phosphatidylinositols (PIs), 51 carnitines (CARs), 14 cholesteryl esters (CEs), 40 ceramides (Cers), 3 coenzyme Qs (CoQs), and others. As shown in Figure 3A,B, the total contents of TG, DG, FFA, CoQ, and CE in the HFD group were obviously higher, whereas the total contents of PC, PC-O, PE-P, PG, PA, and PE-O were significantly lower when compared with Chow group mice. However, the contents of these lipids were significantly reversed after NOB administration (compared with HFD group). On the basis of these results, consumption of $0.1\%$ and $0.2\%$ NOB could effectively ameliorate the disorder of lipid metabolism caused by a HFD in mice. In addition, principal components analysis (PCA) was used to analyze the lipid composition among the four groups. From Figure 3C, it is evident that the HFD group is distinctly separated from the Chow group. As expected, the NOB supplementation groups, especially the HNOB group, are separated away from the HFD group and close to the Chow group, implying that the NOB supplementation might ameliorate the disturbances of lipid metabolisms toward the normal condition. ## 2.6. NOB Supplementation Changed the Important Differential Lipid Species in The Liver To obtain a better understanding of the separation between different groups, orthogonal partial least squares discriminant analysis (OPLS-DA) was conducted to estimate the alterations in global lipids. Three separate multivariate OPLS-DA models (HFD group vs. Chow group, LNOB group vs. HFD group, and HNOB group vs. HFD group) were generated. From Figure 4A–C, we observed an obvious separation of the OPLS-DA score plot shown in the Chow vs. HFD, HFD vs. LNOB, and HFD vs. HNOB, respectively, indicating that lipid metabolic disorders were induced by HFD feeding and improved by NOB supplementation. Volcano plot analysis was employed to identify lipid biomarker candidates accounting for this distinction using the following criteria: FC (Fold change) ≥ 2 or ≤ 0.5 and variable importance in the projection (VIP) ≥ 1, $p \leq 0.05.$ As illustrated in Figure 4D, 428 differentially regulated lipid species were screened out in the Chow group vs. the HFD group model. Among the 428 identified lipids, the levels of 302 lipid species were observably elevated and 126 lipid species were significantly reduced. Notably, 427 lipids were obviously different between HFD and LNOB groups and 449 lipids were obviously different between the HFD and HNOB groups as shown in Figure 4E,F, respectively, and most of them were remarkably downregulated. Taken together, these findings revealed that NOB supplementation can effectively improve the disturbance in lipid metabolism induced by a HFD. Furthermore, the differences in the levels of the possible lipid biomarkers among four groups are shown in Figure 4G–I using the following criteria (VIP > 1, fold change ≥ 2 or ≤ 0.5, $p \leq 0.5$). These significantly changed lipid species including 2 DGs, 4 FFAs, 2 PE-Os, 3 PE-Ps, 2 CEs, 2PCs, and 5 TGs were screened out from the Chow, HFD, LNOB, and HNOB groups. As illustrated in Figure 4G–I, the levels of DG (14:0_18:2), DG (17:1_18:2), FFA (17:0), FFA (20:3), FFA (22:4), FFA (22:5), CE (16:0), CE (17:1), PE (O-18:2_20:4), PE(O-20:3_20:4), PE (P-18:0_22:3), PE (P-16:0_20:1), PE (P-18:2_20:2), PC (24:0_18:1), PC (14:0_18:2), TG (16:0_18:0_18:2), TG (16:0_16:1_18:2), TG (16:0_18:1_18:2), TG (16:0_18:2_18:2), and TG (16:1_18:2_18:2) were markedly changed in the HFD group (compared with the Chow group), implying that HFD feeding led to a significant change in the lipid profile. In contrast, the levels of these lipids were improved after 12 weeks of NOB supplementation. Therefore, the results imply that these lipid markers might be considered as potential biomarkers responsible for the amelioration effects of NOB on fatty liver induced by a HFD. ## 2.7. Pathway Analysis Pathway enrichment analysis was carried out to investigate the most relevant metabolic pathways associated with lipid metabolism. As exhibited in Figure 5A, the mice fed with the HFD had a markedly affected vitamin digestion and absorption, thermogenesis, regulation of lipolysis in adipocytes, lipid and atherosclerosis, insulin resistance, glycerolipid metabolism (GL), fat digestion and absorption, and cholesterol metabolism when compared with the Chow group. However, LNOB and HNOB supplementation improved these changes (Figure 5B,C). These data suggest that NOB greatly improved lipid metabolism in NAFLD mice via these metabolic signaling pathways. ## 2.8. Effect of NOB Supplementation on the Expression of Genes and Proteins Involved in Hepatic Lipid Metabolism and Oxidative Stress In order to investigate the potential mechanism related to the amelioration by NOB of lipid metabolism and oxidative stress in the liver tissues, we further analyzed the expression of genes and proteins associated with lipid metabolism and oxidative stress. Figure 6A demonstrates that the lipid-metabolism-related genes including SREBP-1c, fatty acid synthases (Fas), Scd1, liver X receptor (Lxrα), peroxisome proliferator-activated receptor α (Pparα), cholesterol 7alpha-hydroxylase gene (Cyp7a1), and sterol 27-hydroxylase (Cyp27a1) were significantly disrupted in the HFD group mice (compared with Chow group), whereas the mRNA expression of Srebp-1c, Fas, and Scd1 in both NOB supplementation groups, and especially in the HNOB treatment group, was significantly lower. In addition, the levels of lipolysis gene Pparα were obviously increased (compared with HFD group) in the NOB group. Moreover, HNOB supplementation remarkably elevated (in comparison with the HFD group) the expression level of Lxrα, Cyp7a1, and Cyp27a1, which were involved in cholesterol metabolism. As shown in Figure 6B, supplementation of NOB significantly upregulated the expression of Nrf2 and its target genes, such as Ho-1, Nqo1, Gclc, and Gsta2, which are involved in protecting cells against oxidative stress. Furthermore, the protein levels of SCD-1, SREBP-1, Nrf2, GCLC, HO-1, and NQO1 were assessed by WB analysis. Similar to the results of the mRNA expression analysis, the HFD also elevated SCD-1 and SREBP-1 protein levels in comparison with the Chow group. In contrast, the elevated expression of these protein expressions was reduced by LNOB and HNOB supplementation (Figure 6C). Additionally, the Nucl-NRF2 protein level and those of its target proteins, such as GCLC, HO-1, and NQO1, were also significantly increased in both of the NOB-treated groups (Figure 6C). ## 3. Discussion Previous studies have reported that abnormal hepatic alterations in lipids are crucial pathophysiological hallmarks of NAFLD and higher levels of hepatic lipids lead to oxidative stress and overproduction of ROS [21]. Citrus PMFs are attracting increasing attention due to their beneficial efficacy in the improvement of metabolic syndrome and lipid metabolism [4,5,22,23]. Despite previous studies demonstrating the lipid-reducing effect of NOB [4,6], the mechanism of NOB regulation of lipid homeostasis remains inadequately studied. Therefore, in the present work, hepatic lipidomics, RT-qPCR, and WB were applied to provide new insights into lipid metabolism in NAFLD after NOB intervention. We found that NOB supplementation ameliorated the disturbances in blood glucose, serum lipids, inflammatory factors, hepatic lipid accumulation, steatosis, and oxidative stress in HFD-induced NAFLD mice. A previous study reported the lipid-lowering effect of NOB, but NOB had no effect on body weight [24]. However, we found that $0.2\%$NOB supplementation could inhibit body weight gain, which might be due to the fact that the dose of NOB in the present work was higher. The level of serum AST was significantly decreased and showed a recovery trend back toward the Chow group after $0.2\%$NOB supplementation, demonstrating that NOB has a good safety profile, which had been described in previous work [25]. In addition, $0.2\%$NOB supplementation exhibited an ameliorative effect on hepatic oxidative injury induced by the HFD. The literature also reports that NOB administration can improve glucose concentration and serum lipid levels, as well as inflammatory factors, in rats or mice fed a western diet [24,26]. Our data also show that NOB-supplemented groups of mice exhibited significantly lower serum TC, TG, IL-1β, IL-6, and TNF-α levels, which had been elevated by HFD feeding. Our results are consistent with these previous studies. In current work, we found that NOB intake could reduce hepatic TG and TC content and improve hepatic steatosis by lowering the expression of genes related to lipogenesis (Srebp-1c, Scd-1, and Fas) and increasing the expression of genes involved in lipid oxidation (Pparα). Moreover, the expression levels of SREBP-1c and SCD-1 proteins were also significantly reduced in NOB-treatment mice. Mulvihill et al. found that NOB prevented the hepatic lipid load in Ldlr-/- mice, mainly by enhancing the expression of peroxisome-proliferator-activated receptor gamma coactivator-1 alpha (Pgc-1α) and increased fatty acid β-oxidation [4]. In addition, NOB has been reported to inhibit lipogenesis via activation of the AMPK pathway in high-glucose-induced hepatic lipid accumulation in HepG2 cells [6]. These results imply that NOB could improve dyslipidemia and hepatic steatosis partly due to reduced hepatic lipid synthesis and increased lipid consumption. As we all know, oxidative stress is regarded as a main cause of the progression of NAFLD. Excessive hepatic lipid accumulation leads to an imbalance between oxidant and antioxidant systems, leading to excessive ROS generation, mitochondrial dysfunction, lipid peroxidation, and reduced antioxidant enzymes [13]. Therefore, ameliorating hepatic oxidative stress might improve NAFLD. Nrf2 is a key factor in counteracting oxidative-stress-induced damage, contributing to the restoration of normal lipid metabolism [27]. A previous report has shown that NOB supplementation enhanced SOD activity both in plasma and hepatic tissue, along with concurrent downregulated liver NADPH oxidase subunit gp91phox expression in HFD-fed rats [26]. In contrast, our research showed that NOB supplementation reduced the content of MDA and enhanced the activity of GSH by up-regulating the expression levels of antioxidant factors of NRF2 and its targeted factors HO-1, NQO1, and GSTA2 in the liver tissues, thereby ameliorating the hepatic oxidative stress induced by the HFD. To our knowledge, this is the first report that NOB might improve hepatic oxidative injury through the Nrf2 pathway in a NAFLD mouse model. Long-term dysfunction in lipid metabolism is a hallmark of metabolic syndromes, such as NAFLD [7]. Lipid metabolism disorders, such as excess hepatic TG deposition, can cause the development of hepatic steatosis [8]. In the present study, a lipidomic study was applied to define the types and amounts of lipids that changed in an NAFLD mouse model, thereby aiming to understand the beneficial effects of NOB intervention. The results of hepatic lipidomic analysis showed that the total contents of TG, DG, FFA, and CE were significantly higher in the HFD group (compared to the Chow group), which was also found in previous reports [18]. As expected, NOB administration was associated with lower levels of these lipid species in lipidomic profiles. Higher levels of FFAs can not only cause abnormal hepatic TG storage but can also be converted into lipid intermediates, such as DGs, affecting normal cellular functions. It has been reported that DG intermediates are lipotoxic and are considered as crucial components for accelerating the deterioration of NAFLD [28]. Expectedly, NOB treatment remarkably lowered the deposition of FFAs, TGs, CEs, and DGs, indicating the improvement effect of NOB on hepatic steatosis. The metabolism of TGs, DGs, and FFAs is tightly associated with the factors involved in lipogenesis (SREBP-1c, SCD-1, and FAS) and lipid oxidation (PPARα). Srebp-1c is a key transcription factor in lipogenesis, regulating the expression of its targeted genes, Scd-1 and Fas, which mediate the synthesis of TG and fatty acids [29]. In our work, NOB intake inhibited the expression levels of SREBP-1c, SCD-1, and FAS to reduce TG production and fatty acid biosynthesis, which might contribute to the lower content of the TGs, DGs, and FFAs in lipidomic profiles in the liver and the lower levels of hepatic TG. In addition, NOB supplementation increased the mRNA level of Pparα, which participates in enhancing fatty acid oxidation. Therefore, the reduced content of TGs, DGs, and FFAs may have also had a close relationship with the increase in lipid oxidation after NOB administration. Furthermore, activation of SCD-1 is also involved in the synthesis of CEs [30]. The lower levels of CEs are also observed in Scd-1-deficient mice [31], indicating that inhibition of SCD-1 expression might contribute to the lower level of CEs after NOB intake. A previous study reported that activation of hepatic Lxrα increased the conversion of cholesterol into bile acids by upregulating downstream genes such as Cyp7a1 and Cyp27a1 [32]. Our results demonstrate that NOB supplementation upregulated the genes expression of Cyp7a1 and Cyp27a1, which promote cholesterol conversion into bile acids, while reducing the hepatic TC content. These results are consistent with the findings of the pathway analysis, that NOB intake has an obvious effect on cholesterol metabolism. These data reveal that NOB might exert a cholesterol-reducing benefit on mice fed an HF diet and this pathway may also be beneficial for the improvement of NAFLD. Collectively, the improvement effect of NOB on the NAFLD mouse model may be attributed to the regulation of lipid synthesis and oxidation, thereby affecting liver lipidomic profiles. Previous findings have proposed that glycerophospholipids (GPs), such as PE and PC, played key roles in the progression of NAFLD [17,19]. In our study, several GPs, including PE (O-18:2_20:4), PE(O-20:3_20:4), PE (P-18:0_22:3), PE (P-16:0_20:1), PE (P-18:2_20:2), PC (24:0_18:1), and PC (14:0_18:2), were significantly increased after NOB supplementation (compared with the HFD group). PC is a hydrophilic lipid and is associated with packaging and exporting neutral lipids (e.g., TGs) as VLDL. Thus, the impairment of PC biosynthesis inhibits the synthesis and secretion of VLDL, which contributes to the development of NAFLD [33]. In addition, lipidomic studies of the human liver have demonstrated that NAFLD is associated with a decrease in PC [34]. Similar results were found in our study; the PC was significantly decreased in the HFD group, but NOB treatment increased the PC level. This may also partly contribute to the lower TG levels in liver tissues reported in the lipidomic studies. ## 4.1. Chemicals and Reagents NOB (purity ≥ $98\%$) was obtained from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Paraformaldehyde, urethane, Triton, and Tris-HCl were purchased from Solarbio Science & Technology Co., Ltd. (Beijing, China). Trizol reagent was obtained from Takara (Beijing, China). Hematoxylin and eosin (H&E), the BCA protein assay, Oil Red O (ORO), and total nuclear protein extraction and protein extraction kits were purchased from Beyotime Biotechnology (Beijing, China). The Fast Quantity RT kit was obtained from GenStar Biotechnology (Beijing, China). Commercial kits used to analyze the TC, TG, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), alanine transaminase (ALT), aspartate transaminase (AST), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) levels were purchased from Sino Best Biological Technology (Shanghai, China). HPLC-grade acetonitrile (ACN), methanol (MeOH), isopropanol (IPA), and tert-butyl methyl ether (MTBE) were purchased from Merck (Darmstadt, Germany). HPLC-grade formic acid (FA) was purchased from Sigma (Sigma Aldrich, USA). The antibodies against Nucl-NRF2 (ab62352), HO-1 (ab219360), NOQ1 (ab80588), GCLC (ab207777), stearoyl-CoA desaturase-1 (SCD-1) (ab236868), SREBP-1 (ab28481), β-tubulin (ab6046), and histone-H3 (ab1791) were purchased from Abcam. ## 4.2. Animal Experiments The procedure for the animal experiments was authorized by the Institutional Animal Care and Ethical Committee of Guizhou University of Traditional Chinese Medicine (Approval no: 20210015, Guizhou, China). Male wild-type C57BL/6J mice aged 6–8 weeks were purchased from Changsha Tianqin Biotechnology Co., Ltd. (Changsha, Hunan, China). Mice were housed in a barrier system with a $\frac{12}{12}$ h light–dark cycle, a regular temperature (23–26 °C), and 40–$70\%$ humidity. The mice had access to diet and water ad libitum throughout the experiment. After 1-week adaptive feeding, mice were divided into four groups: Chow group (Research Diets, D12450B), high-fat diet group (HFD) (Research Diets, D12492), HF diet supplemented with $0.1\%$NOB (LNOB) (w/w) ($$n = 8$$) and HF diet supplemented with $0.2\%$NOB (HNOB) (w/w) ($$n = 8$$). The detailed components of the experimental diets are shown in Table 1. The dose of NOB used in the present study was informed by previous works [22,23]. At the end (12 weeks) of the animal experiment, all mice were anesthetized using $20\%$urethane after fasting for 12 h. Blood was obtained from the heart, and thereafter, the supernatant serum samples were collected by centrifuging at 1000 g for 20 min at 4 °C. The liver samples were rapidly frozen using liquid nitrogen and then stored at −80 °C for further analysis. A small part of liver tissues was fixed in $4\%$ buffered formalin for histological analysis. ## 4.3. Glucose Tolerance Test (GTT) The GTT was carried out as previously reported [22]. Briefly, the mice were fasted for 12 h and, thereafter, the fasting glucose blood (FBG) was sampled from the tail vein (0 min). The blood glucose blood concentration at the time points of 15, 30, 60, 90, and 120 min was tested after an intraperitoneal injection of 1 g per kg of body weight of glucose (Sinopharm Chemical Reagent Co., Ltd., Shanghai, China). ## 4.4. Biochemical Analysis and Hepatic Histological Analysis The serum levels of TC, TG, HDL-C, LDL-C, ALT, AST, IL-1β, IL-6, and TNF-α were analyzed using serum biochemistry kits following the manufacturer’s specification. The procedures for the H&E and ORO-staining experiments were carried out as described in our previous study [22], and the images were captured using a Zeiss Axio Imager microscope. In addition, the NAFLD activity score (NAS) was used to measure the severity of NAFLD following the criteria reported by Kleiner et al. [ 35]. Total lipid was extracted from liver samples using ethyl alcohol (g:v (mL) = 1:9), and the hepatic TG and TC contents were detected according to the protocol described in previous work [23]. ## 4.5. Liver Lipidomic Analysis A 1 mL volume of the extraction solvent (MTBE: MeOH =3:1, v/v) containing internal standard mixture was added to the liver tissue samples (50 mg). After homogenization, the mixture was vortexed for 1 min and then centrifuged at 12,000 rpm for 10 min. Then, 500 μL of the upper organic layer was collected and evaporated using a vacuum concentrator. The dry extract was reconstituted using 200 μL of mobile phase B (acetonitrile/isopropanol (10:90, v/v)) prior to analysis. The lipid profile of the sample extracts was analyzed using a UPLC-ESI-MS/MS system (UPLC, ExionLC AD, MS, QTRAP® System). Samples were analyzed on a Thermo Accucore™ C30 column (2.6 μm, 2.1 mm × 100 mm, City, CA, USA) with an injection volume of 2 μL and a flow rate of 0.35 mL/min, and the column temperature was set at 45 °C. The mobile phases consisted of a mixture of acetonitrile/water (60:40, v/v) (A) and a mixture of acetonitrile/isopropanol (10:90, v/v) (B); both liquid mixtures contained $0.1\%$ acetic acid and 10 mmol/L ammonium formate. The solvent gradient program was set as follows: 0–2 min, 20–$30\%$ B; 2–4 min, 30–$60\%$ B; 4–9 min, 60–$85\%$ B; 9–14 min, 85–$90\%$ B; 14–15.5 min, 90–$95\%$ B, 15.5–17.3 min, $95\%$ B; 17.3–20 min, 95–$20\%$ B. The qualitative and quantitative analysis of the lipid profile was carried out using multiple reaction monitoring analysis at Wuhan MetWare Biotechnology Co., Ltd. The analytical methods and detailed work parameters were performed following the description reported in the literature [36,37]. ## 4.6. RNA Extraction and mRNA Expression Levels using Quantitative Real-Time PCR (RT-qPCR) Total RNA extraction and cDNA synthesis were carried out as previously reported [22]. RT-qPCR was performed using a Bio-Rad CFX96 system (Bio-Rad). The primer sequences are listed in Table 2. The expression of targeted mRNA level was normalized to β-actin. ## 4.7. Western Blots (WBs) Hepatic protein extraction and WB were performed as previously described [23]. Briefly, hepatic total and nuclear proteins from the liver tissues were extracted using the total nuclear protein extraction kit and protein extraction kit obtained from Beyotime Biotechnology (Beijing, China). The protein samples were subjected to sodium dodecyl sulfate (SDS)-PAGE and then transferred to a polyvinylidene difluoride membrane (Millipore, USA). Thereafter, these membranes were blocked with $5\%$BSA at an ambient temperature for 2 h. Next, the samples were incubated with primary antibodies including NRF2 (1:800 dilution), HO-1 (1:1000 dilution), NQO1 (1:1000 dilution), GCLC (1:1000 dilution), histone H3 (1:2000 dilution), β-tubulin (1:2000 dilution), SCD-1 (1:1000 dilution), and SREBP-1 (1:1000 dilution), overnight at 4 °C. Then, the membranes were washed with TBST three times and incubated with a horseradish-peroxidase-conjugated secondary antibody (1:2000 dilution) for 2 h at room temperature. The immunoreactive bands were observed using a gel image analysis system using enhanced chemiluminescence (Advansta, California, USA). ## 4.8. Data Analysis SPSS version 22.0 software was used to analyze statistical significance using one-way parametric analysis of variance (ANOVA) followed by Tukey’s post hoc test. The area under the curves (AUCs) of the GTT were analyzed by Origin 8.0 software. All data are shown as means ± standard deviation (SD) of the mean. $p \leq 0.05$ was regarded as a significant difference. ## 5. 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--- title: 'Screening for Gestational Diabetes Mellitus: Is There a Need for Early Screening for All Women in Developing Countries?' journal: Cureus year: 2023 pmcid: PMC10054911 doi: 10.7759/cureus.35533 license: CC BY 3.0 --- # Screening for Gestational Diabetes Mellitus: Is There a Need for Early Screening for All Women in Developing Countries? ## Abstract Background: Gestational diabetes mellitus (GDM) is associated with significant adverse pregnancy outcomes. Early diagnosis and treatment have been proven to reduce adverse pregnancy outcomes among women diagnosed with GDM. Current guidelines recommend routine screening for GDM at 24-28 weeks of pregnancy, with early screening offered to those considered high risk. However, risk stratification may not always be helpful for those who would benefit from early screening, especially in non-Western settings. Aim: To determine the need for early screening for GDM among pregnant women attending antenatal clinics in two tertiary hospitals in Nigeria. Methods: We conducted a cross-sectional study from December 2016 to May 2017. We identified women who presented at the antenatal clinics of the Federal Teaching Hospital Ido-Ekiti and Ekiti State University Teaching Hospital, Ado Ekiti. A total of 270 women who fulfilled the study inclusion criteria were enrolled. The 75 g oral glucose tolerance test was used to screen participants for GDM before 24 weeks and between 24 and 28 weeks for those who screened negative before 24 weeks. Pearson's chi-square test, Fisher's exact test, independent t-test, and Mann-Whitney U test were utilized in the final analysis. Results: The median age of the women in the study was 30 (interquartile range: 27-32) years. Of our study participants, 40 ($14.8\%$) were obese, 27 ($10\%$) had a history of diabetes mellitus in a first-degree relative, and three ($1.1\%$) women had a previous history of GDM. Twenty-one women ($7.8\%$) were diagnosed with GDM, and six ($28.6\%$) were diagnosed before 24 weeks. Women diagnosed with GDM before 24 weeks were older (37 years; interquartile range: 34-37) and more likely to be obese ($80.0\%$). A significant number of these women also had identifiable risk factors for GDM: previous GDM ($20.0\%$), family history of diabetes mellitus in a first-degree relative ($80.0\%$), prior delivery of fetal macrosomia ($60.0\%$), and previous history of congenital fetal anomaly ($20.0\%$). Conclusion: The findings from the present study did not justify universal screening for GDM in all pregnant women. Patients diagnosed before the 24-28 weeks of universal screening are more likely to have significant risk factors for GDM and, therefore, would have been selected for screening based on the risk factor screening. ## Introduction Gestational diabetes mellitus (GDM) is any glucose intolerance with onset or first recognition in pregnancy [1]. It is one of the most common pregnancy complications and affects about 1-$14\%$ of pregnancies worldwide [2]. It is associated with maternal and fetal complications, including fetal macrosomia, stillbirth, birth trauma, preeclampsia, cesarean delivery, post-operative infections, neonatal hypoglycemia, and an increased risk of developing type 2 diabetes mellitus [3-5]. The risk factors for GDM include previous history of GDM, family history of diabetes, and race. Selective screening is carried out in some European countries due to lower costs [1], and the effectiveness of early screening based on maternal risk factors has been supported by the literature [6]. However, screening in the USA is more universal and is associated with lower costs in the long term [7]. Screening for GDM is usually carried out between 24 and 28 weeks for all pregnant women with a 75 g oral glucose tolerance test (OGTT), as proposed by the International Association of Diabetes and Pregnancy Study Groups (IADPSG), and this was adopted by the World Health Organization (WHO) in 2013. Risk-based screening is practiced in Nigeria, where the prevalence of GDM is high [8], and is targeted toward women with an increased risk of GDM at 24-28 weeks [9]. Early screening is usually reserved for women with a high risk of GDM, and it has been found that the prevalence of GDM in the first and second trimesters is significant and that up to one in 20 cases of GDM may be missed by risk-based screening alone [9]. Although recent studies have reported the need for earlier screening, there is not enough evidence to support the revision of current guidelines, especially among low-risk pregnant women [10,11]. Early detection and treatment improve pregnancy outcomes, making universal early screening beneficial. This study, therefore, aims to determine if early universal screening of GDM is beneficial, by identifying the prevalence of GDM diagnosis before 24 weeks. It will also determine if the diagnosis of GDM correlates with identifiable risk factors. ## Materials and methods The study was conducted among pregnant women attending antenatal clinics at the Ekiti State University Teaching Hospital (EKSUTH), Ado Ekiti, and the Federal Teaching Hospital (FTH) Ido-Ekiti, Ekiti State, Western Nigeria. These women attended antenatal care (ANC) between December 2016 and May 2017. Women were excluded if they had no reliable way to date the pregnancy. Women who declined to consent to the study were also excluded. Written informed consent was sought from the study participants. A total of 280 women participated in the study, with 10 lost to follow-up. The 75 g OGTT was performed according to the WHO recommendation on the appointed date for the test. Socio-demographic information was extracted from the case notes of the patients. GDM was diagnosed using the IADPSG criteria. Patients with at least one of the following were classified as having GDM: fasting plasma glucose ≥ 92 mg/dl (≥5.2 mmol/l), one-hour plasma glucose ≥ 180 mg/dl (≥10 mmol/l), or two-hour plasma glucose ≥ 153 mg/dl (≥8.5 mmol/l). The study outcome variable was a diagnosis of GDM based on the IADPSG criteria. This was done twice in pregnancy, before the 24th week, and women who were negative during the first screening had a repeat screening and diagnosis between 24 and 28 weeks. The independent variables included the body mass index (BMI), calculated from measured pre-pregnancy weight (kg) and height (m) at the first visit. Other variables include patients' age, education status, race/ethnicity, and risk factors. We received permission to conduct this study from both the EKSUTH, Ado Ekiti and FTH Ido-Ekiti Institution Review Boards (EKSUTH/A$\frac{67}{2016}$/$\frac{01}{004}$/ERC/$\frac{2016}{01}$/$\frac{12}{02}$A). Statistical analysis We utilized Pearson's chi-square test to evaluate the relationship between the studied variables and the occurrence of GDM before 24 weeks and between 24 and 28 weeks. A two-tailed p-value < 0.05 was considered statistically significant. All statistical analyses were performed using STATA version 16 (StataCorp LLC, College Station, TX). ## Results Table 1 shows the study participants' demographic characteristics and risk factors. Among the 270 women who participated in the study, 42 ($15.6\%$) were >35 years old at the time of the survey. The prevalence of GDM in the sample population was $7.8\%$, with 21 positive cases. Most of the study participants had normal pre-pregnancy BMI (184, $68.1\%$), 55 ($20.4\%$) were overweight, 18 ($6.7\%$) were obese, and only 13 ($4.8\%$) were underweight. Fetal macrosomia was relatively common, with 32 ($11.9\%$) women having a previous delivery of a child with a delivery weight > 4 kg. Only 27 ($10\%$) women had a family history of diabetes in a first-degree relative. There were six ($2.2\%$) cases of chronic hypertension, 10 ($3.7\%$) previous records of intrauterine fetal death or stillbirths, and four ($1.5\%$) prior histories of delivery of a baby with a congenital abnormality. Only three ($1.1\%$) women had a previous history of GDM. **Table 1** | Variables | Total population | GDM (24-28 weeks) | Normal | P-value | | --- | --- | --- | --- | --- | | | (n = 270) | (n = 21) | (n = 249) | | | Median age (interquartile range) | 30 ( 27-32) | 37 (36-38) | 30 (27-32) | <0.001 | | Age | | | | <0.001 | | ≤35 years | 228 (84.4%) | 4 (19.1%) | 224 (90.0%) | | | >35 years | 42 (15.6%) | 17 (80.9%) | 25 (10.0%) | | | Median pre-pregnancy body mass index (interquartile range) | 22.8 (20.8-25.3) | 29.1 (24.8-31.1) | 22.5 (20.3-24.9) | <0.001 | | Body mass index (kg/m2) | | | | <0.001 | | Normal body mass index | 139 (51.5%) | 1 (4.8%) | 138 (55.4%) | | | Overweight | 91 (33.7%) | 6 (28.6%) | 85 (34.1%) | | | Obese | 40 (14.8%) | 14 (66.7%) | 26 (10.4%) | | | Previous gestational diabetes mellitus | 3 (1.1%) | 3 (14.3%) | 0 (0.0%) | <0.001 | | Family history of diabetes mellitus | 27 (10.0%) | 17 (81.0%) | 10 (4.0%) | <0.001 | | Chronic hypertension | 6 (2.2%) | 2 (9.5%) | 4 (1.6%) | 0.02 | | Macrosomia | 32 (11.9%) | 13 (61.9%) | 19 (7.6%) | <0.001 | | Stillbirth | 6 (2.2%) | 0 (0.0%) | 6 (2.4%) | 0.47 | | Spontaneous miscarriage | 37 (13.7%) | 3 (14.3%) | 34 (13.7%) | 0.94 | | Previous congenital anomaly | 4 (1.5%) | 2 (9.5%) | 2 (0.8%) | <0.001 | | Intrauterine fetal death | 4 (1.5%) | 2 (9.5%) | 2 (0.8%) | <0.001 | Table 2 describes the association between some selected traditional risk factors of GDM and the diagnosis of the disease before 24 weeks. Women diagnosed before 24 weeks were older, with a median age of 37 (interquartile range: 34-37) years, $80.0\%$ of these women were obese, and a significant proportion of the women have traditional risk factors for GDM, including previous GDM ($20.0\%$), family history of diabetes ($80.0\%$), prior delivery of a baby weighing ≥ 4 kg ($60.0\%$), and previous history of congenital fetal anomaly ($20.0\%$). **Table 2** | Variable | Total | GDM (<24 weeks) | Normal | P-value | | --- | --- | --- | --- | --- | | | (n = 270) | (n = 6) | (n = 264) | | | Median age (interquartile range) | 30 (27-32) | 37 (34-37) | 30 (27-32) | <0.001 | | Age | | | | <0.001 | | ≤35 years | 228 (84.4%) | 2(40.0%) | 226 (85.3%) | | | >35 years | 42 (15.6%) | 3 (60.0%) | 39 (14.7%) | | | Median pre-pregnancy body mass index (interquartile range) | 22.8 (20.8-25.3) | 29.3 (29.1-31.3) | 22.8 (20.8-25.0) | <0.001 | | Obese | 40 (14.8%) | 4 (80.0%) | 36 (13.6%) | <0.001 | | Previous gestational diabetes mellitus | 3 (1.1%) | 1 (20.0%) | 2 (0.8%) | <0.001 | | Family history of diabetes mellitus | 27 (10.0%) | 4 (80.0%) | 23 (8.7%) | <0.001 | | Chronic hypertension | 6 (2.2%) | 0 (0.0%) | 6 (2.3%) | 0.73 | | Macrosomia | 32 (11.9%) | 3 (60.0%) | 29 (10.9%) | <0.001 | | Spontaneous miscarriage | 37 (13.7%) | 1 (20.0%) | 36 (13.6%) | 0.7 | | Stillbirth | 6 (2.2%) | 0 (0.0%) | 6 (0.73) | 0.73 | | Intrauterine fetal death | 4 (1.5%) | 0 (0.0%) | 4 (1.5%) | 0.78 | | Previous congenital anomaly | 4 (1.5%) | 1 (20.0%) | 3 (1.1%) | <0.001 | ## Discussion In the present study, the prevalence of GDM was $7.8\%$, which is lower than the pooled prevalence of GDM in Nigeria reported in a systematic review ($11\%$), and this was attributed to differences in female characteristics of the study participants and differences in the screening methods utilized [8]. A prevalence of $5.2\%$ was also reported and it was concluded that the prevalence of GDM in Nigeria was on the rise and that the disparities in prevalence reports could be attributed to better screening tools, better screening policies, and increased exposure to risk factors [9]. About one in every three women diagnosed with GDM was diagnosed before 24 weeks, which is lower than previous findings that one in every two women diagnosed with GDM was diagnosed in the first and second trimesters [9]. These findings support early screening for GDM, which will detect women who develop GDM before 24 weeks and would have been missed by universal screening after 24 weeks. However, the United States Preventive Services Task Force (USPSTF) stated that there was insufficient evidence to assess the balance of benefits and harms of screening for gestational diabetes in asymptomatic pregnant persons before 24 weeks of gestation and recommended screening for gestational diabetes in asymptomatic pregnant persons at 24 weeks of gestation or after [12]. In the present study, there was a significant association between risk factors and diagnosis of GDM before the 24th week of pregnancy. The women diagnosed with GDM before 24 weeks were generally older and had a higher pre-pregnancy body mass index. A higher proportion of these women were obese and had traditional risk factors for GDM, similar to the findings of a case-control study carried out in Iran, where the prevalence of GDM was higher than in most regions in the world [13]. The authors found that a family history of type 2 diabetes mellitus was the most important risk factor for GDM, with advanced maternal age and obesity also having significant associations with a diagnosis of GDM. In our study, a previous history of fetal macrosomia was the commonest risk factor for GDM. These findings align with the literature, which supports the association between risk factors and the diagnosis of GDM irrespective of gestational age [6,14] and justifies risk stratification as a reliable way to decide whom to offer early screening. This further implies that older women who are obese or overweight should be the target of early screening efforts and lifestyle modifications. Our findings of a lack of association between some risk factors for GDM, such as spontaneous miscarriage and stillbirth, and diagnosis before 24 weeks may be due to smaller numbers and the multifactorial etiology of these conditions. A retrospective study done in Estonia, where risk-based screening is practiced, showed that women with risk factors for GDM who screened negative with OGTT were still at risk of excessive weight gain and large for gestational age (LGA) deliveries, which are in turn associated with adverse pregnancy outcomes [15]. This may be explained by the confounding effect of other risk factors such as obesity on LGA and excessive weight gain and implies that women with risk factors for GDM who screen negative should not be dismissed and should still be provided with management options for reducing gestational weight gain. It is of interest that some of the women diagnosed with GDM did not have identifiable risk factors, and this is also supported by literature findings [16,17]. These studies overall argue for universal screening of all women for GDM regardless of risk factor stratification. Clearly, both universal screening and risk-based screening have benefits that are applicable in different settings. In settings where the prevalence of GDM is high and resources are available, universal screening would be beneficial in the long term, and in resource-limited settings like Nigeria, risk-based screening may be more appropriate. Irrespective of the setting, however, the adverse pregnancy outcomes associated with GDM can be avoided by initiating behavioral lifestyle modifications during the antenatal period [18] and incorporating these interventions into routine ANC. A major obstacle in detecting and managing GDM in *Nigeria is* low ANC attendance. According to the Nigerian Demographic and Health Survey, only $67\%$ of women have at least one ANC throughout pregnancy, $57\%$ have at least four ANC visits, and more than a third do not have formal ANC [19]. There are obvious benefits of ANC in improving pregnancy outcomes in women with GDM. Adverse pregnancy outcomes such as fetal distress, instrumental delivery, cesarean delivery, poor Apgar scores, and neonatal hypoglycemia, which lead to neonatal intensive care unit (NICU) admission, can be avoided by improving maternal glycemic control. Glycemic control can be achieved in the antenatal period by lifestyle modifications such as dietary restriction and glucose monitoring [20,21]. The current guidelines for screening for GDM at 24-28 weeks are based on evidence that the pathogenic mechanism for GDM (insulin resistance) begins at this period [22,23]. However, other studies have shown that insulin resistance in pregnant women may start as early as 14 weeks of gestation [24]. Overall, there is insufficient evidence to demonstrate a clear benefit, especially in low-resource settings, of the need for early screening [25]. Our study highlights the importance of screening women with risk factors for GDM irrespective of their gestational age and alludes to the importance of initiating intervention in women with risk factors for GDM who may screen negative. It is vital to interpret the findings from this study with caution. First, as a two-center study, the results may not be generalizable to the whole country. Since this is a cross-sectional study, it is challenging to make categorical statements on screening since we cannot establish temporality or causality from cross-sectional studies. Lastly, the authors cannot rule out specific biases such as reporting and selection bias. However, the strengths of the present study include that it addresses a knowledge gap about the association between risk factors of GDM and diagnosis of GDM before 24 weeks. 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--- title: Soy Extract, Rich in Hydroxylated Isoflavones, Exhibits Antidiabetic Properties In Vitro and in Drosophila melanogaster In Vivo authors: - Kai Lüersen - Alexandra Fischer - Ilka Bauer - Patricia Huebbe - Yukiko Uekaji - Keita Chikamoto - Daisuke Nakata - Naoto Hiramatsu - Keiji Terao - Gerald Rimbach journal: Nutrients year: 2023 pmcid: PMC10054920 doi: 10.3390/nu15061392 license: CC BY 4.0 --- # Soy Extract, Rich in Hydroxylated Isoflavones, Exhibits Antidiabetic Properties In Vitro and in Drosophila melanogaster In Vivo ## Abstract In the context of the growing prevalence of type 2 diabetes (T2DM), control of postprandial hyperglycemia is crucial for its prevention. Blood glucose levels are determined by various factors including carbohydrate hydrolyzing enzymes, the incretin system and glucose transporters. Furthermore, inflammatory markers are recognized predictors of diabetes outcome. Although there is some evidence that isoflavones may exhibit anti-diabetic properties, little is known about to what extent their corresponding hydroxylated metabolites may affect glucose metabolism. We evaluated the ability of a soy extract before (pre-) and after (post-) fermentation to counteract hyperglycemia in vitro and in Drosophila melanogaster in vivo. Fermentation with Aspergillus sp. JCM22299 led to an enrichment of hydroxy-isoflavones (HI), including 8-hydroxygenistein, 8-hydroxyglycitein and 8-hydroxydaidzein, accompanied by an enhanced free radical scavenging activity. This HI-rich extract demonstrated inhibitory activity towards α-glucosidase and a reduction of dipeptidyl peptidase-4 enzyme activity. Both the pre- and post-fermented extracts significantly inhibited the glucose transport via sodium-dependent glucose transporter 1. Furthermore, the soy extracts reduced c-reactive protein mRNA and secreted protein levels in interleukin-stimulated Hep B3 cells. Finally, supplementation of a high-starch D. melanogaster diet with post-fermented HI-rich extract decreased the triacylglyceride content of female fruit flies, confirming its anti-diabetic properties in an in vivo model. ## 1. Introduction The prevalence of diabetes, especially type 2 diabetes mellitus (T2DM), is increasing globally [1]. This metabolic disease is characterized by hyperglycaemia, induced by a progressive insulin secretory defect or a diminished or missing response of insulin receptors [2]. Continuously high blood sugar levels may result in long-term complications, including renal and cardiovascular diseases, retinopathy or an impaired blood flow [3]. Thus, controlling postprandial hyperglycemia through dietary means is crucial for the prevention of T2DM. Blood glucose levels are determined by various factors including food constituents and food matrix, glucose transporters, carbohydrate hydrolyzing enzymes (e.g., α-glucosidase, α-amylase) and hormones such as the incretin system. The incretin system relates to the gut hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulin polypeptide (GIP), which increase postprandial insulin production by acting on pancreatic beta cells. Dipeptidyl peptidase-4 (DPP-4) degrades circulating GLP-1 and GIP and reduces the circulating postprandial glucagon level [4]; hence, DPP4 inhibitors are regarded as a novel means for extending the action of insulin and treating T2DM. In addition, intestinal glucose absorption is largely achieved by sodium/glucose symporter 1 (SGLT1) [5]. SGLT1 expression is regulated by the diet, e.g., it is strongly elevated in response to intraluminal glucose and by compounds that activate sweet taste receptors [6]. Moreover, it is induced in patients with T2DM [7]. The development of T2DM is usually associated with chronic inflammation. Accordingly, C-reactive protein (CRP), which is considered a sensitive systemic marker of low-grade inflammation, has been found to be a proper biomarker for T2DM [8]. CRP predominantly synthesized and secreted by hepatocytes is elicited by the dual activity of interleukin (IL)-6 and IL-1ß, and enhances inflammatory pathways by inducing IL-6 secretion [9,10]. A recent meta-analysis investigated the impact of soy intake on inflammatory markers and revealed significantly decreased CRP levels in women; however, the underlying mechanisms by which soy foods and their ingredients influence inflammatory biomarkers has not yet been elucidated [11]. Importantly, legumes, specifically soybeans, are a widespread dietary source of isoflavones, with genistein, daidzein and glycitein forming the major fraction [12]. In contrast, their hydroxylated counterparts, such as 8-hydroxygenistein (8OHGen), 8-hydroxydaidzein (8OHDai) and 8-hydroxyglycitein (8OHGly), are barely found in plants. Hydroxylation at either the C6 or C8 carbon position of the isoflavone backbone is not prioritized during isoflavone biosynthesis in plants, as cytochrome P450 (CYP)-dependent enzymes from plants seem to not catalyze the ortho-hydroxylation. However, food processing can affect the isoflavone concentration and isomer composition of soy products. Thus, most hydroxylated isoflavones (HI) are derived from fermented soybean foods, such as miso, natto, soy sauce and tempeh, where microorganisms, mainly fungi (e.g., Aspergillus) and bacteria (e.g., Rhizopus, Streptomyces), incorporate the hydroxyl-group into the isoflavone molecule during fermentation in a CYP-dependent manner [12,13]. Furthermore, the production of HIs is also feasible via microbial production using genetic engineering [14]. In addition, fermentation increases the cleavage of glycoside bonds of isoflavones, thereby enhancing their bioavailability [15,16]. The basic chemical structure of the isoflavones consists of two benzene rings (1 and 2) linked via a heterocyclic pyrone ring [3] (Figure 1). Isoflavones have been shown to induce endogenous antioxidant defense mechanisms, such as glutathione peroxidase, catalase and superoxide dismutase [18], presumably via an Nrf2-dependent signal transduction pathway [19]. Furthermore, an inhibition of lipoxygenase due to isoflavones has been described [20]. In addition, the dietary intake of genistein and daidzein improved the resistance of LDL against oxidation [21]. Genistein and daidzein are relatively weak scavengers of hydroxyl, superoxide, and nitric oxide free radicals, as determined using spin trapping and electron spin resonance spectroscopy [22]. Interestingly, it has been shown in vitro that the corresponding hydroxylated metabolites of genistein and daidzein exhibited significantly stronger bioactivity in terms of prevention of lipid peroxidation as compared to the parent compounds per se [23,24]. Hirota et al. [ 25] found that, among various isoflavones isolated from soybean miso, 8OHGen represented the most potent antimutagenic and antiproliferative activity. Likewise, in contrast to daidzein, 8OHDai has been found to be a potent aldose reductase inhibitor in vitro [26] and may, therefore, represent a potential substance for the treatment of diabetic complications. However, fermented isoflavones remain an “understudied” group of soy compounds and little is known about the bioactivity of isoflavones regarding their antidiabetic properties [15], especially to what extent their corresponding hydroxylated metabolites, including 8OHGen, 8OHDai and 8OHGly, may affect glucose metabolism and biomarkers of inflammation. The aim of our study was to investigate a soybean extract before (pre-) fermentation and, in particular, a HI-rich extract after (post-) fermentation, regarding their antidiabetic and anti-inflammatory properties in vitro. Aspergillus sp. JCM 22,299 was applied for fermentation, which resulted in a substantial increase in HI, where 8OHGen represented the highest fraction. We tested the in vitro impact of the HI extract on α-glucosidase inhibition, starch digestion via α-amylase and the incretin system regarding DPP4 inhibition. The influence of soy bean pre-extract and HI extract was further evaluated based on the activity of glucose transport by SGLT1 using the Caco-2 cell culture model and CRP expression (mRNA and secreted protein level) in cultured hepatocytes. In order to take into account pharmacological aspects, such as bioavailability, the influence of the gut microbiota and biotransformation, the verification of in vitro bioactivities in animal models usually represents the next important step in the development of new therapeutic approaches. In recent years, the fruit fly Drosophila melanogaster has been acknowledged as a valuable model in food science [27]. In particular, owing to the remarkable similarity between D. melanogaster and humans in terms of the metabolic pathways involved in energy metabolism and its hormonal regulation, several genetic and diet-based diabetes models have been established in fruit flies [28,29,30], which can serve as helpful tools to test putative antidiabetic substances [31,32]. Accordingly, we employed a high-sugar diet D. melanogaster obesity model, which we have previously used to validate the efficacy of plant extracts with α-amylase and α-glucosidase inhibitor activities [32] to examine whether the post-fermented HI extract exerted antidiabetic properties in vivo. ## 2.1. Preparation of Pre-Fermented and Hydroxy-Isoflavone (HI)-Enriched Post-Fermented Soybean Extract and Isoflavone Analysis Using HPLC Soy isoflavone extract was supplied by Toyo Hakko Co., Ltd. (Aichi, Japan). To obtain an extract enriched in HI, soy isoflavone extracts (pre-fermented samples) were sterilized at 121 °C for 20 min and, subsequently, fermented with Aspergillus sp. JCM 22,299 for 8 d at 30 °C with aeration and continuous stirring. After ethanol extraction and two separation steps, the extract was concentrated using evaporation and filtrated through a 30-mesh filter. The obtained post-fermented samples as well as the pre-fermented samples were analyzed in terms of their isoflavone content through HPLC (Prominence UFLC, Shimadzu Corporation, Kyoto, Japan) using a Phenomenex, Kinetex C18 column, 100A (5 μm, 4.6 mm I.D. × 250 mm, Phenomenex Inc., Torrance, CA, USA). Mobile phase A consisted of $0.1\%$ acetic acid and mobile phase B was made of acetonitrile while using a gradient profile (0~50 min (15~$35\%$ B), 50~55 min ($100\%$ B), 55~60 min ($15\%$ B)) at a flow rate of 1.0 mL/min and a temperature of 35 °C. The injection volume was 10 µL and detection was carried out at 254 nm. An external standard curve was applied to calculate the concentration using the peak area (Figure 2). Hence, the concentrations of 8OHGen, 8OHGly and 8OHDai were determined to be $35\%$, $9\%$ and $8\%$ of total isoflavones content in the post-fermented extract, respectively. ## 2.2. Antioxidant Capacity Assays The free radical scavenging properties of pre- and post-fermented soy extracts (10 µg/mL) were determined with the ferric-reducing ability of plasma (FRAP) assay and the trolox equivalent antioxidant capacity (TEAC) assay, as previously described [33,34]. For the FRAP assay, which measures how well a test compound reduces ferric ions (Fe3+) to ferrous ions (Fe2+), pre- or post-fermented soy extracts were added to a 2 mM iron (III) chloride solution with 2,4,6-tris(2-pyridyl)-s-triazine (TPTZ, 1 mM) in acetate buffer (228 mM, pH 3.6). After 15 min of incubation, absorbance was measured at 620 nm in an iEMS reader MF (Labsystems, Helsinki, Finland). Results are given in µmol ascorbic acid equivalents per mg extract. The TEAC assay is related to the reduction of ABTS (2,20-azino-bis-(3-ethylbenzthiazoline-6-sulfonic acid) radical cation by antioxidants. The increase in reduction by pre- or post-fermented extracts was photometrically measured at 750 nm in a Tecan Infinite 200 (Tecan Group Ltd., Crailsheim, Germany) microplate reader and compared to trolox as external standard. TEAC values are given in µmol trolox equivalents per mg extract. ## 2.3.1. In Vitro α-Glucosidase Inhibition Assay A total of 15 µL of diluted (0.05–10 mg/mL) HI extracts was added to 105 μL of 0.1 M phosphate buffer, pH 6.8 and 15 μL of 0.5 U/mL baker yeast α-glucosidase (Sigma-Aldrich, Taufkirchen, Germany). Acarbose was used as a reference inhibitor. After 5 min of pre-incubation at 37 °C, 15 μL of the substrate p-nitrophenyl-α-D-glucopyranoside (10 mM, Sigma-Aldrich, Taufkirchen, Germany) was added and incubated for 20 min at 37 °C in a 96-well microtest plate (VWR, Darmstadt, Germany). The reaction was stopped by adding 50 μL 2 M Na2CO3 (VWR, Darmstadt, Germany) and the absorbance of samples was measured photometrically at 405 nm (iEMS Reader MF). ## 2.3.2. In Vitro α-Amylase Inhibition (Disc) Assay Four filter discs with a diameter of 0.5 cm were placed in a 92 × 16 mm Petri dish (Sarstedt, Nuernbrecht, Germany) filled with medium comprising $1\%$ agar–agar (Carl Roth GmbH & Co. KG, Karlsruhe, Germany) and $1\%$ starch (VWR, Darmstadt, Germany). Then, 80 µL of HI extract at concentrations of 0–10 mg/mL was mixed with 20 µL α-amylase (derived from porcine pancreas, Sigma-Aldrich, Taufkirchen, Germany). Acarbose was utilized as a reference inhibitor. A total of 20 μL of each sample was pipetted onto filter discs and left at 37 °C overnight. After removing the filter discs, plates were incubated with 5 mM iodine in $3\%$ potassium iodide solution (Merck, Darmstadt, Germany). After 15 min, the diameters of the cleared zones were evaluated and the percentage inhibition of α-amylase was calculated. The disc assay was performed on two independent testing days. ## 2.3.3. In Vitro Dipeptidyl Peptidase-4 (DPP4) Inhibition Assay The DPP4 inhibitor activities of HI extracts were determined using the DPP4 inhibitor screening kit according to the manufacturer’s instructions (MAK203, Sigma-Aldrich, Taufkirchen, Germany). The HI extract was dissolved in DMSO to a concentration of 100 mg/mL and further diluted to a final concentration of 1 mg/mL, 250 µg/mL and 100 µg/mL with assay buffer. Then, 18 nM of the established DPP4 inhibitor sitagliptin (representing its IC50 concentration) served as the positive inhibitor control, whereas assay buffer only was used as the control for DPP4 enzyme activity and was set to $100\%$. Subsequently, 49 μL assay buffer and 1 μL DPP4 enzyme were mixed with 25 μL of HI extract and 18 nM sitagliptin or assay buffer. After 10 min pre-incubation at 37 °C, a reaction mix of 23 μL assay buffer and 2 μL substrate was given to each well. The fluorescence signal (excitation: 360 nm, emission: 465 nm) was measured in black 96-well microtiter plates at 37 °C over a period of 30 min in 1 min intervals (Tecan Infinite 200 microplate reader). ## 2.4. Testing for Mycoplasma Contamination All cell lines were regularly tested for mycoplasma contamination via the Mycoplasma Detection Kit for conventional PCR (Venor®GeM Classic, Minerva Biolabs, Berlin, Germany) using MB Taq Polymerase (5 Unit/µL, 50 Units). All tested cell lines were found to be mycoplasma-negative. ## 2.5. Sodium-Dependent Glucose Transporter 1 (SGLT1) Assay Using Ussing Chambers in Caco-2/PD7 Cells SGLT1 was determined in Caco-2/PD7 cells by employing the Ussing chambers methodology [32]. Cells were provided by Edith Brot-Laroche, Unité de Recherches sur la Différenciation Cellulaire Intestinale (Villejuif Cedex, France) and seeded at a density of 1 × 106 cells/well into 6-well Corning® Costar® Snapwell cell culture inserts (0.4 μm pore size, 1.12 cm2surface area, Merck, Darmstadt, Germany). Following 21 days of culturing, 0.5 mL of the cell-containing medium was given to the apical side (upper compartment) and 2.5 mL of cell-free medium was seeded into the basolateral side (lower compartment). After 7 days, the apical medium was withdrawn FBS. Only monolayers with a transepithelial electrical resistance (TEER) value exceeding 300 Ω cm2, measured via a Millicell ERS-2 Volt-Ohm Meter, equipped with a STX01 planar electrode (Merck, Darmstadt, Germany), were regarded as functional barriers and used in the transport studies. Before starting the experiments, Hank’s balanced salt solution (HBSS, pH 7.2) was heated to 37 °C and oxygenated using an influx of carbogen-gas ($95\%$ oxygen, $5\%$ carbon dioxide). HBSS was used to fill half-chambers and wash Caco-2/PD7 monolayers before mounting the Snapwell inserts in Ussing chamber slides. Subsequently, both half-chambers were replenished with HBSS solution containing mannitol (10 mmol/L) apically and glucose (10 mmol/L) basolaterally. The measurement of the transepithelial potential difference was performed at 37 °C under open-circuit conditions using a DVC 1000 amplifier (WPI) and continuous carbogen bubbling. The potential difference was continuously monitored and recorded through Ag–AgCl electrodes and KBR agarose bridges. The short-circuit current (ISC; μA cm−2) was measured via an automatic VCCMC8 MultiChannel Voltage Current Clamp (Physiologic Instruments) and data were stored using the Acquire & Analyze Data II acquisition software (Physiologic Instruments). The potential difference was allowed to stabilize for 20 min. Then, 10 mM glucose solution was given apically and 10 mM mannitol solution basolaterally. The glucose-stimulated ISC was challenged by applying either pre-fermented extract (1 mg/mL), post-fermented HI-rich extract (1 mg/mL) or phlorizin (0.1 mM) as a positive control for inhibition of SGLT1 activity. The decline in the glucose-induced ISC was assessed. ## 2.6. Induction of CRP in Hep 3B Cells and Measurement of CRP mRNA and Secreted Protein Level Induction of CRP in Hep 3B cells and measurement of CRP mRNA and secreted protein levels were conducted according to [35,36]. Hep 3B cells were kindly gifted by Claudia Geismann (Laboratory of Molecular Gastroenterology & Hepatology, Department of Internal Medicine I, UKSH-Campus Kiel, 24,105 Kiel, Germany). Cells were cultivated for 5 days in MEM with Earle’s balanced salt solution (EBSS), L-glutamine (PAN Biotech, Aidenbach, Germany) and 2.2 g/L NaHCO3; and supplemented with $10\%$ (vol/vol) heat inactivated fetal bovine serum (Gibco™ by Thermo Fisher Scientific GmbH, Life Technologies™, Darmstadt, Germany) and $1\%$ penicillin/streptomycin (PAN Biotech, Aidenbach, Germany). For CRP induction, Hep 3B cells were incubated with 10 µg/mL isoflavone extract in DMSO in serum-free media containing 1 µM of dexamethasone (Dex) and stimulated with interleukin-1ß (IL1ß, 400 U/mL) and interleukin-6 (IL6, 200 U/mL) (both from ImmunoTools GmbH, Friesoythe, Germany) for 18 h for mRNA isolation or 48 h for ELISA analyses. DMSO served as the solvent control at a final dilution of $0.1\%$. RNA isolation and quantitative RT-PCR were performed as previously described [37]. In brief, cells were harvested and RNA isolated with peqGOLD TriFast (VWR International, Radnor, PA, USA). The RNA isolation procedure is based on phenol and guanidinium thiocyanate extraction and on separation of RNA, protein and DNA into three phases upon centrifugation after adding chloroform. RNA concentrations and purity ($\frac{260}{280}$ nm) were determined with a Nanodrop 2000 (Thermo Fisher Scientific GmbH, Life Technologies, Darmstadt, Germany). Gene expression was determined using quantitative RT-PCR with the SensiFAST™ SYBR® No-ROX One-Step Kit (Bioline, Luckenwalde, Germany) via Rotorgene 6000 cycler (Corbett Life Science, Sydney, Australia). Gene expression levels were analyzed using a standard curve and normalized to the expression level of GAPDH. Primers were as follows: CRP forward primer: 5′-CCCTGAACTTTCAGCCGAATACA-3′; CRP reverse primer 5′-CGTCCTGCTGCCAGTGATACA-3′; GAPDH forward primer: 5′-CAATGACCCCTTCATTGACC-3′; and GAPDH reverse primer: 5′-GATCTCGCTCCTGGAAGATG-3′. To determine the secreted CRP protein levels, the cell culture medium was diluted 1:250 before being used for the ELISA according to the manufacturer’s instructions (Hu-man C-reactive Protein ELISA Kit, Sigma-Aldrich, Taufkirchen, Germany). ## 2.7. Drosophila Melanogaster Feeding Assay Using a High-Starch Diet The D. melanogaster wild-type strain w1118 (#5905, Bloomington Drosophila Stock Center, Indiana University, Bloomington, United States) was maintained under standard conditions in climate cabinets HPP750 or HPP110 (Memmert, Schwabach, Germany) at 25 °C, $60\%$ humidity, and a $\frac{12}{12}$ h light/dark cycle [32]. The fruit flies were cultured on *Caltech medium* ($6.0\%$ cornmeal, $5.5\%$ dextrose, $3.0\%$ sucrose, $2.5\%$ inactive dry yeast, $1.0\%$ agar Type II, Kisker, Steinfurt, Germany). Propionic acid ($0.3\%$, Carl Roth, Karlsruhe, Germany) and Tegosept ($0.15\%$, Genesee Scientific, San Diego, SC, USA) were added to the medium as preservatives. The feeding assay was started by transferring freshly eclosed adult animals to CT medium for mating. On day 3, female fruit flies were sorted and transferred onto a starch-based control diet ($20\%$ soluble starch (Carl Roth), $5\%$ yeast, $2\%$ agar, $0.18\%$ nipagin, $0.3\%$ propionic acid) or experimental diets that were supplemented with $0.8\%$, $1.6\%$ or $2.4\%$ of the post-fermented HI-rich extract. A medium containing 1.8 μg/mL acarbose was used as positive control [32]. The mated female flies were then transferred to the respective fresh experimental medium every other day. On day 10, the animals were harvested and ten flies per vial were homogenized for 10 min at 4 °C and 25 Hz in $0.05\%$ Triton X100-containing PBS using a tissue lyser (Qiagen TissueLyser II, Hilden, Germany). The protein and triglyceride content of the fly lysates were measured using a Pierce BCA Protein Assay Kit (Pierce Biotechnology, Rockford, IL, USA) and colorimetric assay reagent (GPO-PAP Kit, Dialab, Wiener Neudorf, Austria), respectively. ## 2.8. Statistics Statistical analyses were performed using the software GraphPad Prism (Ver. 7.05). The IC50 value of glucosidase inhibition by the post-fermented HI-rich extract was calculated using nonlinear regression. Prior to statistical tests, normal distribution of data was approved using the Shapiro–Wilk normality test. An analysis of variance (ANOVA) was conducted for α-amylase inhibition and in vivo fly data, followed by a post-hoc multiple comparison test of Dunnett to compare means of treatment with the post-fermented HI extract to the controls. Results from Ussing chamber experiments, CRP, FRAP and TEAC measurements were analyzed with two-sided unpaired Student’s t-tests. In cases without normally distributed data, non-parametric tests were applied. Data from the DPP4 inhibiting assay were tested using the Kruskal–Wallis test and the Dunn’s multiple comparison test. For secreted CRP protein level, the Mann–Whitney test was conducted. p-values less than 0.05 were considered significantly different. ## 3.1. Post-Fermented Hydroxy-Isoflavone (HI)-Rich Soybean Extract Exhibited Significant Inhibitory Activity towards α-Glucosidase and DPP4 In Vitro, but Not towards α-Amylase In order to test the ability of HI extracts to modulate carbohydrate-hydrolyzing enzymes in vitro, we first examined the influence on α-amylase activity. However, we did not observe a significant modulation of α-amylase enzyme activity by the post-fermented HI-rich extract up to a concentration of 10 mg/mL (Figure 3a). When we looked at the in vitro inhibition of α- glucosidase activity, we discovered a concentration-dependent inhibitory effect of the soy HI extract (Figure 3b). The IC50 value of the extract was estimated to be 78.6 μg/mL (R2: 0.985; $95\%$ confidence interval: 60.6–102 µg/mL). The soy HI extract was six times more potent than the positive control acarbose (IC50 = 493 µg/mL, R2: 0.973; $95\%$ confidence interval: 348–697 µg/mL) at inhibiting α-glucosidase activity. Furthermore, the HI extract inhibited the dipeptidyl peptidase activity of DPP4 in a dose-dependent manner (ANOVA: $p \leq 0.001$), leading to an approximately $60\%$ inhibition of enzyme activity at the highest concentration of 1 mg/mL when compared to controls (Figure 3c). A similar inhibition of DPP4 activity was achieved by the inhibitor control sitagliptin, but at a much lower concentration of 18 nM (this equates to 7.33 ng/mL). Thus, HI extract might serve only as a moderate inhibitor of DPP4 enzyme activity. ## 3.2. Pre- and Post-Fermented Soy Isoflavone Extracts Were Moderate Inhibitors of SGLT1-Mediated Glucose Transport To examine whether soy isoflavone extracts before (pre-) fermentation and HI-enriched after (post-) fermentation affect SGLT1-mediated glucose transport, we employed Ussing chamber experiments using the Caco-2/PD7 cell monolayer model. Representative runs are given in Figure 4a, c. Adding either pre- or post-fermented extract at a concentration of 1 mg/mL to the Ussing chamber system substantially lowered the glucose-induced short-circuit current from 6.90 ± 0.36 to 4.05 ± 0.66 µA/cm2 (pre-fermented extract) and from 7.45 ± 0.69 to 4.51 ± 0.63 µA/cm2 (post-fermented HI-rich extract), respectively (Figure 4d). This represents a SGLT1 inhibition of approximately $60\%$ for both extracts. In comparison, glucose uptake was almost completely blocked by the established SGLT1 inhibitor phlorizin at a concentration of 0.1 mM (Figure 4b). ## 3.3. Expression of C-Reactive Protein (CRP)-Coding mRNA and CRP Protein Secretion Were Reduced in Hep 3B Cells by Pre- and HI-Enriched Post-Fermented Soy Extract Incubation of Hep 3B cells with 10 µg/mL pre-fermented soy extract significantly inhibited the mRNA expression of the inflammatory marker CRP after IL1ß plus IL6 stimulation by ca. $30\%$ (Figure 5). An even more potent inhibition of ca. $60\%$ was observed by incubating the cells with post-fermented HI-rich extract (10 µg/mL). However, when analyzing the impact on the level of secreted protein, both pre- and post-fermented extracts significantly reduced the CRP concentration similarly by about $50\%$. ## 3.4. Post-Fermented HI-Rich Soy Extract Exhibited Higher Antioxidative Capacity Than Pre-Fermented Soy Extract We next tested the free radical scavenging properties of pre- or post-fermented soy extracts (10 µg/mL) by employing the ferric-reducing ability of plasma (FRAP) assay as well as the Trolox equivalent antioxidant capacity (TEAC) assay, respectively. As shown in Figure 6, in both cases the fermented soy extract with the increased HI content exhibited a significantly higher antioxidative capacity than the pre-fermented soy extract. ## 3.5. Supplementation of a High-Starch Drosophila Melanogaster Diet with Post-Fermented HI-Rich Extract Decreased the Triacylglyceride (TAG) Content of Female Fruit Flies Dietary supplementation of the $20\%$ starch-based diet with increasing concentrations of the post-fermented HI-rich extract led to a dose-dependent reduction of the triglyceride content in 10-day-old female flies (Figure 7). In flies fed $2.4\%$ of the post-fermented HI-rich extract, the TAG to protein ratio was found to be 0.36 compared to control animals which had a value of 0.51. The treatment with the positive control acarbose induced an even more drastic decline in lipid storage to a TAG to protein ratio of 0.08. ## 4. Discussion The prevalence of T2DM is growing globally; hence, controlling postprandial hyperglycemia and inflammation is central for halting disease progression. Soy isoflavones are believed to play a role in diabetes prevention [38]. The dietary intake of soy products has consistently been inversely associated with the risk of T2DM among women [39]. However, the underlying mechanisms and, in particular, the role of soy-derived HI in diabetes prevention remain unclear. By applying a portfolio of numerous in vitro assays related to various important steps within the glucose metabolism (from intestinal digestion to glucose uptake), as well as assessing potential anti-inflammatory properties, we have addressed this research question in the present study. Furthermore, we have included adequate positive controls (e.g., acarbose, sitaglibtin, phlorizin) in the respective assays. We have shown that a HI-enriched soy extract demonstrated inhibitory activity towards α-glucosidase, moderately reduced the DPP4 enzyme activity and significantly inhibited SGLT1-dependent glucose transport. Furthermore, the fermented HI-rich extract substantially decreased CRP mRNA and secreted protein levels in cultured Hep B3 hepatocytes. Thus, the HI-rich soy extract mediated antidiabetic properties by addressing multiple targets. Since we observed an inhibition of α-glucosidase but not α-amylase, HI may, nevertheless, exhibit a certain specificity as far as carbohydrate digesting enzymes are concerned. A shortcoming of our present experimental approach may be that we studied only the soy isoflavone-rich extracts (although analytically well characterized) but not their purified constituents, which should be taken into consideration in future studies. A decrease in intestinal glucose uptake could be an important mechanism in counteracting hyperglycemia [40]. Interestingly, we observed a significant inhibition of SGLT1 due to a HI-rich soy extract, as previously reported for other extracts rich in secondary plant metabolites [32,41]. We did not investigate whether the decrease in glucose uptake was mediated via a competitive inhibition of SGLT1. Phlorizin was used as a positive control in our Ussing chamber experiments. Thus, it would also be interesting to study whether there is a synergistic interaction between phlorizin and isoflavones/HI in terms of SGLT1 inhibition. Furthermore, other glucose transporters, such as Glut4, as a potential target of flavonoids [42] could be considered in response to the treatment with HI in additional studies. In terms of the SGLT1 assay, the fermented isoflavones did not show higher bioactivity than the unfermented extract as far as sodium-dependent glucose uptake was concerned. However, regarding anti-inflammatory properties, we observed a stronger inhibition of CRP gene expression in interleukin 1ß- and interleukin 6-stimulated hepatocytes in response to fermented versus unfermented isoflavones, whereas both extracts reduced the amount of secreted CRP protein to the same extent. Thus, fermentation may affect bioactivity in some but not all assays. Furthermore, it was unclear whether the inhibition of CRP gene expression was via a nuclear factor kappa B-controlled signal transduction pathway, as previously reported for the flavone quercetin in cultured hepatocytes [43]. We further observed a moderate inhibition of DPP4 activity due to HI in vitro. Our data were in line with previous studies indicating that prenyl isoflavones improve glucose homeostasis by inhibiting DPP4 in hyperglycemic rats in vivo [44]. Accordingly, genistein has been shown to inhibit DPP4 in diabetic laboratory mice. This bioactivity was accompanied by an enhanced GLP1 concentration [45], which was not monitored in the present study. However, we have validated the antidiabetic activity of the fermented HI-rich extract in a starch-based high-sugar diet model of D. melanogaster. High-sugar diets have been frequently demonstrated to lead to enhanced triglyceride levels in fruit flies [46,47,48]. By choosing starch as the sole carbohydrate source, we addressed all steps of the carbohydrate degradation pathway including the intestinal enzymes α-amylase and α-glucosidase. Therefore, we cannot currently assess which target molecule(s) is/are responsible for the triglyceride-lowering effect of the post-fermented HI-rich extract. Accordingly, further studies are necessary to clarify the precise in vivo mechanism of action. Overall, data from the present study and literature suggest that structural modifications of isoflavones, either through fermentation or endogenous metabolism, affect their pharmacological properties in terms of their bioactivity and possibly also their bioavailability [16]. The inclusion of additional hydroxyl groups into isoflavone molecules due to fermentation often enhances their bioactivity [23]. In contrast, sulfation [49] or glucuronidation [50], which mainly occur in the small intestine as well as in the liver, are associated with the loss of hydroxyl groups, and thereby decrease the bioactivity of isoflavones. Changes in the bioactivity through structural modifications were also evident in the case of the free radical scavenging activity of the post-fermented HI versus the pre-fermented soy extract. Thus, hydroxylation of isoflavones was accompanied with improved free radical scavenging properties, which has also been reported elsewhere for 8OHGen [25], 3OHDai [51], 6-hydroxyequol [52] and 8OHDai [53]. Accordingly, fermentation of soybean residues with R. oligosporus and L. plantarum resulted in an improved yield of isoflavone aglycones and gamma amino butyric acid, which led to lowered ROS levels and an increased antioxidative capacity, better blood glucose homeostasis and improved blood biochemistry in STZ-induced hyperglycemic mice [54]. Hence, we cannot fully exclude the possibility that beside HI, other ingredients could have contributed to the antidiabetic and anti-inflammatory effect, seen in our study. Improved free radical scavenging activity due to fermentation could also impact the food quality and shelf life of HI-rich soy derived food. Several efforts have been made to increase the bioavailability of isoflavones from soy beans, including the functional cloning of a soy isoflavone conjugate hydrolyzing β-glucosidase as a potential candidate for soy isoflavone bioavailability enhancement [16]. Although the bioavailability of genistein and daidzein has been studied in laboratory rodents [55,56], as well as in humans [57,58], little is known in terms of the bioavailability (e.g., plasma and tissue concentration) of HI including 8OHGen and 8OHGly. Nevertheless, it has been suggested that 8-OHDai is relatively easily absorbed in rats and distributed to peripheral tissues [59]. Such studies are necessary to evaluate whether the isoflavone concentrations used in in vitro studies are physiologically achievable under in vivo conditions. On the other hand, bioavailability was not an issue when isoflavones and HI inhibited intestinal targets, such as α-glucosidase and SGLT1,96 identified here. ## 5. Conclusions A soy isoflavone extract rich in 8-hydroxygenistein, 8-hydroxyglycitein and 8-hydroxydaidzein exhibited antidiabetic properties in vitro and in an in vivo diabetes model of Drosophila melanogaster. Such an extract may have the capability to serve as a dietary natural plant bioactive for prevention strategies in terms of T2DM. However, in the future, the potential antidiabetic and anti-inflammatory properties of HI need to be validated in laboratory rodents, as well as in human intervention studies, also taking their bioavailability into account. ## References 1. 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